6127 lines
449 KiB
Plaintext
6127 lines
449 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "c45428f2",
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||
"metadata": {},
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"source": [
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"This notebook is designed for ray integrations for signals\n",
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"\n",
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"lets load askbid candlesticks file."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"id": "2b5ebffa",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" .dataframe thead th {\n",
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" }\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
|
||
" <tr style=\"text-align: right;\">\n",
|
||
" <th></th>\n",
|
||
" <th>open</th>\n",
|
||
" <th>high</th>\n",
|
||
" <th>low</th>\n",
|
||
" <th>close</th>\n",
|
||
" <th>vol</th>\n",
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||
" <th>date</th>\n",
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" </tr>\n",
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" </thead>\n",
|
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" <tbody>\n",
|
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" <tr>\n",
|
||
" <th>0</th>\n",
|
||
" <td>0.67323</td>\n",
|
||
" <td>0.67351</td>\n",
|
||
" <td>0.67323</td>\n",
|
||
" <td>0.67351</td>\n",
|
||
" <td>21.50</td>\n",
|
||
" <td>2020-09-01 03:00:00+03:00</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>1</th>\n",
|
||
" <td>0.67349</td>\n",
|
||
" <td>0.67350</td>\n",
|
||
" <td>0.67349</td>\n",
|
||
" <td>0.67350</td>\n",
|
||
" <td>5.69</td>\n",
|
||
" <td>2020-09-01 03:00:05+03:00</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>2</th>\n",
|
||
" <td>0.67350</td>\n",
|
||
" <td>0.67350</td>\n",
|
||
" <td>0.67350</td>\n",
|
||
" <td>0.67350</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>2020-09-01 03:00:10+03:00</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>3</th>\n",
|
||
" <td>0.67355</td>\n",
|
||
" <td>0.67355</td>\n",
|
||
" <td>0.67351</td>\n",
|
||
" <td>0.67351</td>\n",
|
||
" <td>4.50</td>\n",
|
||
" <td>2020-09-01 03:00:15+03:00</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>4</th>\n",
|
||
" <td>0.67351</td>\n",
|
||
" <td>0.67352</td>\n",
|
||
" <td>0.67351</td>\n",
|
||
" <td>0.67352</td>\n",
|
||
" <td>7.00</td>\n",
|
||
" <td>2020-09-01 03:00:20+03:00</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>...</th>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" <td>...</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>380145</th>\n",
|
||
" <td>0.66212</td>\n",
|
||
" <td>0.66212</td>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>2.25</td>\n",
|
||
" <td>2020-10-01 02:58:45+03:00</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>380146</th>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>2020-10-01 02:58:50+03:00</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>380147</th>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>2020-10-01 02:58:55+03:00</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>380148</th>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.66209</td>\n",
|
||
" <td>0.00</td>\n",
|
||
" <td>2020-10-01 02:59:00+03:00</td>\n",
|
||
" </tr>\n",
|
||
" <tr>\n",
|
||
" <th>380149</th>\n",
|
||
" <td>0.66208</td>\n",
|
||
" <td>0.66208</td>\n",
|
||
" <td>0.66207</td>\n",
|
||
" <td>0.66207</td>\n",
|
||
" <td>4.00</td>\n",
|
||
" <td>2020-10-01 02:59:05+03:00</td>\n",
|
||
" </tr>\n",
|
||
" </tbody>\n",
|
||
"</table>\n",
|
||
"<p>380150 rows × 6 columns</p>\n",
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"</div>"
|
||
],
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"text/plain": [
|
||
" open high low close vol date\n",
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||
"0 0.67323 0.67351 0.67323 0.67351 21.50 2020-09-01 03:00:00+03:00\n",
|
||
"1 0.67349 0.67350 0.67349 0.67350 5.69 2020-09-01 03:00:05+03:00\n",
|
||
"2 0.67350 0.67350 0.67350 0.67350 0.00 2020-09-01 03:00:10+03:00\n",
|
||
"3 0.67355 0.67355 0.67351 0.67351 4.50 2020-09-01 03:00:15+03:00\n",
|
||
"4 0.67351 0.67352 0.67351 0.67352 7.00 2020-09-01 03:00:20+03:00\n",
|
||
"... ... ... ... ... ... ...\n",
|
||
"380145 0.66212 0.66212 0.66209 0.66209 2.25 2020-10-01 02:58:45+03:00\n",
|
||
"380146 0.66209 0.66209 0.66209 0.66209 0.00 2020-10-01 02:58:50+03:00\n",
|
||
"380147 0.66209 0.66209 0.66209 0.66209 0.00 2020-10-01 02:58:55+03:00\n",
|
||
"380148 0.66209 0.66209 0.66209 0.66209 0.00 2020-10-01 02:59:00+03:00\n",
|
||
"380149 0.66208 0.66208 0.66207 0.66207 4.00 2020-10-01 02:59:05+03:00\n",
|
||
"\n",
|
||
"[380150 rows x 6 columns]"
|
||
]
|
||
},
|
||
"execution_count": 20,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import market_trade.constants\n",
|
||
"import market_trade.dataloader\n",
|
||
"\n",
|
||
"candlesticks_filepaths = [filepath for filepath in market_trade.constants.CANDLESTICK_DATASETS_PATH.iterdir()]\n",
|
||
"candlesticks_filepath = candlesticks_filepaths[0]\n",
|
||
"duka_interface = market_trade.dataloader.DukaMTInterface(candlesticks_filepath)\n",
|
||
"duka_interface.bid_candlesticks"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "ae9c0943",
|
||
"metadata": {},
|
||
"source": [
|
||
"Let's test signal."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 21,
|
||
"id": "7f284ae6",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'chstota': -0.0021010505252626313,\n",
|
||
" 'zeroNum %': 0.8750375187593797,\n",
|
||
" 't %': 0.06143071535767884,\n",
|
||
" 'f %': 0.06353176588294147,\n",
|
||
" 'toch': 0.49159327461969576}"
|
||
]
|
||
},
|
||
"execution_count": 21,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"import market_trade.signals.Signal1\n",
|
||
"\n",
|
||
"bid_candlesticks_df = duka_interface.bid_candlesticks[:10000]\n",
|
||
"\n",
|
||
"ind_params = {'MeanType': 'SMA', 'window': 5, 'valueType': 'low', 'kDev': 2}\n",
|
||
"indEl1 = {\n",
|
||
" 'df': bid_candlesticks_df,\n",
|
||
" 'params': ind_params,\n",
|
||
" 'needFig': False,\n",
|
||
" 'showOnlyIndex': False,\n",
|
||
" 'drawFig': True\n",
|
||
"}\n",
|
||
"signal_result = market_trade.signals.Signal1.SignalBollingerBands1({'BB': indEl1})\n",
|
||
"signal_result.analiz"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "2f0acadd",
|
||
"metadata": {},
|
||
"source": [
|
||
"Now let's design ray trainable."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 22,
|
||
"id": "32624a56",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"def trainable(config):\n",
|
||
" ind_params = {'MeanType': 'SMA',\n",
|
||
" 'window': config['window'],\n",
|
||
" 'valueType': config['value_type'],\n",
|
||
" 'kDev': config['k_dev']}\n",
|
||
" indEl1 = {\n",
|
||
" 'df': bid_candlesticks_df,\n",
|
||
" 'params': ind_params,\n",
|
||
" 'needFig': False,\n",
|
||
" 'showOnlyIndex': False,\n",
|
||
" 'drawFig': True\n",
|
||
" }\n",
|
||
" signal_result = market_trade.signals.Signal1.SignalBollingerBands1({'BB': indEl1})\n",
|
||
" tune.report(accuracy=signal_result.analiz[\"toch\"])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "5e132728",
|
||
"metadata": {},
|
||
"source": [
|
||
"Let's create config space."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 23,
|
||
"id": "1ce577cf",
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"from ray import tune\n",
|
||
"\n",
|
||
"config = {\n",
|
||
" 'window': tune.qrandint(5,100,5),\n",
|
||
" 'value_type': tune.choice(['open', 'low', 'high', 'close']),\n",
|
||
" 'k_dev': tune.uniform(1,4)\n",
|
||
"}"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "2ddd8e0a",
|
||
"metadata": {},
|
||
"source": [
|
||
"Let's run ray tune"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 24,
|
||
"id": "067de743",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:33:51,021\tWARNING tune.py:636 -- Tune detects GPUs, but no trials are using GPUs. To enable trials to use GPUs, set tune.run(resources_per_trial={'gpu': 1}...) which allows Tune to expose 1 GPU to each trial. You can also override `Trainable.default_resource_request` if using the Trainable API.\n",
|
||
"2022-06-01 19:33:51,187\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00000\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:33:53 (running for 00:00:02.09)<br>Memory usage on this node: 10.8/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 1.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 16/100 (15 PENDING, 1 RUNNING)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>RUNNING </td><td>192.168.1.14:9985</td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00007</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.04865</td><td>close </td><td style=\"text-align: right;\"> 30</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00008</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.38263</td><td>high </td><td style=\"text-align: right;\"> 55</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00009</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.9824 </td><td>low </td><td style=\"text-align: right;\"> 95</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00010</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.96683</td><td>high </td><td style=\"text-align: right;\"> 95</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00011</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.36129</td><td>low </td><td style=\"text-align: right;\"> 5</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00012</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.81256</td><td>open </td><td style=\"text-align: right;\"> 15</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00013</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.80733</td><td>high </td><td style=\"text-align: right;\"> 35</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00014</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.52009</td><td>low </td><td style=\"text-align: right;\"> 65</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00015</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.5003 </td><td>high </td><td style=\"text-align: right;\"> 30</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br><br>"
|
||
],
|
||
"text/plain": [
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:33:53,205\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00001\n",
|
||
"2022-06-01 19:33:53,215\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00002\n",
|
||
"2022-06-01 19:33:53,228\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00003\n",
|
||
"2022-06-01 19:33:53,244\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00004\n",
|
||
"2022-06-01 19:33:53,262\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00005\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n",
|
||
"2022-06-01 19:33:53,326\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00006\n",
|
||
"2022-06-01 19:33:53,354\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00007\n",
|
||
"2022-06-01 19:33:53,386\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00008\n",
|
||
"2022-06-01 19:33:53,420\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00009\n",
|
||
"2022-06-01 19:33:53,458\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00010\n",
|
||
"2022-06-01 19:33:53,504\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00011\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:33:58 (running for 00:00:07.64)<br>Memory usage on this node: 12.1/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 28/100 (16 PENDING, 12 RUNNING)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>RUNNING </td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>RUNNING </td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>RUNNING </td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>RUNNING </td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>RUNNING </td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>RUNNING </td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>RUNNING </td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00007</td><td>RUNNING </td><td>192.168.1.14:10031</td><td style=\"text-align: right;\">2.04865</td><td>close </td><td style=\"text-align: right;\"> 30</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00008</td><td>RUNNING </td><td>192.168.1.14:10033</td><td style=\"text-align: right;\">2.38263</td><td>high </td><td style=\"text-align: right;\"> 55</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00009</td><td>RUNNING </td><td>192.168.1.14:10035</td><td style=\"text-align: right;\">2.9824 </td><td>low </td><td style=\"text-align: right;\"> 95</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00012</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.81256</td><td>open </td><td style=\"text-align: right;\"> 15</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00013</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.80733</td><td>high </td><td style=\"text-align: right;\"> 35</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00014</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.52009</td><td>low </td><td style=\"text-align: right;\"> 65</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00015</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.5003 </td><td>high </td><td style=\"text-align: right;\"> 30</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00016</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.82771</td><td>low </td><td style=\"text-align: right;\"> 70</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00017</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.9332 </td><td>high </td><td style=\"text-align: right;\"> 95</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00018</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.97031</td><td>open </td><td style=\"text-align: right;\"> 50</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00019</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.3669 </td><td>high </td><td style=\"text-align: right;\"> 20</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00020</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.2511 </td><td>high </td><td style=\"text-align: right;\"> 30</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00021</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.18569</td><td>open </td><td style=\"text-align: right;\"> 85</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 8 more trials not shown (2 RUNNING, 6 PENDING)<br><br>"
|
||
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|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:34:06 (running for 00:00:15.09)<br>Memory usage on this node: 12.0/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 28/100 (16 PENDING, 12 RUNNING)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th></tr>\n",
|
||
"</thead>\n",
|
||
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|
||
"<tr><td>trainable_9e7a8_00000</td><td>RUNNING </td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>RUNNING </td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>RUNNING </td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>RUNNING </td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>RUNNING </td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>RUNNING </td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>RUNNING </td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00007</td><td>RUNNING </td><td>192.168.1.14:10031</td><td style=\"text-align: right;\">2.04865</td><td>close </td><td style=\"text-align: right;\"> 30</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00008</td><td>RUNNING </td><td>192.168.1.14:10033</td><td style=\"text-align: right;\">2.38263</td><td>high </td><td style=\"text-align: right;\"> 55</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00009</td><td>RUNNING </td><td>192.168.1.14:10035</td><td style=\"text-align: right;\">2.9824 </td><td>low </td><td style=\"text-align: right;\"> 95</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00012</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.81256</td><td>open </td><td style=\"text-align: right;\"> 15</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00013</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.80733</td><td>high </td><td style=\"text-align: right;\"> 35</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00014</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.52009</td><td>low </td><td style=\"text-align: right;\"> 65</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00015</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.5003 </td><td>high </td><td style=\"text-align: right;\"> 30</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00016</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.82771</td><td>low </td><td style=\"text-align: right;\"> 70</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00017</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.9332 </td><td>high </td><td style=\"text-align: right;\"> 95</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00018</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.97031</td><td>open </td><td style=\"text-align: right;\"> 50</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00019</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.3669 </td><td>high </td><td style=\"text-align: right;\"> 20</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00020</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.2511 </td><td>high </td><td style=\"text-align: right;\"> 30</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00021</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.18569</td><td>open </td><td style=\"text-align: right;\"> 85</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 8 more trials not shown (2 RUNNING, 6 PENDING)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00000:\n",
|
||
" accuracy: 0.46153846153846156\n",
|
||
" date: 2022-06-01_19-34-06\n",
|
||
" done: false\n",
|
||
" experiment_id: dd508a19143b4ab0b6b5466494a701e5\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 9985\n",
|
||
" time_since_restore: 13.739934206008911\n",
|
||
" time_this_iter_s: 13.739934206008911\n",
|
||
" time_total_s: 13.739934206008911\n",
|
||
" timestamp: 1654101246\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00000\n",
|
||
" warmup_time: 0.0024194717407226562\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00000:\n",
|
||
" accuracy: 0.46153846153846156\n",
|
||
" date: 2022-06-01_19-34-06\n",
|
||
" done: true\n",
|
||
" experiment_id: dd508a19143b4ab0b6b5466494a701e5\n",
|
||
" experiment_tag: 0_k_dev=3.5873,value_type=close,window=30\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 9985\n",
|
||
" time_since_restore: 13.739934206008911\n",
|
||
" time_this_iter_s: 13.739934206008911\n",
|
||
" time_total_s: 13.739934206008911\n",
|
||
" timestamp: 1654101246\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00000\n",
|
||
" warmup_time: 0.0024194717407226562\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:34:08,271\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00012\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00003:\n",
|
||
" accuracy: 0.49736842105263157\n",
|
||
" date: 2022-06-01_19-34-11\n",
|
||
" done: false\n",
|
||
" experiment_id: 97f33c5e76b746f7a765446ab2136149\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10023\n",
|
||
" time_since_restore: 13.583420276641846\n",
|
||
" time_this_iter_s: 13.583420276641846\n",
|
||
" time_total_s: 13.583420276641846\n",
|
||
" timestamp: 1654101251\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00003\n",
|
||
" warmup_time: 0.005610227584838867\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:34:12 (running for 00:00:21.76)<br>Memory usage on this node: 12.1/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00003 with accuracy=0.49736842105263157 and parameters={'window': 40, 'value_type': 'low', 'k_dev': 2.407825494050322}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 29/100 (16 PENDING, 12 RUNNING, 1 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>RUNNING </td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>RUNNING </td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>RUNNING </td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>RUNNING </td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>RUNNING </td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>RUNNING </td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00007</td><td>RUNNING </td><td>192.168.1.14:10031</td><td style=\"text-align: right;\">2.04865</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00008</td><td>RUNNING </td><td>192.168.1.14:10033</td><td style=\"text-align: right;\">2.38263</td><td>high </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00009</td><td>RUNNING </td><td>192.168.1.14:10035</td><td style=\"text-align: right;\">2.9824 </td><td>low </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00010</td><td>RUNNING </td><td>192.168.1.14:10036</td><td style=\"text-align: right;\">1.96683</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00013</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.80733</td><td>high </td><td style=\"text-align: right;\"> 35</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00014</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.52009</td><td>low </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00015</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.5003 </td><td>high </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00016</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.82771</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00017</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.9332 </td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00018</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.97031</td><td>open </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00019</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.3669 </td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00020</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.2511 </td><td>high </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00021</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.18569</td><td>open </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00022</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.9816 </td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 9 more trials not shown (2 RUNNING, 6 PENDING)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00010:\n",
|
||
" accuracy: 0.4887169568020632\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: false\n",
|
||
" experiment_id: 21171a81f97e4ceab4a2ebf418342710\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10036\n",
|
||
" time_since_restore: 14.459006547927856\n",
|
||
" time_this_iter_s: 14.459006547927856\n",
|
||
" time_total_s: 14.459006547927856\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00010\n",
|
||
" warmup_time: 0.004714012145996094\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00001:\n",
|
||
" accuracy: 0.5070921985815603\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: false\n",
|
||
" experiment_id: 500dd4a950e04521aa8c39510d3e2709\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10019\n",
|
||
" time_since_restore: 14.583298921585083\n",
|
||
" time_this_iter_s: 14.583298921585083\n",
|
||
" time_total_s: 14.583298921585083\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00001\n",
|
||
" warmup_time: 0.004272937774658203\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00007:\n",
|
||
" accuracy: 0.4906779661016949\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: true\n",
|
||
" experiment_id: ad1f045cecba4e5cb33d6ca9bc8cc914\n",
|
||
" experiment_tag: 7_k_dev=2.0486,value_type=close,window=30\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10031\n",
|
||
" time_since_restore: 14.571169137954712\n",
|
||
" time_this_iter_s: 14.571169137954712\n",
|
||
" time_total_s: 14.571169137954712\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00007\n",
|
||
" warmup_time: 0.005751132965087891\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00001:\n",
|
||
" accuracy: 0.5070921985815603\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: true\n",
|
||
" experiment_id: 500dd4a950e04521aa8c39510d3e2709\n",
|
||
" experiment_tag: 1_k_dev=2.9955,value_type=high,window=90\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10019\n",
|
||
" time_since_restore: 14.583298921585083\n",
|
||
" time_this_iter_s: 14.583298921585083\n",
|
||
" time_total_s: 14.583298921585083\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00001\n",
|
||
" warmup_time: 0.004272937774658203\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00010:\n",
|
||
" accuracy: 0.4887169568020632\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: true\n",
|
||
" experiment_id: 21171a81f97e4ceab4a2ebf418342710\n",
|
||
" experiment_tag: 10_k_dev=1.9668,value_type=high,window=95\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10036\n",
|
||
" time_since_restore: 14.459006547927856\n",
|
||
" time_this_iter_s: 14.459006547927856\n",
|
||
" time_total_s: 14.459006547927856\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00010\n",
|
||
" warmup_time: 0.004714012145996094\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00002:\n",
|
||
" accuracy: 0.5043478260869565\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: false\n",
|
||
" experiment_id: 05aea56bd6ec4c9aac43da9b333d30c7\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10021\n",
|
||
" time_since_restore: 15.037883758544922\n",
|
||
" time_this_iter_s: 15.037883758544922\n",
|
||
" time_total_s: 15.037883758544922\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00002\n",
|
||
" warmup_time: 0.007447481155395508\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00009:\n",
|
||
" accuracy: 0.5460992907801419\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: true\n",
|
||
" experiment_id: c0b2e38985174caf8330b6972f808605\n",
|
||
" experiment_tag: 9_k_dev=2.9824,value_type=low,window=95\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10035\n",
|
||
" time_since_restore: 13.997156858444214\n",
|
||
" time_this_iter_s: 13.997156858444214\n",
|
||
" time_total_s: 13.997156858444214\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00009\n",
|
||
" warmup_time: 0.005003213882446289\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00002:\n",
|
||
" accuracy: 0.5043478260869565\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: true\n",
|
||
" experiment_id: 05aea56bd6ec4c9aac43da9b333d30c7\n",
|
||
" experiment_tag: 2_k_dev=3.9129,value_type=high,window=20\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10021\n",
|
||
" time_since_restore: 15.037883758544922\n",
|
||
" time_this_iter_s: 15.037883758544922\n",
|
||
" time_total_s: 15.037883758544922\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00002\n",
|
||
" warmup_time: 0.007447481155395508\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00006:\n",
|
||
" accuracy: 0.48802190280629704\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: false\n",
|
||
" experiment_id: 28f8355c59bb4338b01419a9080f85e2\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10029\n",
|
||
" time_since_restore: 14.945950508117676\n",
|
||
" time_this_iter_s: 14.945950508117676\n",
|
||
" time_total_s: 14.945950508117676\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00006\n",
|
||
" warmup_time: 0.0067691802978515625\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00005:\n",
|
||
" accuracy: 0.5173210161662818\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: false\n",
|
||
" experiment_id: 842dab8d618c46ceb905e1a829daef52\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10026\n",
|
||
" time_since_restore: 14.724257707595825\n",
|
||
" time_this_iter_s: 14.724257707595825\n",
|
||
" time_total_s: 14.724257707595825\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00005\n",
|
||
" warmup_time: 0.004319906234741211\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00004:\n",
|
||
" accuracy: 0.48586118251928023\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: true\n",
|
||
" experiment_id: f3c82d32277a4d99ad52e7e1cfec7d67\n",
|
||
" experiment_tag: 4_k_dev=2.8374,value_type=high,window=95\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10025\n",
|
||
" time_since_restore: 14.679120779037476\n",
|
||
" time_this_iter_s: 14.679120779037476\n",
|
||
" time_total_s: 14.679120779037476\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00004\n",
|
||
" warmup_time: 0.0037331581115722656\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00005:\n",
|
||
" accuracy: 0.5173210161662818\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: true\n",
|
||
" experiment_id: 842dab8d618c46ceb905e1a829daef52\n",
|
||
" experiment_tag: 5_k_dev=2.7833,value_type=open,window=70\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10026\n",
|
||
" time_since_restore: 14.724257707595825\n",
|
||
" time_this_iter_s: 14.724257707595825\n",
|
||
" time_total_s: 14.724257707595825\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00005\n",
|
||
" warmup_time: 0.004319906234741211\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00006:\n",
|
||
" accuracy: 0.48802190280629704\n",
|
||
" date: 2022-06-01_19-34-12\n",
|
||
" done: true\n",
|
||
" experiment_id: 28f8355c59bb4338b01419a9080f85e2\n",
|
||
" experiment_tag: 6_k_dev=2.0225,value_type=low,window=90\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10029\n",
|
||
" time_since_restore: 14.945950508117676\n",
|
||
" time_this_iter_s: 14.945950508117676\n",
|
||
" time_total_s: 14.945950508117676\n",
|
||
" timestamp: 1654101252\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00006\n",
|
||
" warmup_time: 0.0067691802978515625\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00008:\n",
|
||
" accuracy: 0.46082337317397076\n",
|
||
" date: 2022-06-01_19-34-13\n",
|
||
" done: false\n",
|
||
" experiment_id: addc5a22af734fffa198efb2005acd93\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10033\n",
|
||
" time_since_restore: 14.97620677947998\n",
|
||
" time_this_iter_s: 14.97620677947998\n",
|
||
" time_total_s: 14.97620677947998\n",
|
||
" timestamp: 1654101253\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00008\n",
|
||
" warmup_time: 0.00495600700378418\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00008:\n",
|
||
" accuracy: 0.46082337317397076\n",
|
||
" date: 2022-06-01_19-34-13\n",
|
||
" done: true\n",
|
||
" experiment_id: addc5a22af734fffa198efb2005acd93\n",
|
||
" experiment_tag: 8_k_dev=2.3826,value_type=high,window=55\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10033\n",
|
||
" time_since_restore: 14.97620677947998\n",
|
||
" time_this_iter_s: 14.97620677947998\n",
|
||
" time_total_s: 14.97620677947998\n",
|
||
" timestamp: 1654101253\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00008\n",
|
||
" warmup_time: 0.00495600700378418\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00011:\n",
|
||
" accuracy: 0.46779767514923026\n",
|
||
" date: 2022-06-01_19-34-13\n",
|
||
" done: false\n",
|
||
" experiment_id: 2b1c06fad9df4861aac65670c0d0e137\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10038\n",
|
||
" time_since_restore: 15.24082326889038\n",
|
||
" time_this_iter_s: 15.24082326889038\n",
|
||
" time_total_s: 15.24082326889038\n",
|
||
" timestamp: 1654101253\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00011\n",
|
||
" warmup_time: 0.007975101470947266\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00011:\n",
|
||
" accuracy: 0.46779767514923026\n",
|
||
" date: 2022-06-01_19-34-13\n",
|
||
" done: true\n",
|
||
" experiment_id: 2b1c06fad9df4861aac65670c0d0e137\n",
|
||
" experiment_tag: 11_k_dev=1.3613,value_type=low,window=5\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10038\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" warmup_time: 0.007975101470947266\n",
|
||
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|
||
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|
||
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|
||
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|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:34:14,762\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00013\n",
|
||
"2022-06-01 19:34:14,782\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00014\n",
|
||
"2022-06-01 19:34:14,803\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00015\n",
|
||
"2022-06-01 19:34:14,821\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00016\n",
|
||
"2022-06-01 19:34:14,842\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00017\n",
|
||
"2022-06-01 19:34:14,873\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00018\n",
|
||
"2022-06-01 19:34:14,897\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00019\n",
|
||
"2022-06-01 19:34:14,921\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00020\n",
|
||
"2022-06-01 19:34:14,949\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00021\n",
|
||
"2022-06-01 19:34:14,992\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00022\n",
|
||
"2022-06-01 19:34:15,042\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00023\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
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|
||
"== Status ==<br>Current time: 2022-06-01 19:34:21 (running for 00:00:30.37)<br>Memory usage on this node: 12.3/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00009 with accuracy=0.5460992907801419 and parameters={'window': 95, 'value_type': 'low', 'k_dev': 2.982399582158353}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 40/100 (16 PENDING, 12 RUNNING, 12 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00012</td><td>RUNNING </td><td>192.168.1.14:10448</td><td style=\"text-align: right;\">3.81256</td><td>open </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00013</td><td>RUNNING </td><td>192.168.1.14:10694</td><td style=\"text-align: right;\">1.80733</td><td>high </td><td style=\"text-align: right;\"> 35</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00014</td><td>RUNNING </td><td>192.168.1.14:10705</td><td style=\"text-align: right;\">1.52009</td><td>low </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00015</td><td>RUNNING </td><td>192.168.1.14:10718</td><td style=\"text-align: right;\">1.5003 </td><td>high </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00016</td><td>RUNNING </td><td>192.168.1.14:10738</td><td style=\"text-align: right;\">3.82771</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00017</td><td>RUNNING </td><td>192.168.1.14:10791</td><td style=\"text-align: right;\">2.9332 </td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00018</td><td>RUNNING </td><td>192.168.1.14:10820</td><td style=\"text-align: right;\">1.97031</td><td>open </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00024</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.37796</td><td>open </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00025</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.76634</td><td>open </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00026</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.58155</td><td>low </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00027</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.00967</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00028</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.50349</td><td>low </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00029</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.12407</td><td>open </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00030</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.93617</td><td>high </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 20 more trials not shown (5 RUNNING, 9 PENDING, 5 TERMINATED)<br><br>"
|
||
],
|
||
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|
||
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||
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|
||
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|
||
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|
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00012:\n",
|
||
" accuracy: 0.5121107266435986\n",
|
||
" date: 2022-06-01_19-34-26\n",
|
||
" done: false\n",
|
||
" experiment_id: 1a22fe6f70954d6b9088455ee5c20962\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
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|
||
" pid: 10448\n",
|
||
" time_since_restore: 14.0254967212677\n",
|
||
" time_this_iter_s: 14.0254967212677\n",
|
||
" time_total_s: 14.0254967212677\n",
|
||
" timestamp: 1654101266\n",
|
||
" timesteps_since_restore: 0\n",
|
||
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|
||
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|
||
" warmup_time: 0.002529621124267578\n",
|
||
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|
||
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|
||
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|
||
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|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:34:26 (running for 00:00:35.80)<br>Memory usage on this node: 12.2/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00009 with accuracy=0.5460992907801419 and parameters={'window': 95, 'value_type': 'low', 'k_dev': 2.982399582158353}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 40/100 (16 PENDING, 12 RUNNING, 12 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00012</td><td>RUNNING </td><td>192.168.1.14:10448</td><td style=\"text-align: right;\">3.81256</td><td>open </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.0255</td><td style=\"text-align: right;\"> 0.512111</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00013</td><td>RUNNING </td><td>192.168.1.14:10694</td><td style=\"text-align: right;\">1.80733</td><td>high </td><td style=\"text-align: right;\"> 35</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00014</td><td>RUNNING </td><td>192.168.1.14:10705</td><td style=\"text-align: right;\">1.52009</td><td>low </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00015</td><td>RUNNING </td><td>192.168.1.14:10718</td><td style=\"text-align: right;\">1.5003 </td><td>high </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00016</td><td>RUNNING </td><td>192.168.1.14:10738</td><td style=\"text-align: right;\">3.82771</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00017</td><td>RUNNING </td><td>192.168.1.14:10791</td><td style=\"text-align: right;\">2.9332 </td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00018</td><td>RUNNING </td><td>192.168.1.14:10820</td><td style=\"text-align: right;\">1.97031</td><td>open </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00024</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.37796</td><td>open </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00025</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.76634</td><td>open </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00026</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.58155</td><td>low </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00027</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.00967</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00028</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.50349</td><td>low </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00029</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.12407</td><td>open </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00030</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.93617</td><td>high </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 20 more trials not shown (5 RUNNING, 9 PENDING, 5 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00012:\n",
|
||
" accuracy: 0.5121107266435986\n",
|
||
" date: 2022-06-01_19-34-26\n",
|
||
" done: true\n",
|
||
" experiment_id: 1a22fe6f70954d6b9088455ee5c20962\n",
|
||
" experiment_tag: 12_k_dev=3.8126,value_type=open,window=15\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10448\n",
|
||
" time_since_restore: 14.0254967212677\n",
|
||
" time_this_iter_s: 14.0254967212677\n",
|
||
" time_total_s: 14.0254967212677\n",
|
||
" timestamp: 1654101266\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00012\n",
|
||
" warmup_time: 0.002529621124267578\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:34:27,867\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00024\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:34:32 (running for 00:00:41.90)<br>Memory usage on this node: 12.2/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00009 with accuracy=0.5460992907801419 and parameters={'window': 95, 'value_type': 'low', 'k_dev': 2.982399582158353}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 41/100 (16 PENDING, 12 RUNNING, 13 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00013</td><td>RUNNING </td><td>192.168.1.14:10694</td><td style=\"text-align: right;\">1.80733</td><td>high </td><td style=\"text-align: right;\"> 35</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00014</td><td>RUNNING </td><td>192.168.1.14:10705</td><td style=\"text-align: right;\">1.52009</td><td>low </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00015</td><td>RUNNING </td><td>192.168.1.14:10718</td><td style=\"text-align: right;\">1.5003 </td><td>high </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00016</td><td>RUNNING </td><td>192.168.1.14:10738</td><td style=\"text-align: right;\">3.82771</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00017</td><td>RUNNING </td><td>192.168.1.14:10791</td><td style=\"text-align: right;\">2.9332 </td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00018</td><td>RUNNING </td><td>192.168.1.14:10820</td><td style=\"text-align: right;\">1.97031</td><td>open </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00019</td><td>RUNNING </td><td>192.168.1.14:10826</td><td style=\"text-align: right;\">3.3669 </td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00025</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.76634</td><td>open </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00026</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.58155</td><td>low </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00027</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.00967</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00028</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.50349</td><td>low </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00029</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.12407</td><td>open </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00030</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.93617</td><td>high </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00031</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.56237</td><td>high </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 21 more trials not shown (5 RUNNING, 9 PENDING, 6 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00019:\n",
|
||
" accuracy: 0.5130434782608696\n",
|
||
" date: 2022-06-01_19-34-33\n",
|
||
" done: false\n",
|
||
" experiment_id: d96c80c310fa4d4da89a3dd1e96a2d10\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10826\n",
|
||
" time_since_restore: 13.773784160614014\n",
|
||
" time_this_iter_s: 13.773784160614014\n",
|
||
" time_total_s: 13.773784160614014\n",
|
||
" timestamp: 1654101273\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00019\n",
|
||
" warmup_time: 0.006046295166015625\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00019:\n",
|
||
" accuracy: 0.5130434782608696\n",
|
||
" date: 2022-06-01_19-34-33\n",
|
||
" done: true\n",
|
||
" experiment_id: d96c80c310fa4d4da89a3dd1e96a2d10\n",
|
||
" experiment_tag: 19_k_dev=3.3669,value_type=high,window=20\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10826\n",
|
||
" time_since_restore: 13.773784160614014\n",
|
||
" time_this_iter_s: 13.773784160614014\n",
|
||
" time_total_s: 13.773784160614014\n",
|
||
" timestamp: 1654101273\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00019\n",
|
||
" warmup_time: 0.006046295166015625\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:34:35,042\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00025\n",
|
||
"2022-06-01 19:34:35,076\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00026\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00016:\n",
|
||
" accuracy: 0.5555555555555556\n",
|
||
" date: 2022-06-01_19-34-34\n",
|
||
" done: false\n",
|
||
" experiment_id: 7f00783cf5514779a1f37a0ee620c5f9\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10738\n",
|
||
" time_since_restore: 15.381575345993042\n",
|
||
" time_this_iter_s: 15.381575345993042\n",
|
||
" time_total_s: 15.381575345993042\n",
|
||
" timestamp: 1654101274\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00016\n",
|
||
" warmup_time: 0.005811214447021484\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00016:\n",
|
||
" accuracy: 0.5555555555555556\n",
|
||
" date: 2022-06-01_19-34-34\n",
|
||
" done: true\n",
|
||
" experiment_id: 7f00783cf5514779a1f37a0ee620c5f9\n",
|
||
" experiment_tag: 16_k_dev=3.8277,value_type=low,window=70\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10738\n",
|
||
" time_since_restore: 15.381575345993042\n",
|
||
" time_this_iter_s: 15.381575345993042\n",
|
||
" time_total_s: 15.381575345993042\n",
|
||
" timestamp: 1654101274\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00016\n",
|
||
" warmup_time: 0.005811214447021484\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00013:\n",
|
||
" accuracy: 0.4691780821917808\n",
|
||
" date: 2022-06-01_19-34-35\n",
|
||
" done: false\n",
|
||
" experiment_id: 6c52b00a8a8c4056b09e0bd0c60ed9b2\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10694\n",
|
||
" time_since_restore: 15.529388189315796\n",
|
||
" time_this_iter_s: 15.529388189315796\n",
|
||
" time_total_s: 15.529388189315796\n",
|
||
" timestamp: 1654101275\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00013\n",
|
||
" warmup_time: 0.007336616516113281\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00013:\n",
|
||
" accuracy: 0.4691780821917808\n",
|
||
" date: 2022-06-01_19-34-35\n",
|
||
" done: true\n",
|
||
" experiment_id: 6c52b00a8a8c4056b09e0bd0c60ed9b2\n",
|
||
" experiment_tag: 13_k_dev=1.8073,value_type=high,window=35\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10694\n",
|
||
" time_since_restore: 15.529388189315796\n",
|
||
" time_this_iter_s: 15.529388189315796\n",
|
||
" time_total_s: 15.529388189315796\n",
|
||
" timestamp: 1654101275\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00013\n",
|
||
" warmup_time: 0.007336616516113281\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:34:35,964\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00027\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00018:\n",
|
||
" accuracy: 0.4855562384757222\n",
|
||
" date: 2022-06-01_19-34-35\n",
|
||
" done: false\n",
|
||
" experiment_id: bbd1c2b5b2664d6fb2788ed0f94d3966\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10820\n",
|
||
" time_since_restore: 15.152493000030518\n",
|
||
" time_this_iter_s: 15.152493000030518\n",
|
||
" time_total_s: 15.152493000030518\n",
|
||
" timestamp: 1654101275\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00018\n",
|
||
" warmup_time: 0.008821725845336914\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00018:\n",
|
||
" accuracy: 0.4855562384757222\n",
|
||
" date: 2022-06-01_19-34-35\n",
|
||
" done: true\n",
|
||
" experiment_id: bbd1c2b5b2664d6fb2788ed0f94d3966\n",
|
||
" experiment_tag: 18_k_dev=1.9703,value_type=open,window=50\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10820\n",
|
||
" time_since_restore: 15.152493000030518\n",
|
||
" time_this_iter_s: 15.152493000030518\n",
|
||
" time_total_s: 15.152493000030518\n",
|
||
" timestamp: 1654101275\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00018\n",
|
||
" warmup_time: 0.008821725845336914\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00014:\n",
|
||
" accuracy: 0.47731691510045365\n",
|
||
" date: 2022-06-01_19-34-35\n",
|
||
" done: false\n",
|
||
" experiment_id: 98c2ddc8e35644379aa67b29a3854518\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10705\n",
|
||
" time_since_restore: 16.20167064666748\n",
|
||
" time_this_iter_s: 16.20167064666748\n",
|
||
" time_total_s: 16.20167064666748\n",
|
||
" timestamp: 1654101275\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00014\n",
|
||
" warmup_time: 0.005467653274536133\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00014:\n",
|
||
" accuracy: 0.47731691510045365\n",
|
||
" date: 2022-06-01_19-34-35\n",
|
||
" done: true\n",
|
||
" experiment_id: 98c2ddc8e35644379aa67b29a3854518\n",
|
||
" experiment_tag: 14_k_dev=1.5201,value_type=low,window=65\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10705\n",
|
||
" time_since_restore: 16.20167064666748\n",
|
||
" time_this_iter_s: 16.20167064666748\n",
|
||
" time_total_s: 16.20167064666748\n",
|
||
" timestamp: 1654101275\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00014\n",
|
||
" warmup_time: 0.005467653274536133\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:34:36,008\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00028\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00017:\n",
|
||
" accuracy: 0.4887459807073955\n",
|
||
" date: 2022-06-01_19-34-36\n",
|
||
" done: false\n",
|
||
" experiment_id: 124fd42fb2be4130bfb31bce3955b460\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10791\n",
|
||
" time_since_restore: 15.400557518005371\n",
|
||
" time_this_iter_s: 15.400557518005371\n",
|
||
" time_total_s: 15.400557518005371\n",
|
||
" timestamp: 1654101276\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00017\n",
|
||
" warmup_time: 0.007220745086669922\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00017:\n",
|
||
" accuracy: 0.4887459807073955\n",
|
||
" date: 2022-06-01_19-34-36\n",
|
||
" done: true\n",
|
||
" experiment_id: 124fd42fb2be4130bfb31bce3955b460\n",
|
||
" experiment_tag: 17_k_dev=2.9332,value_type=high,window=95\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10791\n",
|
||
" time_since_restore: 15.400557518005371\n",
|
||
" time_this_iter_s: 15.400557518005371\n",
|
||
" time_total_s: 15.400557518005371\n",
|
||
" timestamp: 1654101276\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00017\n",
|
||
" warmup_time: 0.007220745086669922\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00022:\n",
|
||
" accuracy: 0.5232974910394266\n",
|
||
" date: 2022-06-01_19-34-36\n",
|
||
" done: false\n",
|
||
" experiment_id: 1ed3ffcd32a54b43b15fadb717fa8b03\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10851\n",
|
||
" time_since_restore: 16.078017473220825\n",
|
||
" time_this_iter_s: 16.078017473220825\n",
|
||
" time_total_s: 16.078017473220825\n",
|
||
" timestamp: 1654101276\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00022\n",
|
||
" warmup_time: 0.010663270950317383\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00022:\n",
|
||
" accuracy: 0.5232974910394266\n",
|
||
" date: 2022-06-01_19-34-36\n",
|
||
" done: true\n",
|
||
" experiment_id: 1ed3ffcd32a54b43b15fadb717fa8b03\n",
|
||
" experiment_tag: 22_k_dev=2.9816,value_type=low,window=40\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10851\n",
|
||
" time_since_restore: 16.078017473220825\n",
|
||
" time_this_iter_s: 16.078017473220825\n",
|
||
" time_total_s: 16.078017473220825\n",
|
||
" timestamp: 1654101276\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00022\n",
|
||
" warmup_time: 0.010663270950317383\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:34:36,935\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00029\n",
|
||
"2022-06-01 19:34:36,974\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00030\n",
|
||
"2022-06-01 19:34:37,004\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00031\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00015:\n",
|
||
" accuracy: 0.46335927367055774\n",
|
||
" date: 2022-06-01_19-34-36\n",
|
||
" done: false\n",
|
||
" experiment_id: e84d4c0d12a249888656f4d05d0ca15e\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10718\n",
|
||
" time_since_restore: 17.18942403793335\n",
|
||
" time_this_iter_s: 17.18942403793335\n",
|
||
" time_total_s: 17.18942403793335\n",
|
||
" timestamp: 1654101276\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00015\n",
|
||
" warmup_time: 0.006697416305541992\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00015:\n",
|
||
" accuracy: 0.46335927367055774\n",
|
||
" date: 2022-06-01_19-34-36\n",
|
||
" done: true\n",
|
||
" experiment_id: e84d4c0d12a249888656f4d05d0ca15e\n",
|
||
" experiment_tag: 15_k_dev=1.5003,value_type=high,window=30\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10718\n",
|
||
" time_since_restore: 17.18942403793335\n",
|
||
" time_this_iter_s: 17.18942403793335\n",
|
||
" time_total_s: 17.18942403793335\n",
|
||
" timestamp: 1654101276\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00015\n",
|
||
" warmup_time: 0.006697416305541992\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00021:\n",
|
||
" accuracy: 0.4594293357111012\n",
|
||
" date: 2022-06-01_19-34-37\n",
|
||
" done: false\n",
|
||
" experiment_id: 1030124ef9d242f59f71b692f6ea69b2\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10832\n",
|
||
" time_since_restore: 17.364789485931396\n",
|
||
" time_this_iter_s: 17.364789485931396\n",
|
||
" time_total_s: 17.364789485931396\n",
|
||
" timestamp: 1654101277\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00021\n",
|
||
" warmup_time: 0.006062030792236328\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00021:\n",
|
||
" accuracy: 0.4594293357111012\n",
|
||
" date: 2022-06-01_19-34-37\n",
|
||
" done: true\n",
|
||
" experiment_id: 1030124ef9d242f59f71b692f6ea69b2\n",
|
||
" experiment_tag: 21_k_dev=1.1857,value_type=open,window=85\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10832\n",
|
||
" time_since_restore: 17.364789485931396\n",
|
||
" time_this_iter_s: 17.364789485931396\n",
|
||
" time_total_s: 17.364789485931396\n",
|
||
" timestamp: 1654101277\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00021\n",
|
||
" warmup_time: 0.006062030792236328\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00020:\n",
|
||
" accuracy: 0.4541328236980411\n",
|
||
" date: 2022-06-01_19-34-37\n",
|
||
" done: false\n",
|
||
" experiment_id: a960db88989a4dd68719193685d3bae9\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10827\n",
|
||
" time_since_restore: 17.48743748664856\n",
|
||
" time_this_iter_s: 17.48743748664856\n",
|
||
" time_total_s: 17.48743748664856\n",
|
||
" timestamp: 1654101277\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00020\n",
|
||
" warmup_time: 0.00461578369140625\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00020:\n",
|
||
" accuracy: 0.4541328236980411\n",
|
||
" date: 2022-06-01_19-34-37\n",
|
||
" done: true\n",
|
||
" experiment_id: a960db88989a4dd68719193685d3bae9\n",
|
||
" experiment_tag: 20_k_dev=1.2511,value_type=high,window=30\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10827\n",
|
||
" time_since_restore: 17.48743748664856\n",
|
||
" time_this_iter_s: 17.48743748664856\n",
|
||
" time_total_s: 17.48743748664856\n",
|
||
" timestamp: 1654101277\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00020\n",
|
||
" warmup_time: 0.00461578369140625\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:34:41 (running for 00:00:50.22)<br>Memory usage on this node: 12.0/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 9.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00016 with accuracy=0.5555555555555556 and parameters={'window': 70, 'value_type': 'low', 'k_dev': 3.8277095850346097}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 48/100 (16 PENDING, 9 RUNNING, 23 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00023</td><td>RUNNING </td><td>192.168.1.14:10853</td><td style=\"text-align: right;\">1.12381</td><td>close </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00024</td><td>RUNNING </td><td>192.168.1.14:11212</td><td style=\"text-align: right;\">2.37796</td><td>open </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00025</td><td>RUNNING </td><td>192.168.1.14:11277</td><td style=\"text-align: right;\">3.76634</td><td>open </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00026</td><td>RUNNING </td><td>192.168.1.14:11278</td><td style=\"text-align: right;\">1.58155</td><td>low </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00027</td><td>RUNNING </td><td>192.168.1.14:11283</td><td style=\"text-align: right;\">2.00967</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00028</td><td>RUNNING </td><td>192.168.1.14:11286</td><td style=\"text-align: right;\">3.50349</td><td>low </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00029</td><td>RUNNING </td><td>192.168.1.14:11365</td><td style=\"text-align: right;\">3.12407</td><td>open </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00032</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.71263</td><td>close </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00033</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.61494</td><td>close </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00034</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.25605</td><td>open </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00035</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.19443</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00036</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.10051</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00037</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.1924 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00038</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.33683</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 28 more trials not shown (2 RUNNING, 9 PENDING, 16 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:34:41,582\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00032\n",
|
||
"2022-06-01 19:34:41,628\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00033\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00023:\n",
|
||
" accuracy: 0.4529396921524098\n",
|
||
" date: 2022-06-01_19-34-38\n",
|
||
" done: false\n",
|
||
" experiment_id: 6675f1f46eaf4e10a950e564e24a23e6\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10853\n",
|
||
" time_since_restore: 17.483032703399658\n",
|
||
" time_this_iter_s: 17.483032703399658\n",
|
||
" time_total_s: 17.483032703399658\n",
|
||
" timestamp: 1654101278\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00023\n",
|
||
" warmup_time: 0.007616519927978516\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00023:\n",
|
||
" accuracy: 0.4529396921524098\n",
|
||
" date: 2022-06-01_19-34-38\n",
|
||
" done: true\n",
|
||
" experiment_id: 6675f1f46eaf4e10a950e564e24a23e6\n",
|
||
" experiment_tag: 23_k_dev=1.1238,value_type=close,window=10\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 10853\n",
|
||
" time_since_restore: 17.483032703399658\n",
|
||
" time_this_iter_s: 17.483032703399658\n",
|
||
" time_total_s: 17.483032703399658\n",
|
||
" timestamp: 1654101278\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00023\n",
|
||
" warmup_time: 0.007616519927978516\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:34:41,962\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00034\n",
|
||
"2022-06-01 19:34:42,005\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00035\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00024:\n",
|
||
" accuracy: 0.49518716577540106\n",
|
||
" date: 2022-06-01_19-34-45\n",
|
||
" done: false\n",
|
||
" experiment_id: 82ae1d7ce6ee493e8675bce3d400fc7a\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11212\n",
|
||
" time_since_restore: 13.099290132522583\n",
|
||
" time_this_iter_s: 13.099290132522583\n",
|
||
" time_total_s: 13.099290132522583\n",
|
||
" timestamp: 1654101285\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00024\n",
|
||
" warmup_time: 0.004574775695800781\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
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|
||
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|
||
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|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:34:47 (running for 00:00:56.56)<br>Memory usage on this node: 12.3/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00016 with accuracy=0.5555555555555556 and parameters={'window': 70, 'value_type': 'low', 'k_dev': 3.8277095850346097}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 52/100 (16 PENDING, 12 RUNNING, 24 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00024</td><td>RUNNING </td><td>192.168.1.14:11212</td><td style=\"text-align: right;\">2.37796</td><td>open </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.0993</td><td style=\"text-align: right;\"> 0.495187</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00025</td><td>RUNNING </td><td>192.168.1.14:11277</td><td style=\"text-align: right;\">3.76634</td><td>open </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00026</td><td>RUNNING </td><td>192.168.1.14:11278</td><td style=\"text-align: right;\">1.58155</td><td>low </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00027</td><td>RUNNING </td><td>192.168.1.14:11283</td><td style=\"text-align: right;\">2.00967</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00028</td><td>RUNNING </td><td>192.168.1.14:11286</td><td style=\"text-align: right;\">3.50349</td><td>low </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00029</td><td>RUNNING </td><td>192.168.1.14:11365</td><td style=\"text-align: right;\">3.12407</td><td>open </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00030</td><td>RUNNING </td><td>192.168.1.14:11367</td><td style=\"text-align: right;\">2.93617</td><td>high </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00036</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.10051</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00037</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.1924 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00038</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.33683</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00039</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.42366</td><td>open </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00040</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.82909</td><td>low </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00041</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.00435</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00042</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.13066</td><td>close </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 32 more trials not shown (5 RUNNING, 9 PENDING, 17 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00024:\n",
|
||
" accuracy: 0.49518716577540106\n",
|
||
" date: 2022-06-01_19-34-45\n",
|
||
" done: true\n",
|
||
" experiment_id: 82ae1d7ce6ee493e8675bce3d400fc7a\n",
|
||
" experiment_tag: 24_k_dev=2.378,value_type=open,window=30\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11212\n",
|
||
" time_since_restore: 13.099290132522583\n",
|
||
" time_this_iter_s: 13.099290132522583\n",
|
||
" time_total_s: 13.099290132522583\n",
|
||
" timestamp: 1654101285\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00024\n",
|
||
" warmup_time: 0.004574775695800781\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:34:49,045\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00036\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00025:\n",
|
||
" accuracy: 0.5394736842105263\n",
|
||
" date: 2022-06-01_19-34-53\n",
|
||
" done: false\n",
|
||
" experiment_id: 47cb2440acab44fd822ed5089c6e9c49\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11277\n",
|
||
" time_since_restore: 14.249480247497559\n",
|
||
" time_this_iter_s: 14.249480247497559\n",
|
||
" time_total_s: 14.249480247497559\n",
|
||
" timestamp: 1654101293\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00025\n",
|
||
" warmup_time: 0.00903463363647461\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:34:54 (running for 00:01:03.01)<br>Memory usage on this node: 12.3/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00016 with accuracy=0.5555555555555556 and parameters={'window': 70, 'value_type': 'low', 'k_dev': 3.8277095850346097}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 53/100 (16 PENDING, 12 RUNNING, 25 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00025</td><td>RUNNING </td><td>192.168.1.14:11277</td><td style=\"text-align: right;\">3.76634</td><td>open </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.2495</td><td style=\"text-align: right;\"> 0.539474</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00026</td><td>RUNNING </td><td>192.168.1.14:11278</td><td style=\"text-align: right;\">1.58155</td><td>low </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00027</td><td>RUNNING </td><td>192.168.1.14:11283</td><td style=\"text-align: right;\">2.00967</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00028</td><td>RUNNING </td><td>192.168.1.14:11286</td><td style=\"text-align: right;\">3.50349</td><td>low </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00029</td><td>RUNNING </td><td>192.168.1.14:11365</td><td style=\"text-align: right;\">3.12407</td><td>open </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00030</td><td>RUNNING </td><td>192.168.1.14:11367</td><td style=\"text-align: right;\">2.93617</td><td>high </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00031</td><td>RUNNING </td><td>192.168.1.14:11369</td><td style=\"text-align: right;\">2.56237</td><td>high </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00037</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.1924 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00038</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.33683</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00039</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.42366</td><td>open </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00040</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.82909</td><td>low </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00041</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.00435</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00042</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.13066</td><td>close </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00043</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.78005</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 33 more trials not shown (5 RUNNING, 9 PENDING, 18 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
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|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00028:\n",
|
||
" accuracy: 0.5204081632653061\n",
|
||
" date: 2022-06-01_19-34-53\n",
|
||
" done: false\n",
|
||
" experiment_id: 0882929c199d4878b9b117a5abddf001\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11286\n",
|
||
" time_since_restore: 13.5071702003479\n",
|
||
" time_this_iter_s: 13.5071702003479\n",
|
||
" time_total_s: 13.5071702003479\n",
|
||
" timestamp: 1654101293\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00028\n",
|
||
" warmup_time: 0.0036194324493408203\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00027:\n",
|
||
" accuracy: 0.49630624580255206\n",
|
||
" date: 2022-06-01_19-34-53\n",
|
||
" done: false\n",
|
||
" experiment_id: eda8276c93f247629c8ac087b30d2382\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11283\n",
|
||
" time_since_restore: 14.29230809211731\n",
|
||
" time_this_iter_s: 14.29230809211731\n",
|
||
" time_total_s: 14.29230809211731\n",
|
||
" timestamp: 1654101293\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00027\n",
|
||
" warmup_time: 0.004743337631225586\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00027:\n",
|
||
" accuracy: 0.49630624580255206\n",
|
||
" date: 2022-06-01_19-34-53\n",
|
||
" done: true\n",
|
||
" experiment_id: eda8276c93f247629c8ac087b30d2382\n",
|
||
" experiment_tag: 27_k_dev=2.0097,value_type=open,window=90\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11283\n",
|
||
" time_since_restore: 14.29230809211731\n",
|
||
" time_this_iter_s: 14.29230809211731\n",
|
||
" time_total_s: 14.29230809211731\n",
|
||
" timestamp: 1654101293\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00027\n",
|
||
" warmup_time: 0.004743337631225586\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00028:\n",
|
||
" accuracy: 0.5204081632653061\n",
|
||
" date: 2022-06-01_19-34-53\n",
|
||
" done: true\n",
|
||
" experiment_id: 0882929c199d4878b9b117a5abddf001\n",
|
||
" experiment_tag: 28_k_dev=3.5035,value_type=low,window=60\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11286\n",
|
||
" time_since_restore: 13.5071702003479\n",
|
||
" time_this_iter_s: 13.5071702003479\n",
|
||
" time_total_s: 13.5071702003479\n",
|
||
" timestamp: 1654101293\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00028\n",
|
||
" warmup_time: 0.0036194324493408203\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00025:\n",
|
||
" accuracy: 0.5394736842105263\n",
|
||
" date: 2022-06-01_19-34-53\n",
|
||
" done: true\n",
|
||
" experiment_id: 47cb2440acab44fd822ed5089c6e9c49\n",
|
||
" experiment_tag: 25_k_dev=3.7663,value_type=open,window=80\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11277\n",
|
||
" time_since_restore: 14.249480247497559\n",
|
||
" time_this_iter_s: 14.249480247497559\n",
|
||
" time_total_s: 14.249480247497559\n",
|
||
" timestamp: 1654101293\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00025\n",
|
||
" warmup_time: 0.00903463363647461\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00026:\n",
|
||
" accuracy: 0.4725121781489214\n",
|
||
" date: 2022-06-01_19-34-54\n",
|
||
" done: false\n",
|
||
" experiment_id: c28c935754aa4f2fa230eff702a30abc\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11278\n",
|
||
" time_since_restore: 15.291823148727417\n",
|
||
" time_this_iter_s: 15.291823148727417\n",
|
||
" time_total_s: 15.291823148727417\n",
|
||
" timestamp: 1654101294\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00026\n",
|
||
" warmup_time: 0.00337982177734375\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00026:\n",
|
||
" accuracy: 0.4725121781489214\n",
|
||
" date: 2022-06-01_19-34-54\n",
|
||
" done: true\n",
|
||
" experiment_id: c28c935754aa4f2fa230eff702a30abc\n",
|
||
" experiment_tag: 26_k_dev=1.5816,value_type=low,window=85\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11278\n",
|
||
" time_since_restore: 15.291823148727417\n",
|
||
" time_this_iter_s: 15.291823148727417\n",
|
||
" time_total_s: 15.291823148727417\n",
|
||
" timestamp: 1654101294\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00026\n",
|
||
" warmup_time: 0.00337982177734375\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00029:\n",
|
||
" accuracy: 0.5289256198347108\n",
|
||
" date: 2022-06-01_19-34-55\n",
|
||
" done: false\n",
|
||
" experiment_id: 605e41d8d7964989b2abc019fe9caecf\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11365\n",
|
||
" time_since_restore: 14.431620359420776\n",
|
||
" time_this_iter_s: 14.431620359420776\n",
|
||
" time_total_s: 14.431620359420776\n",
|
||
" timestamp: 1654101295\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00029\n",
|
||
" warmup_time: 0.0033860206604003906\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00029:\n",
|
||
" accuracy: 0.5289256198347108\n",
|
||
" date: 2022-06-01_19-34-55\n",
|
||
" done: true\n",
|
||
" experiment_id: 605e41d8d7964989b2abc019fe9caecf\n",
|
||
" experiment_tag: 29_k_dev=3.1241,value_type=open,window=65\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11365\n",
|
||
" time_since_restore: 14.431620359420776\n",
|
||
" time_this_iter_s: 14.431620359420776\n",
|
||
" time_total_s: 14.431620359420776\n",
|
||
" timestamp: 1654101295\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00029\n",
|
||
" warmup_time: 0.0033860206604003906\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00031:\n",
|
||
" accuracy: 0.45229007633587787\n",
|
||
" date: 2022-06-01_19-34-55\n",
|
||
" done: false\n",
|
||
" experiment_id: 9515ffaf5067434cb2a8800410bfd04b\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11369\n",
|
||
" time_since_restore: 14.678828954696655\n",
|
||
" time_this_iter_s: 14.678828954696655\n",
|
||
" time_total_s: 14.678828954696655\n",
|
||
" timestamp: 1654101295\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00031\n",
|
||
" warmup_time: 0.0055849552154541016\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00031:\n",
|
||
" accuracy: 0.45229007633587787\n",
|
||
" date: 2022-06-01_19-34-55\n",
|
||
" done: true\n",
|
||
" experiment_id: 9515ffaf5067434cb2a8800410bfd04b\n",
|
||
" experiment_tag: 31_k_dev=2.5624,value_type=high,window=40\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11369\n",
|
||
" time_since_restore: 14.678828954696655\n",
|
||
" time_this_iter_s: 14.678828954696655\n",
|
||
" time_total_s: 14.678828954696655\n",
|
||
" timestamp: 1654101295\n",
|
||
" timesteps_since_restore: 0\n",
|
||
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|
||
" trial_id: 9e7a8_00031\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"2022-06-01 19:34:55,863\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00037\n",
|
||
"2022-06-01 19:34:55,902\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00038\n",
|
||
"2022-06-01 19:34:55,926\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00039\n",
|
||
"2022-06-01 19:34:55,959\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00040\n",
|
||
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|
||
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|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00030:\n",
|
||
" accuracy: 0.4820717131474104\n",
|
||
" date: 2022-06-01_19-34-56\n",
|
||
" done: false\n",
|
||
" experiment_id: b3c577e7d4ba4e2a84ec8035ccdf983e\n",
|
||
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|
||
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||
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||
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|
||
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|
||
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||
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|
||
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|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00030\n",
|
||
" warmup_time: 0.005486965179443359\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00030:\n",
|
||
" accuracy: 0.4820717131474104\n",
|
||
" date: 2022-06-01_19-34-56\n",
|
||
" done: true\n",
|
||
" experiment_id: b3c577e7d4ba4e2a84ec8035ccdf983e\n",
|
||
" experiment_tag: 30_k_dev=2.9362,value_type=high,window=60\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
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|
||
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|
||
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|
||
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||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"2022-06-01 19:34:56,966\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00043\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
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||
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|
||
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|
||
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|
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|
||
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|
||
"== Status ==<br>Current time: 2022-06-01 19:35:02 (running for 00:01:11.19)<br>Memory usage on this node: 12.6/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00016 with accuracy=0.5555555555555556 and parameters={'window': 70, 'value_type': 'low', 'k_dev': 3.8277095850346097}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 60/100 (16 PENDING, 12 RUNNING, 32 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00032</td><td>RUNNING </td><td>192.168.1.14:11542</td><td style=\"text-align: right;\">2.71263</td><td>close </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.4148</td><td style=\"text-align: right;\"> 0.505119</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00033</td><td>RUNNING </td><td>192.168.1.14:11545</td><td style=\"text-align: right;\">1.61494</td><td>close </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00034</td><td>RUNNING </td><td>192.168.1.14:11548</td><td style=\"text-align: right;\">2.25605</td><td>open </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00035</td><td>RUNNING </td><td>192.168.1.14:11549</td><td style=\"text-align: right;\">1.19443</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00036</td><td>RUNNING </td><td>192.168.1.14:11705</td><td style=\"text-align: right;\">2.10051</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00037</td><td>RUNNING </td><td>192.168.1.14:11803</td><td style=\"text-align: right;\">2.1924 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00038</td><td>RUNNING </td><td>192.168.1.14:11820</td><td style=\"text-align: right;\">3.33683</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00044</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.43104</td><td>close </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00045</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.24024</td><td>open </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00046</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.34936</td><td>open </td><td style=\"text-align: right;\"> 5</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00047</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.95935</td><td>open </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00048</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.62893</td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00049</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.98399</td><td>close </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00050</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.40408</td><td>close </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 40 more trials not shown (5 RUNNING, 9 PENDING, 25 TERMINATED)<br><br>"
|
||
],
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"name": "stderr",
|
||
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|
||
"text": [
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
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|
||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00033:\n",
|
||
" accuracy: 0.48287506029908345\n",
|
||
" date: 2022-06-01_19-35-01\n",
|
||
" done: true\n",
|
||
" experiment_id: 72a7abc2eb9146ba8e5c09212fbaa3fa\n",
|
||
" experiment_tag: 33_k_dev=1.6149,value_type=close,window=15\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11545\n",
|
||
" time_since_restore: 15.1469144821167\n",
|
||
" time_this_iter_s: 15.1469144821167\n",
|
||
" time_total_s: 15.1469144821167\n",
|
||
" timestamp: 1654101301\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00033\n",
|
||
" warmup_time: 0.0038747787475585938\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00034:\n",
|
||
" accuracy: 0.49657198824681686\n",
|
||
" date: 2022-06-01_19-35-03\n",
|
||
" done: false\n",
|
||
" experiment_id: 4752525a18c7492e9fc6d6f0a50502d7\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11548\n",
|
||
" time_since_restore: 15.908806800842285\n",
|
||
" time_this_iter_s: 15.908806800842285\n",
|
||
" time_total_s: 15.908806800842285\n",
|
||
" timestamp: 1654101303\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00034\n",
|
||
" warmup_time: 0.009506464004516602\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00034:\n",
|
||
" accuracy: 0.49657198824681686\n",
|
||
" date: 2022-06-01_19-35-03\n",
|
||
" done: true\n",
|
||
" experiment_id: 4752525a18c7492e9fc6d6f0a50502d7\n",
|
||
" experiment_tag: 34_k_dev=2.256,value_type=open,window=75\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11548\n",
|
||
" time_since_restore: 15.908806800842285\n",
|
||
" time_this_iter_s: 15.908806800842285\n",
|
||
" time_total_s: 15.908806800842285\n",
|
||
" timestamp: 1654101303\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00034\n",
|
||
" warmup_time: 0.009506464004516602\n",
|
||
" \n"
|
||
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|
||
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|
||
{
|
||
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|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:35:04,071\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00044\n",
|
||
"2022-06-01 19:35:04,112\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00045\n",
|
||
"2022-06-01 19:35:04,160\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00046\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00035:\n",
|
||
" accuracy: 0.45585874799357945\n",
|
||
" date: 2022-06-01_19-35-05\n",
|
||
" done: false\n",
|
||
" experiment_id: 1694cadd332843a6a40865444a843b6a\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11549\n",
|
||
" time_since_restore: 17.696004152297974\n",
|
||
" time_this_iter_s: 17.696004152297974\n",
|
||
" time_total_s: 17.696004152297974\n",
|
||
" timestamp: 1654101305\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00035\n",
|
||
" warmup_time: 0.016307592391967773\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00035:\n",
|
||
" accuracy: 0.45585874799357945\n",
|
||
" date: 2022-06-01_19-35-05\n",
|
||
" done: true\n",
|
||
" experiment_id: 1694cadd332843a6a40865444a843b6a\n",
|
||
" experiment_tag: 35_k_dev=1.1944,value_type=high,window=95\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11549\n",
|
||
" time_since_restore: 17.696004152297974\n",
|
||
" time_this_iter_s: 17.696004152297974\n",
|
||
" time_total_s: 17.696004152297974\n",
|
||
" timestamp: 1654101305\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00035\n",
|
||
" warmup_time: 0.016307592391967773\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:35:05,969\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00047\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
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||
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"== Status ==<br>Current time: 2022-06-01 19:35:11 (running for 00:01:20.30)<br>Memory usage on this node: 12.6/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00016 with accuracy=0.5555555555555556 and parameters={'window': 70, 'value_type': 'low', 'k_dev': 3.8277095850346097}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 63/100 (15 PENDING, 12 RUNNING, 36 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
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|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00036</td><td>RUNNING </td><td>192.168.1.14:11705</td><td style=\"text-align: right;\">2.10051</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00037</td><td>RUNNING </td><td>192.168.1.14:11803</td><td style=\"text-align: right;\">2.1924 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00038</td><td>RUNNING </td><td>192.168.1.14:11820</td><td style=\"text-align: right;\">3.33683</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00039</td><td>RUNNING </td><td>192.168.1.14:11834</td><td style=\"text-align: right;\">2.42366</td><td>open </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00040</td><td>RUNNING </td><td>192.168.1.14:11842</td><td style=\"text-align: right;\">3.82909</td><td>low </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00041</td><td>RUNNING </td><td>192.168.1.14:11844</td><td style=\"text-align: right;\">1.00435</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00042</td><td>RUNNING </td><td>192.168.1.14:11858</td><td style=\"text-align: right;\">2.13066</td><td>close </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00048</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.62893</td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00049</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.98399</td><td>close </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00050</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.40408</td><td>close </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00051</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.63469</td><td>open </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00052</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.55978</td><td>close </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00053</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.58736</td><td>high </td><td style=\"text-align: right;\"> 35</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00054</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.46559</td><td>low </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 43 more trials not shown (5 RUNNING, 8 PENDING, 29 TERMINATED)<br><br>"
|
||
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|
||
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|
||
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|
||
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|
||
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|
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
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|
||
"text": [
|
||
"Result for trainable_9e7a8_00036:\n",
|
||
" accuracy: 0.4790732436472347\n",
|
||
" date: 2022-06-01_19-35-09\n",
|
||
" done: false\n",
|
||
" experiment_id: daa35894c08f4289a2c2a28ba28251e5\n",
|
||
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|
||
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|
||
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|
||
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|
||
" time_since_restore: 15.722806215286255\n",
|
||
" time_this_iter_s: 15.722806215286255\n",
|
||
" time_total_s: 15.722806215286255\n",
|
||
" timestamp: 1654101309\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00036\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"== Status ==<br>Current time: 2022-06-01 19:35:11 (running for 00:01:20.57)<br>Memory usage on this node: 12.6/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00016 with accuracy=0.5555555555555556 and parameters={'window': 70, 'value_type': 'low', 'k_dev': 3.8277095850346097}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 64/100 (16 PENDING, 12 RUNNING, 36 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00036</td><td>RUNNING </td><td>192.168.1.14:11705</td><td style=\"text-align: right;\">2.10051</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.7228</td><td style=\"text-align: right;\"> 0.479073</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00037</td><td>RUNNING </td><td>192.168.1.14:11803</td><td style=\"text-align: right;\">2.1924 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00038</td><td>RUNNING </td><td>192.168.1.14:11820</td><td style=\"text-align: right;\">3.33683</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00039</td><td>RUNNING </td><td>192.168.1.14:11834</td><td style=\"text-align: right;\">2.42366</td><td>open </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00040</td><td>RUNNING </td><td>192.168.1.14:11842</td><td style=\"text-align: right;\">3.82909</td><td>low </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00041</td><td>RUNNING </td><td>192.168.1.14:11844</td><td style=\"text-align: right;\">1.00435</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00042</td><td>RUNNING </td><td>192.168.1.14:11858</td><td style=\"text-align: right;\">2.13066</td><td>close </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00048</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.62893</td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00049</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.98399</td><td>close </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00050</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.40408</td><td>close </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00051</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.63469</td><td>open </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00052</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.55978</td><td>close </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00053</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.58736</td><td>high </td><td style=\"text-align: right;\"> 35</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00054</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.46559</td><td>low </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 44 more trials not shown (5 RUNNING, 9 PENDING, 29 TERMINATED)<br><br>"
|
||
],
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00036:\n",
|
||
" accuracy: 0.4790732436472347\n",
|
||
" date: 2022-06-01_19-35-09\n",
|
||
" done: true\n",
|
||
" experiment_id: daa35894c08f4289a2c2a28ba28251e5\n",
|
||
" experiment_tag: 36_k_dev=2.1005,value_type=open,window=70\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
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|
||
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|
||
" time_since_restore: 15.722806215286255\n",
|
||
" time_this_iter_s: 15.722806215286255\n",
|
||
" time_total_s: 15.722806215286255\n",
|
||
" timestamp: 1654101309\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00036\n",
|
||
" warmup_time: 0.003968477249145508\n",
|
||
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|
||
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|
||
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|
||
{
|
||
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|
||
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|
||
"text": [
|
||
"2022-06-01 19:35:13,191\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00048\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00040:\n",
|
||
" accuracy: 0.5271317829457365\n",
|
||
" date: 2022-06-01_19-35-15\n",
|
||
" done: false\n",
|
||
" experiment_id: d0c8ead9b7334dc2bd05e36c89dff5ce\n",
|
||
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|
||
" iterations_since_restore: 1\n",
|
||
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|
||
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|
||
" time_since_restore: 14.479460716247559\n",
|
||
" time_this_iter_s: 14.479460716247559\n",
|
||
" time_total_s: 14.479460716247559\n",
|
||
" timestamp: 1654101315\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00040\n",
|
||
" warmup_time: 0.005458354949951172\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00040:\n",
|
||
" accuracy: 0.5271317829457365\n",
|
||
" date: 2022-06-01_19-35-15\n",
|
||
" done: true\n",
|
||
" experiment_id: d0c8ead9b7334dc2bd05e36c89dff5ce\n",
|
||
" experiment_tag: 40_k_dev=3.8291,value_type=low,window=20\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11842\n",
|
||
" time_since_restore: 14.479460716247559\n",
|
||
" time_this_iter_s: 14.479460716247559\n",
|
||
" time_total_s: 14.479460716247559\n",
|
||
" timestamp: 1654101315\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00040\n",
|
||
" warmup_time: 0.005458354949951172\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00039:\n",
|
||
" accuracy: 0.511318242343542\n",
|
||
" date: 2022-06-01_19-35-16\n",
|
||
" done: false\n",
|
||
" experiment_id: 1d557ac66ae446f38f38ec0b8b245ba5\n",
|
||
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|
||
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|
||
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|
||
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|
||
" time_since_restore: 15.016530990600586\n",
|
||
" time_this_iter_s: 15.016530990600586\n",
|
||
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||
" timestamp: 1654101316\n",
|
||
" timesteps_since_restore: 0\n",
|
||
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|
||
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|
||
" warmup_time: 0.010867118835449219\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00039:\n",
|
||
" accuracy: 0.511318242343542\n",
|
||
" date: 2022-06-01_19-35-16\n",
|
||
" done: true\n",
|
||
" experiment_id: 1d557ac66ae446f38f38ec0b8b245ba5\n",
|
||
" experiment_tag: 39_k_dev=2.4237,value_type=open,window=95\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
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|
||
" time_since_restore: 15.016530990600586\n",
|
||
" time_this_iter_s: 15.016530990600586\n",
|
||
" time_total_s: 15.016530990600586\n",
|
||
" timestamp: 1654101316\n",
|
||
" timesteps_since_restore: 0\n",
|
||
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|
||
" trial_id: 9e7a8_00039\n",
|
||
" warmup_time: 0.010867118835449219\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00042:\n",
|
||
" accuracy: 0.48770894788593905\n",
|
||
" date: 2022-06-01_19-35-16\n",
|
||
" done: false\n",
|
||
" experiment_id: 4edf9b8f4ead4bd98ff0831e874863e4\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11858\n",
|
||
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|
||
" time_this_iter_s: 15.049045085906982\n",
|
||
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|
||
" timestamp: 1654101316\n",
|
||
" timesteps_since_restore: 0\n",
|
||
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|
||
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|
||
" warmup_time: 0.013311624526977539\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00042:\n",
|
||
" accuracy: 0.48770894788593905\n",
|
||
" date: 2022-06-01_19-35-16\n",
|
||
" done: true\n",
|
||
" experiment_id: 4edf9b8f4ead4bd98ff0831e874863e4\n",
|
||
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|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
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|
||
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|
||
" time_this_iter_s: 15.049045085906982\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" warmup_time: 0.013311624526977539\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00038:\n",
|
||
" accuracy: 0.5743243243243243\n",
|
||
" date: 2022-06-01_19-35-16\n",
|
||
" done: false\n",
|
||
" experiment_id: a266d42f6f4e4e519b19fd62c9a6bd09\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11820\n",
|
||
" time_since_restore: 15.951253652572632\n",
|
||
" time_this_iter_s: 15.951253652572632\n",
|
||
" time_total_s: 15.951253652572632\n",
|
||
" timestamp: 1654101316\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00038\n",
|
||
" warmup_time: 0.0055162906646728516\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00038:\n",
|
||
" accuracy: 0.5743243243243243\n",
|
||
" date: 2022-06-01_19-35-16\n",
|
||
" done: true\n",
|
||
" experiment_id: a266d42f6f4e4e519b19fd62c9a6bd09\n",
|
||
" experiment_tag: 38_k_dev=3.3368,value_type=low,window=80\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11820\n",
|
||
" time_since_restore: 15.951253652572632\n",
|
||
" time_this_iter_s: 15.951253652572632\n",
|
||
" time_total_s: 15.951253652572632\n",
|
||
" timestamp: 1654101316\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00038\n",
|
||
" warmup_time: 0.0055162906646728516\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00037:\n",
|
||
" accuracy: 0.48705179282868527\n",
|
||
" date: 2022-06-01_19-35-16\n",
|
||
" done: false\n",
|
||
" experiment_id: 23e9a939b7b341639e36eaf7352b4ff6\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11803\n",
|
||
" time_since_restore: 15.124496698379517\n",
|
||
" time_this_iter_s: 15.124496698379517\n",
|
||
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|
||
" timestamp: 1654101316\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00037\n",
|
||
" warmup_time: 0.006184577941894531\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00037:\n",
|
||
" accuracy: 0.48705179282868527\n",
|
||
" date: 2022-06-01_19-35-16\n",
|
||
" done: true\n",
|
||
" experiment_id: 23e9a939b7b341639e36eaf7352b4ff6\n",
|
||
" experiment_tag: 37_k_dev=2.1924,value_type=close,window=80\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11803\n",
|
||
" time_since_restore: 15.124496698379517\n",
|
||
" time_this_iter_s: 15.124496698379517\n",
|
||
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|
||
" timestamp: 1654101316\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00037\n",
|
||
" warmup_time: 0.006184577941894531\n",
|
||
" \n"
|
||
]
|
||
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|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:35:16,693\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00049\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
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|
||
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|
||
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|
||
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|
||
"data": {
|
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"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:35:20 (running for 00:01:29.34)<br>Memory usage on this node: 12.2/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 8.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00038 with accuracy=0.5743243243243243 and parameters={'window': 80, 'value_type': 'low', 'k_dev': 3.3368279156307263}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 65/100 (15 PENDING, 8 RUNNING, 42 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00041</td><td>RUNNING </td><td>192.168.1.14:11844</td><td style=\"text-align: right;\">1.00435</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00043</td><td>RUNNING </td><td>192.168.1.14:11860</td><td style=\"text-align: right;\">3.78005</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00044</td><td>RUNNING </td><td>192.168.1.14:12123</td><td style=\"text-align: right;\">1.43104</td><td>close </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00045</td><td>RUNNING </td><td>192.168.1.14:12141</td><td style=\"text-align: right;\">2.24024</td><td>open </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00046</td><td>RUNNING </td><td>192.168.1.14:12145</td><td style=\"text-align: right;\">2.34936</td><td>open </td><td style=\"text-align: right;\"> 5</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00047</td><td>RUNNING </td><td>192.168.1.14:12223</td><td style=\"text-align: right;\">3.95935</td><td>open </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00048</td><td>RUNNING </td><td>192.168.1.14:12304</td><td style=\"text-align: right;\">2.62893</td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00050</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.40408</td><td>close </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00051</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.63469</td><td>open </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00052</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.55978</td><td>close </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00053</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.58736</td><td>high </td><td style=\"text-align: right;\"> 35</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00054</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.46559</td><td>low </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00055</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.74483</td><td>high </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00056</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.93169</td><td>open </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 45 more trials not shown (1 RUNNING, 8 PENDING, 35 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
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|
||
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|
||
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|
||
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|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:35:20,517\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00050\n",
|
||
"2022-06-01 19:35:20,531\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00051\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n",
|
||
"2022-06-01 19:35:20,609\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00052\n",
|
||
"2022-06-01 19:35:20,660\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00053\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00041:\n",
|
||
" accuracy: 0.4559420801695215\n",
|
||
" date: 2022-06-01_19-35-18\n",
|
||
" done: false\n",
|
||
" experiment_id: 4e3a01830cf74d4bbacde00caf0acf99\n",
|
||
" hostname: parf\n",
|
||
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|
||
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|
||
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|
||
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|
||
" time_this_iter_s: 17.168471574783325\n",
|
||
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|
||
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|
||
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|
||
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|
||
" trial_id: 9e7a8_00041\n",
|
||
" warmup_time: 0.006995439529418945\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00043:\n",
|
||
" accuracy: 0.55\n",
|
||
" date: 2022-06-01_19-35-17\n",
|
||
" done: false\n",
|
||
" experiment_id: 750e296811534dfb971470074e788537\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" time_this_iter_s: 14.797376871109009\n",
|
||
" time_total_s: 14.797376871109009\n",
|
||
" timestamp: 1654101317\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00043\n",
|
||
" warmup_time: 0.005739450454711914\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00041:\n",
|
||
" accuracy: 0.4559420801695215\n",
|
||
" date: 2022-06-01_19-35-18\n",
|
||
" done: true\n",
|
||
" experiment_id: 4e3a01830cf74d4bbacde00caf0acf99\n",
|
||
" experiment_tag: 41_k_dev=1.0043,value_type=low,window=40\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11844\n",
|
||
" time_since_restore: 17.168471574783325\n",
|
||
" time_this_iter_s: 17.168471574783325\n",
|
||
" time_total_s: 17.168471574783325\n",
|
||
" timestamp: 1654101318\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00041\n",
|
||
" warmup_time: 0.006995439529418945\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00043:\n",
|
||
" accuracy: 0.55\n",
|
||
" date: 2022-06-01_19-35-17\n",
|
||
" done: true\n",
|
||
" experiment_id: 750e296811534dfb971470074e788537\n",
|
||
" experiment_tag: 43_k_dev=3.78,value_type=low,window=70\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 11860\n",
|
||
" time_since_restore: 14.797376871109009\n",
|
||
" time_this_iter_s: 14.797376871109009\n",
|
||
" time_total_s: 14.797376871109009\n",
|
||
" timestamp: 1654101317\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00043\n",
|
||
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|
||
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|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:35:20,973\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00054\n",
|
||
"2022-06-01 19:35:21,009\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00055\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00045:\n",
|
||
" accuracy: 0.4852801519468186\n",
|
||
" date: 2022-06-01_19-35-21\n",
|
||
" done: false\n",
|
||
" experiment_id: 62b7fa35c807470da7739613f2d8e43b\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12141\n",
|
||
" time_since_restore: 12.428421974182129\n",
|
||
" time_this_iter_s: 12.428421974182129\n",
|
||
" time_total_s: 12.428421974182129\n",
|
||
" timestamp: 1654101321\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00045\n",
|
||
" warmup_time: 0.004401445388793945\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00045:\n",
|
||
" accuracy: 0.4852801519468186\n",
|
||
" date: 2022-06-01_19-35-21\n",
|
||
" done: true\n",
|
||
" experiment_id: 62b7fa35c807470da7739613f2d8e43b\n",
|
||
" experiment_tag: 45_k_dev=2.2402,value_type=open,window=65\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12141\n",
|
||
" time_since_restore: 12.428421974182129\n",
|
||
" time_this_iter_s: 12.428421974182129\n",
|
||
" time_total_s: 12.428421974182129\n",
|
||
" timestamp: 1654101321\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00045\n",
|
||
" warmup_time: 0.004401445388793945\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:35:21,973\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00056\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
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|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:35:26 (running for 00:01:35.47)<br>Memory usage on this node: 12.7/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00038 with accuracy=0.5743243243243243 and parameters={'window': 80, 'value_type': 'low', 'k_dev': 3.3368279156307263}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 72/100 (15 PENDING, 12 RUNNING, 45 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00044</td><td>RUNNING </td><td>192.168.1.14:12123</td><td style=\"text-align: right;\">1.43104</td><td>close </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00046</td><td>RUNNING </td><td>192.168.1.14:12145</td><td style=\"text-align: right;\">2.34936</td><td>open </td><td style=\"text-align: right;\"> 5</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00047</td><td>RUNNING </td><td>192.168.1.14:12223</td><td style=\"text-align: right;\">3.95935</td><td>open </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00048</td><td>RUNNING </td><td>192.168.1.14:12304</td><td style=\"text-align: right;\">2.62893</td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00049</td><td>RUNNING </td><td>192.168.1.14:12364</td><td style=\"text-align: right;\">2.98399</td><td>close </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00050</td><td>RUNNING </td><td>192.168.1.14:12456</td><td style=\"text-align: right;\">3.40408</td><td>close </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00051</td><td>RUNNING </td><td>192.168.1.14:12458</td><td style=\"text-align: right;\">1.63469</td><td>open </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00057</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.34213</td><td>high </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00058</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.98504</td><td>high </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00059</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.80529</td><td>open </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00060</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.24152</td><td>close </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00061</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.58144</td><td>close </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00062</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.61595</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00063</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.88298</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 52 more trials not shown (5 RUNNING, 8 PENDING, 38 TERMINATED)<br><br>"
|
||
],
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00046:\n",
|
||
" accuracy: 0.46997206703910616\n",
|
||
" date: 2022-06-01_19-35-23\n",
|
||
" done: false\n",
|
||
" experiment_id: 7941b8b196064738920ad87807417300\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12145\n",
|
||
" time_since_restore: 13.997588396072388\n",
|
||
" time_this_iter_s: 13.997588396072388\n",
|
||
" time_total_s: 13.997588396072388\n",
|
||
" timestamp: 1654101323\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00046\n",
|
||
" warmup_time: 0.011566638946533203\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00046:\n",
|
||
" accuracy: 0.46997206703910616\n",
|
||
" date: 2022-06-01_19-35-23\n",
|
||
" done: true\n",
|
||
" experiment_id: 7941b8b196064738920ad87807417300\n",
|
||
" experiment_tag: 46_k_dev=2.3494,value_type=open,window=5\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12145\n",
|
||
" time_since_restore: 13.997588396072388\n",
|
||
" time_this_iter_s: 13.997588396072388\n",
|
||
" time_total_s: 13.997588396072388\n",
|
||
" timestamp: 1654101323\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00046\n",
|
||
" warmup_time: 0.011566638946533203\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00044:\n",
|
||
" accuracy: 0.4702558001189768\n",
|
||
" date: 2022-06-01_19-35-22\n",
|
||
" done: false\n",
|
||
" experiment_id: acce403d631e4f8bb4d1d7fa4cc150af\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12123\n",
|
||
" time_since_restore: 13.797248363494873\n",
|
||
" time_this_iter_s: 13.797248363494873\n",
|
||
" time_total_s: 13.797248363494873\n",
|
||
" timestamp: 1654101322\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00044\n",
|
||
" warmup_time: 0.006886482238769531\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00047:\n",
|
||
" accuracy: 0.559322033898305\n",
|
||
" date: 2022-06-01_19-35-23\n",
|
||
" done: false\n",
|
||
" experiment_id: 7948274e350043a2a652c3c1bcc9f67c\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12223\n",
|
||
" time_since_restore: 11.89772629737854\n",
|
||
" time_this_iter_s: 11.89772629737854\n",
|
||
" time_total_s: 11.89772629737854\n",
|
||
" timestamp: 1654101323\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00047\n",
|
||
" warmup_time: 0.0060422420501708984\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00044:\n",
|
||
" accuracy: 0.4702558001189768\n",
|
||
" date: 2022-06-01_19-35-22\n",
|
||
" done: true\n",
|
||
" experiment_id: acce403d631e4f8bb4d1d7fa4cc150af\n",
|
||
" experiment_tag: 44_k_dev=1.431,value_type=close,window=65\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
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||
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||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
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|
||
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|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
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||
"<tr><td>trainable_9e7a8_00048</td><td>RUNNING </td><td>192.168.1.14:12304</td><td style=\"text-align: right;\">2.62893</td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
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||
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||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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||
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|
||
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||
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|
||
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|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 53 more trials not shown (3 RUNNING, 8 PENDING, 41 TERMINATED)<br><br>"
|
||
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|
||
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},
|
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{
|
||
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|
||
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|
||
"text": [
|
||
"Result for trainable_9e7a8_00048:\n",
|
||
" accuracy: 0.49904397705544934\n",
|
||
" date: 2022-06-01_19-35-28\n",
|
||
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|
||
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|
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|
||
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|
||
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|
||
" accuracy: 0.49904397705544934\n",
|
||
" date: 2022-06-01_19-35-28\n",
|
||
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|
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|
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|
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|
||
"text": [
|
||
"Result for trainable_9e7a8_00049:\n",
|
||
" accuracy: 0.4858757062146893\n",
|
||
" date: 2022-06-01_19-35-34\n",
|
||
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||
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||
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|
||
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|
||
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|
||
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|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
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|
||
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|
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|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
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|
||
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|
||
"<tr><td>trainable_9e7a8_00049</td><td>RUNNING </td><td>192.168.1.14:12364</td><td style=\"text-align: right;\">2.98399</td><td>close </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.6483</td><td style=\"text-align: right;\"> 0.485876</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00050</td><td>RUNNING </td><td>192.168.1.14:12456</td><td style=\"text-align: right;\">3.40408</td><td>close </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00051</td><td>RUNNING </td><td>192.168.1.14:12458</td><td style=\"text-align: right;\">1.63469</td><td>open </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00052</td><td>RUNNING </td><td>192.168.1.14:12459</td><td style=\"text-align: right;\">1.55978</td><td>close </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00053</td><td>RUNNING </td><td>192.168.1.14:12461</td><td style=\"text-align: right;\">2.58736</td><td>high </td><td style=\"text-align: right;\"> 35</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00054</td><td>RUNNING </td><td>192.168.1.14:12466</td><td style=\"text-align: right;\">1.46559</td><td>low </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00055</td><td>RUNNING </td><td>192.168.1.14:12468</td><td style=\"text-align: right;\">2.74483</td><td>high </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00061</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.58144</td><td>close </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00062</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.61595</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00063</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.88298</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00064</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.87921</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00065</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.3177 </td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00066</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.65135</td><td>close </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00067</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.71342</td><td>low </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 57 more trials not shown (5 RUNNING, 9 PENDING, 42 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00050:\n",
|
||
" accuracy: 0.125\n",
|
||
" date: 2022-06-01_19-35-36\n",
|
||
" done: false\n",
|
||
" experiment_id: ec43fab210744f0d87c7cf7c34054e82\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12456\n",
|
||
" time_since_restore: 12.250865697860718\n",
|
||
" time_this_iter_s: 12.250865697860718\n",
|
||
" time_total_s: 12.250865697860718\n",
|
||
" timestamp: 1654101336\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00050\n",
|
||
" warmup_time: 0.005457401275634766\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00055:\n",
|
||
" accuracy: 0.489247311827957\n",
|
||
" date: 2022-06-01_19-35-38\n",
|
||
" done: false\n",
|
||
" experiment_id: 7a00014ee9ee4dcc8ecce8a971564269\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12468\n",
|
||
" time_since_restore: 12.681321144104004\n",
|
||
" time_this_iter_s: 12.681321144104004\n",
|
||
" time_total_s: 12.681321144104004\n",
|
||
" timestamp: 1654101338\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00055\n",
|
||
" warmup_time: 0.003793954849243164\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00050:\n",
|
||
" accuracy: 0.125\n",
|
||
" date: 2022-06-01_19-35-36\n",
|
||
" done: true\n",
|
||
" experiment_id: ec43fab210744f0d87c7cf7c34054e82\n",
|
||
" experiment_tag: 50_k_dev=3.4041,value_type=close,window=10\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12456\n",
|
||
" time_since_restore: 12.250865697860718\n",
|
||
" time_this_iter_s: 12.250865697860718\n",
|
||
" time_total_s: 12.250865697860718\n",
|
||
" timestamp: 1654101336\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00050\n",
|
||
" warmup_time: 0.005457401275634766\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00049:\n",
|
||
" accuracy: 0.4858757062146893\n",
|
||
" date: 2022-06-01_19-35-34\n",
|
||
" done: true\n",
|
||
" experiment_id: 30895e40e00b4f6685c32171aefc61cc\n",
|
||
" experiment_tag: 49_k_dev=2.984,value_type=close,window=55\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12364\n",
|
||
" time_since_restore: 13.648305654525757\n",
|
||
" time_this_iter_s: 13.648305654525757\n",
|
||
" time_total_s: 13.648305654525757\n",
|
||
" timestamp: 1654101334\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00049\n",
|
||
" warmup_time: 0.0028488636016845703\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00055:\n",
|
||
" accuracy: 0.489247311827957\n",
|
||
" date: 2022-06-01_19-35-38\n",
|
||
" done: true\n",
|
||
" experiment_id: 7a00014ee9ee4dcc8ecce8a971564269\n",
|
||
" experiment_tag: 55_k_dev=2.7448,value_type=high,window=70\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12468\n",
|
||
" time_since_restore: 12.681321144104004\n",
|
||
" time_this_iter_s: 12.681321144104004\n",
|
||
" time_total_s: 12.681321144104004\n",
|
||
" timestamp: 1654101338\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00055\n",
|
||
" warmup_time: 0.003793954849243164\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00052:\n",
|
||
" accuracy: 0.47584973166368516\n",
|
||
" date: 2022-06-01_19-35-38\n",
|
||
" done: false\n",
|
||
" experiment_id: 3706599cf6524c7b82771ab7adc8c66d\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12459\n",
|
||
" time_since_restore: 13.855209827423096\n",
|
||
" time_this_iter_s: 13.855209827423096\n",
|
||
" time_total_s: 13.855209827423096\n",
|
||
" timestamp: 1654101338\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00052\n",
|
||
" warmup_time: 0.010962724685668945\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00052:\n",
|
||
" accuracy: 0.47584973166368516\n",
|
||
" date: 2022-06-01_19-35-38\n",
|
||
" done: true\n",
|
||
" experiment_id: 3706599cf6524c7b82771ab7adc8c66d\n",
|
||
" experiment_tag: 52_k_dev=1.5598,value_type=close,window=60\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12459\n",
|
||
" time_since_restore: 13.855209827423096\n",
|
||
" time_this_iter_s: 13.855209827423096\n",
|
||
" time_total_s: 13.855209827423096\n",
|
||
" timestamp: 1654101338\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00052\n",
|
||
" warmup_time: 0.010962724685668945\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00054:\n",
|
||
" accuracy: 0.4714795008912656\n",
|
||
" date: 2022-06-01_19-35-38\n",
|
||
" done: false\n",
|
||
" experiment_id: 17dea376587c41a0a26528298910e3dc\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12466\n",
|
||
" time_since_restore: 13.265269756317139\n",
|
||
" time_this_iter_s: 13.265269756317139\n",
|
||
" time_total_s: 13.265269756317139\n",
|
||
" timestamp: 1654101338\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00054\n",
|
||
" warmup_time: 0.01656317710876465\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00054:\n",
|
||
" accuracy: 0.4714795008912656\n",
|
||
" date: 2022-06-01_19-35-38\n",
|
||
" done: true\n",
|
||
" experiment_id: 17dea376587c41a0a26528298910e3dc\n",
|
||
" experiment_tag: 54_k_dev=1.4656,value_type=low,window=50\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12466\n",
|
||
" time_since_restore: 13.265269756317139\n",
|
||
" time_this_iter_s: 13.265269756317139\n",
|
||
" time_total_s: 13.265269756317139\n",
|
||
" timestamp: 1654101338\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00054\n",
|
||
" warmup_time: 0.01656317710876465\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00051:\n",
|
||
" accuracy: 0.47394446557626474\n",
|
||
" date: 2022-06-01_19-35-38\n",
|
||
" done: false\n",
|
||
" experiment_id: 7181eb7e2b5e44339db85fb4e61766ff\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12458\n",
|
||
" time_since_restore: 13.853472471237183\n",
|
||
" time_this_iter_s: 13.853472471237183\n",
|
||
" time_total_s: 13.853472471237183\n",
|
||
" timestamp: 1654101338\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00051\n",
|
||
" warmup_time: 0.007745981216430664\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00051:\n",
|
||
" accuracy: 0.47394446557626474\n",
|
||
" date: 2022-06-01_19-35-38\n",
|
||
" done: true\n",
|
||
" experiment_id: 7181eb7e2b5e44339db85fb4e61766ff\n",
|
||
" experiment_tag: 51_k_dev=1.6347,value_type=open,window=15\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12458\n",
|
||
" time_since_restore: 13.853472471237183\n",
|
||
" time_this_iter_s: 13.853472471237183\n",
|
||
" time_total_s: 13.853472471237183\n",
|
||
" timestamp: 1654101338\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00051\n",
|
||
" warmup_time: 0.007745981216430664\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00053:\n",
|
||
" accuracy: 0.44356435643564357\n",
|
||
" date: 2022-06-01_19-35-39\n",
|
||
" done: false\n",
|
||
" experiment_id: 9b6c2e5c908b4fb2bb70db679c9b16a4\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12461\n",
|
||
" time_since_restore: 13.831803560256958\n",
|
||
" time_this_iter_s: 13.831803560256958\n",
|
||
" time_total_s: 13.831803560256958\n",
|
||
" timestamp: 1654101339\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00053\n",
|
||
" warmup_time: 0.0035173892974853516\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:35:39 (running for 00:01:48.23)<br>Memory usage on this node: 12.1/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 6.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00038 with accuracy=0.5743243243243243 and parameters={'window': 80, 'value_type': 'low', 'k_dev': 3.3368279156307263}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 77/100 (16 PENDING, 6 RUNNING, 55 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00053</td><td>RUNNING </td><td>192.168.1.14:12461</td><td style=\"text-align: right;\">2.58736</td><td>high </td><td style=\"text-align: right;\"> 35</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.8318</td><td style=\"text-align: right;\"> 0.443564</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00056</td><td>RUNNING </td><td>192.168.1.14:12471</td><td style=\"text-align: right;\">2.93169</td><td>open </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00057</td><td>RUNNING </td><td>192.168.1.14:12776</td><td style=\"text-align: right;\">3.34213</td><td>high </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00058</td><td>RUNNING </td><td>192.168.1.14:12847</td><td style=\"text-align: right;\">1.98504</td><td>high </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00059</td><td>RUNNING </td><td>192.168.1.14:12849</td><td style=\"text-align: right;\">2.80529</td><td>open </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00060</td><td>RUNNING </td><td>192.168.1.14:12852</td><td style=\"text-align: right;\">1.24152</td><td>close </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00061</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.58144</td><td>close </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00062</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.61595</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00063</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.88298</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00064</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.87921</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00065</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.3177 </td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00066</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.65135</td><td>close </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00067</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.71342</td><td>low </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 57 more trials not shown (9 PENDING, 48 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00053:\n",
|
||
" accuracy: 0.44356435643564357\n",
|
||
" date: 2022-06-01_19-35-39\n",
|
||
" done: true\n",
|
||
" experiment_id: 9b6c2e5c908b4fb2bb70db679c9b16a4\n",
|
||
" experiment_tag: 53_k_dev=2.5874,value_type=high,window=35\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12461\n",
|
||
" time_since_restore: 13.831803560256958\n",
|
||
" time_this_iter_s: 13.831803560256958\n",
|
||
" time_total_s: 13.831803560256958\n",
|
||
" timestamp: 1654101339\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00053\n",
|
||
" warmup_time: 0.0035173892974853516\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:35:39,944\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00061\n",
|
||
"2022-06-01 19:35:39,963\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00062\n",
|
||
"2022-06-01 19:35:39,984\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00063\n",
|
||
"2022-06-01 19:35:40,032\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00064\n",
|
||
"2022-06-01 19:35:40,061\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00065\n",
|
||
"2022-06-01 19:35:40,089\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00066\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00056:\n",
|
||
" accuracy: 0.5165692007797271\n",
|
||
" date: 2022-06-01_19-35-39\n",
|
||
" done: false\n",
|
||
" experiment_id: b19b5a008d5241d69de78d3f863ff9a3\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12471\n",
|
||
" time_since_restore: 13.42310881614685\n",
|
||
" time_this_iter_s: 13.42310881614685\n",
|
||
" time_total_s: 13.42310881614685\n",
|
||
" timestamp: 1654101339\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00056\n",
|
||
" warmup_time: 0.004828929901123047\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00056:\n",
|
||
" accuracy: 0.5165692007797271\n",
|
||
" date: 2022-06-01_19-35-39\n",
|
||
" done: true\n",
|
||
" experiment_id: b19b5a008d5241d69de78d3f863ff9a3\n",
|
||
" experiment_tag: 56_k_dev=2.9317,value_type=open,window=20\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12471\n",
|
||
" time_since_restore: 13.42310881614685\n",
|
||
" time_this_iter_s: 13.42310881614685\n",
|
||
" time_total_s: 13.42310881614685\n",
|
||
" timestamp: 1654101339\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00056\n",
|
||
" warmup_time: 0.004828929901123047\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:35:40,142\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00067\n",
|
||
"2022-06-01 19:35:40,182\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00068\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:35:46 (running for 00:01:55.39)<br>Memory usage on this node: 12.8/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00038 with accuracy=0.5743243243243243 and parameters={'window': 80, 'value_type': 'low', 'k_dev': 3.3368279156307263}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 85/100 (16 PENDING, 12 RUNNING, 57 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00057</td><td>RUNNING </td><td>192.168.1.14:12776</td><td style=\"text-align: right;\">3.34213</td><td>high </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00058</td><td>RUNNING </td><td>192.168.1.14:12847</td><td style=\"text-align: right;\">1.98504</td><td>high </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00059</td><td>RUNNING </td><td>192.168.1.14:12849</td><td style=\"text-align: right;\">2.80529</td><td>open </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00060</td><td>RUNNING </td><td>192.168.1.14:12852</td><td style=\"text-align: right;\">1.24152</td><td>close </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00061</td><td>RUNNING </td><td>192.168.1.14:13083</td><td style=\"text-align: right;\">2.58144</td><td>close </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00062</td><td>RUNNING </td><td>192.168.1.14:13089</td><td style=\"text-align: right;\">1.61595</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00063</td><td>RUNNING </td><td>192.168.1.14:13106</td><td style=\"text-align: right;\">1.88298</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00069</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.82523</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00070</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.268 </td><td>low </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00071</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.12592</td><td>high </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00072</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.23254</td><td>low </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00073</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.90762</td><td>close </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00074</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.52124</td><td>low </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00075</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.42818</td><td>close </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 65 more trials not shown (5 RUNNING, 9 PENDING, 50 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00057:\n",
|
||
" accuracy: 0.47774480712166173\n",
|
||
" date: 2022-06-01_19-35-46\n",
|
||
" done: false\n",
|
||
" experiment_id: 12c7c0edfcc14691ac9ced451f9b7c9e\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12776\n",
|
||
" time_since_restore: 14.150588035583496\n",
|
||
" time_this_iter_s: 14.150588035583496\n",
|
||
" time_total_s: 14.150588035583496\n",
|
||
" timestamp: 1654101346\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00057\n",
|
||
" warmup_time: 0.0038924217224121094\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00057:\n",
|
||
" accuracy: 0.47774480712166173\n",
|
||
" date: 2022-06-01_19-35-46\n",
|
||
" done: true\n",
|
||
" experiment_id: 12c7c0edfcc14691ac9ced451f9b7c9e\n",
|
||
" experiment_tag: 57_k_dev=3.3421,value_type=high,window=10\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 12776\n",
|
||
" time_since_restore: 14.150588035583496\n",
|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
" date: 2022-06-01_19-35-52\n",
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||
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||
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||
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||
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||
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|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
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|
||
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|
||
"<tr><td>trainable_9e7a8_00058</td><td>RUNNING </td><td>192.168.1.14:12847</td><td style=\"text-align: right;\">1.98504</td><td>high </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
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|
||
"<tr><td>trainable_9e7a8_00060</td><td>RUNNING </td><td>192.168.1.14:12852</td><td style=\"text-align: right;\">1.24152</td><td>close </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00061</td><td>RUNNING </td><td>192.168.1.14:13083</td><td style=\"text-align: right;\">2.58144</td><td>close </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00062</td><td>RUNNING </td><td>192.168.1.14:13089</td><td style=\"text-align: right;\">1.61595</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00063</td><td>RUNNING </td><td>192.168.1.14:13106</td><td style=\"text-align: right;\">1.88298</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00064</td><td>RUNNING </td><td>192.168.1.14:13128</td><td style=\"text-align: right;\">2.87921</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00070</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.268 </td><td>low </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00071</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.12592</td><td>high </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
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|
||
"<tr><td>trainable_9e7a8_00073</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.90762</td><td>close </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00074</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.52124</td><td>low </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00075</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.42818</td><td>close </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00076</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.99823</td><td>high </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 66 more trials not shown (5 RUNNING, 9 PENDING, 51 TERMINATED)<br><br>"
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"text": [
|
||
"Result for trainable_9e7a8_00059:\n",
|
||
" accuracy: 0.5254237288135594\n",
|
||
" date: 2022-06-01_19-35-52\n",
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||
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|
||
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|
||
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||
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|
||
" warmup_time: 0.005212306976318359\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00058:\n",
|
||
" accuracy: 0.468586387434555\n",
|
||
" date: 2022-06-01_19-35-53\n",
|
||
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|
||
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|
||
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|
||
" \n",
|
||
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|
||
" accuracy: 0.468586387434555\n",
|
||
" date: 2022-06-01_19-35-53\n",
|
||
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|
||
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|
||
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" trial_id: 9e7a8_00058\n",
|
||
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|
||
" \n",
|
||
"Result for trainable_9e7a8_00060:\n",
|
||
" accuracy: 0.4608654528257271\n",
|
||
" date: 2022-06-01_19-35-54\n",
|
||
" done: false\n",
|
||
" experiment_id: 73c45794874949818df555af27cf4588\n",
|
||
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|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
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||
" pid: 12852\n",
|
||
" time_since_restore: 17.009721755981445\n",
|
||
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|
||
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||
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|
||
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||
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" trial_id: 9e7a8_00060\n",
|
||
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|
||
" \n",
|
||
"Result for trainable_9e7a8_00060:\n",
|
||
" accuracy: 0.4608654528257271\n",
|
||
" date: 2022-06-01_19-35-54\n",
|
||
" done: true\n",
|
||
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|
||
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|
||
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||
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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||
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|
||
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||
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|
||
"2022-06-01 19:35:56,305\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00070\n",
|
||
"2022-06-01 19:35:56,369\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00071\n",
|
||
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|
||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00065:\n",
|
||
" accuracy: 0.5490196078431373\n",
|
||
" date: 2022-06-01_19-35-59\n",
|
||
" done: false\n",
|
||
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|
||
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|
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|
||
" timestamp: 1654101359\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00065\n",
|
||
" warmup_time: 0.005694150924682617\n",
|
||
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|
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|
||
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|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
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|
||
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|
||
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"== Status ==<br>Current time: 2022-06-01 19:36:01 (running for 00:02:10.20)<br>Memory usage on this node: 12.8/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00038 with accuracy=0.5743243243243243 and parameters={'window': 80, 'value_type': 'low', 'k_dev': 3.3368279156307263}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 89/100 (16 PENDING, 12 RUNNING, 61 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
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|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00061</td><td>RUNNING </td><td>192.168.1.14:13083</td><td style=\"text-align: right;\">2.58144</td><td>close </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00062</td><td>RUNNING </td><td>192.168.1.14:13089</td><td style=\"text-align: right;\">1.61595</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00063</td><td>RUNNING </td><td>192.168.1.14:13106</td><td style=\"text-align: right;\">1.88298</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00064</td><td>RUNNING </td><td>192.168.1.14:13128</td><td style=\"text-align: right;\">2.87921</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00065</td><td>RUNNING </td><td>192.168.1.14:13130</td><td style=\"text-align: right;\">3.3177 </td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7332</td><td style=\"text-align: right;\"> 0.54902 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00066</td><td>RUNNING </td><td>192.168.1.14:13132</td><td style=\"text-align: right;\">1.65135</td><td>close </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00067</td><td>RUNNING </td><td>192.168.1.14:13133</td><td style=\"text-align: right;\">2.71342</td><td>low </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00073</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.90762</td><td>close </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00074</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.52124</td><td>low </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00075</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.42818</td><td>close </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00076</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.99823</td><td>high </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00077</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.21075</td><td>high </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00078</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.62677</td><td>open </td><td style=\"text-align: right;\"> 5</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00079</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.45973</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 69 more trials not shown (5 RUNNING, 9 PENDING, 54 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00062:\n",
|
||
" accuracy: 0.4754601226993865\n",
|
||
" date: 2022-06-01_19-36-00\n",
|
||
" done: false\n",
|
||
" experiment_id: aa26a83503aa4dc6a671a888b1e0135d\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13089\n",
|
||
" time_since_restore: 15.619421482086182\n",
|
||
" time_this_iter_s: 15.619421482086182\n",
|
||
" time_total_s: 15.619421482086182\n",
|
||
" timestamp: 1654101360\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00062\n",
|
||
" warmup_time: 0.0051763057708740234\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00066:\n",
|
||
" accuracy: 0.4742676167854315\n",
|
||
" date: 2022-06-01_19-36-01\n",
|
||
" done: false\n",
|
||
" experiment_id: f55808ee9dbe4868801fd20b02bd0f1b\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13132\n",
|
||
" time_since_restore: 15.999192237854004\n",
|
||
" time_this_iter_s: 15.999192237854004\n",
|
||
" time_total_s: 15.999192237854004\n",
|
||
" timestamp: 1654101361\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00066\n",
|
||
" warmup_time: 0.0056378841400146484\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00061:\n",
|
||
" accuracy: 0.5103734439834025\n",
|
||
" date: 2022-06-01_19-36-00\n",
|
||
" done: false\n",
|
||
" experiment_id: 95898e23e88b4be4b70f03befd4651aa\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13083\n",
|
||
" time_since_restore: 14.885961055755615\n",
|
||
" time_this_iter_s: 14.885961055755615\n",
|
||
" time_total_s: 14.885961055755615\n",
|
||
" timestamp: 1654101360\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00061\n",
|
||
" warmup_time: 0.006001949310302734\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00064:\n",
|
||
" accuracy: 0.5014164305949008\n",
|
||
" date: 2022-06-01_19-36-00\n",
|
||
" done: false\n",
|
||
" experiment_id: 4ad91f70d6374c9b8b4b83478761c8c5\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13128\n",
|
||
" time_since_restore: 15.386110305786133\n",
|
||
" time_this_iter_s: 15.386110305786133\n",
|
||
" time_total_s: 15.386110305786133\n",
|
||
" timestamp: 1654101360\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00064\n",
|
||
" warmup_time: 0.006777763366699219\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00065:\n",
|
||
" accuracy: 0.5490196078431373\n",
|
||
" date: 2022-06-01_19-35-59\n",
|
||
" done: true\n",
|
||
" experiment_id: b93434890af74b569340a211980de915\n",
|
||
" experiment_tag: 65_k_dev=3.3177,value_type=low,window=40\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13130\n",
|
||
" time_since_restore: 14.733199119567871\n",
|
||
" time_this_iter_s: 14.733199119567871\n",
|
||
" time_total_s: 14.733199119567871\n",
|
||
" timestamp: 1654101359\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00065\n",
|
||
" warmup_time: 0.005694150924682617\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00067:\n",
|
||
" accuracy: 0.5328947368421053\n",
|
||
" date: 2022-06-01_19-36-00\n",
|
||
" done: false\n",
|
||
" experiment_id: 8a45b6f7749247de833b2f00309002f8\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13133\n",
|
||
" time_since_restore: 15.050776243209839\n",
|
||
" time_this_iter_s: 15.050776243209839\n",
|
||
" time_total_s: 15.050776243209839\n",
|
||
" timestamp: 1654101360\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00067\n",
|
||
" warmup_time: 0.005591630935668945\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00062:\n",
|
||
" accuracy: 0.4754601226993865\n",
|
||
" date: 2022-06-01_19-36-00\n",
|
||
" done: true\n",
|
||
" experiment_id: aa26a83503aa4dc6a671a888b1e0135d\n",
|
||
" experiment_tag: 62_k_dev=1.6159,value_type=close,window=85\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13089\n",
|
||
" time_since_restore: 15.619421482086182\n",
|
||
" time_this_iter_s: 15.619421482086182\n",
|
||
" time_total_s: 15.619421482086182\n",
|
||
" timestamp: 1654101360\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00062\n",
|
||
" warmup_time: 0.0051763057708740234\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00063:\n",
|
||
" accuracy: 0.4846322722283205\n",
|
||
" date: 2022-06-01_19-36-00\n",
|
||
" done: false\n",
|
||
" experiment_id: abede3d95a27446cb5573a65e71b4463\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13106\n",
|
||
" time_since_restore: 14.994568586349487\n",
|
||
" time_this_iter_s: 14.994568586349487\n",
|
||
" time_total_s: 14.994568586349487\n",
|
||
" timestamp: 1654101360\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00063\n",
|
||
" warmup_time: 0.01875782012939453\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00064:\n",
|
||
" accuracy: 0.5014164305949008\n",
|
||
" date: 2022-06-01_19-36-00\n",
|
||
" done: true\n",
|
||
" experiment_id: 4ad91f70d6374c9b8b4b83478761c8c5\n",
|
||
" experiment_tag: 64_k_dev=2.8792,value_type=high,window=95\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13128\n",
|
||
" time_since_restore: 15.386110305786133\n",
|
||
" time_this_iter_s: 15.386110305786133\n",
|
||
" time_total_s: 15.386110305786133\n",
|
||
" timestamp: 1654101360\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00064\n",
|
||
" warmup_time: 0.006777763366699219\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00066:\n",
|
||
" accuracy: 0.4742676167854315\n",
|
||
" date: 2022-06-01_19-36-01\n",
|
||
" done: true\n",
|
||
" experiment_id: f55808ee9dbe4868801fd20b02bd0f1b\n",
|
||
" experiment_tag: 66_k_dev=1.6513,value_type=close,window=75\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13132\n",
|
||
" time_since_restore: 15.999192237854004\n",
|
||
" time_this_iter_s: 15.999192237854004\n",
|
||
" time_total_s: 15.999192237854004\n",
|
||
" timestamp: 1654101361\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00066\n",
|
||
" warmup_time: 0.0056378841400146484\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00061:\n",
|
||
" accuracy: 0.5103734439834025\n",
|
||
" date: 2022-06-01_19-36-00\n",
|
||
" done: true\n",
|
||
" experiment_id: 95898e23e88b4be4b70f03befd4651aa\n",
|
||
" experiment_tag: 61_k_dev=2.5814,value_type=close,window=70\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13083\n",
|
||
" time_since_restore: 14.885961055755615\n",
|
||
" time_this_iter_s: 14.885961055755615\n",
|
||
" time_total_s: 14.885961055755615\n",
|
||
" timestamp: 1654101360\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00061\n",
|
||
" warmup_time: 0.006001949310302734\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00068:\n",
|
||
" accuracy: 0.5005793742757821\n",
|
||
" date: 2022-06-01_19-36-00\n",
|
||
" done: false\n",
|
||
" experiment_id: dfa6f5f40d664043a4722184db31494f\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13135\n",
|
||
" time_since_restore: 15.302860021591187\n",
|
||
" time_this_iter_s: 15.302860021591187\n",
|
||
" time_total_s: 15.302860021591187\n",
|
||
" timestamp: 1654101360\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00068\n",
|
||
" warmup_time: 0.01061868667602539\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00067:\n",
|
||
" accuracy: 0.5328947368421053\n",
|
||
" date: 2022-06-01_19-36-00\n",
|
||
" done: true\n",
|
||
" experiment_id: 8a45b6f7749247de833b2f00309002f8\n",
|
||
" experiment_tag: 67_k_dev=2.7134,value_type=low,window=95\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13133\n",
|
||
" time_since_restore: 15.050776243209839\n",
|
||
" time_this_iter_s: 15.050776243209839\n",
|
||
" time_total_s: 15.050776243209839\n",
|
||
" timestamp: 1654101360\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00067\n",
|
||
" warmup_time: 0.005591630935668945\n",
|
||
" \n",
|
||
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|
||
" accuracy: 0.5005793742757821\n",
|
||
" date: 2022-06-01_19-36-00\n",
|
||
" done: true\n",
|
||
" experiment_id: dfa6f5f40d664043a4722184db31494f\n",
|
||
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||
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|
||
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||
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||
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||
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||
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|
||
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||
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|
||
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||
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|
||
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|
||
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|
||
" \n",
|
||
"Result for trainable_9e7a8_00063:\n",
|
||
" accuracy: 0.4846322722283205\n",
|
||
" date: 2022-06-01_19-36-00\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
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|
||
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|
||
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"== Status ==<br>Current time: 2022-06-01 19:36:09 (running for 00:02:18.10)<br>Memory usage on this node: 12.8/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00038 with accuracy=0.5743243243243243 and parameters={'window': 80, 'value_type': 'low', 'k_dev': 3.3368279156307263}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 97/100 (16 PENDING, 12 RUNNING, 69 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00069</td><td>RUNNING </td><td>192.168.1.14:13414</td><td style=\"text-align: right;\">3.82523</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.3848</td><td style=\"text-align: right;\"> 0.555556</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00070</td><td>RUNNING </td><td>192.168.1.14:13512</td><td style=\"text-align: right;\">1.268 </td><td>low </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
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|
||
"<tr><td>trainable_9e7a8_00072</td><td>RUNNING </td><td>192.168.1.14:13531</td><td style=\"text-align: right;\">3.23254</td><td>low </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00073</td><td>RUNNING </td><td>192.168.1.14:13769</td><td style=\"text-align: right;\">1.90762</td><td>close </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00074</td><td>RUNNING </td><td>192.168.1.14:13785</td><td style=\"text-align: right;\">2.52124</td><td>low </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
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|
||
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|
||
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|
||
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||
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|
||
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|
||
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|
||
"<tr><td>trainable_9e7a8_00087</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.35735</td><td>open </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 77 more trials not shown (5 RUNNING, 9 PENDING, 62 TERMINATED)<br><br>"
|
||
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|
||
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|
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|
||
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|
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|
||
"text": [
|
||
"Result for trainable_9e7a8_00069:\n",
|
||
" accuracy: 0.5555555555555556\n",
|
||
" date: 2022-06-01_19-36-07\n",
|
||
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|
||
" experiment_id: ec462f1060664a658e9072352c3bb890\n",
|
||
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||
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||
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|
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|
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|
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||
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|
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|
||
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|
||
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|
||
"text": [
|
||
"Result for trainable_9e7a8_00071:\n",
|
||
" accuracy: 0.520618556701031\n",
|
||
" date: 2022-06-01_19-36-15\n",
|
||
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|
||
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|
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|
||
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||
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|
||
" timestamp: 1654101375\n",
|
||
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|
||
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|
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|
||
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|
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|
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|
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|
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||
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|
||
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|
||
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|
||
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|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
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|
||
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|
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"== Status ==<br>Current time: 2022-06-01 19:36:16 (running for 00:02:25.55)<br>Memory usage on this node: 12.7/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00038 with accuracy=0.5743243243243243 and parameters={'window': 80, 'value_type': 'low', 'k_dev': 3.3368279156307263}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 98/100 (16 PENDING, 12 RUNNING, 70 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
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|
||
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|
||
"<tr><td>trainable_9e7a8_00070</td><td>RUNNING </td><td>192.168.1.14:13512</td><td style=\"text-align: right;\">1.268 </td><td>low </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00071</td><td>RUNNING </td><td>192.168.1.14:13529</td><td style=\"text-align: right;\">3.12592</td><td>high </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.354 </td><td style=\"text-align: right;\"> 0.520619</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00072</td><td>RUNNING </td><td>192.168.1.14:13531</td><td style=\"text-align: right;\">3.23254</td><td>low </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00073</td><td>RUNNING </td><td>192.168.1.14:13769</td><td style=\"text-align: right;\">1.90762</td><td>close </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00074</td><td>RUNNING </td><td>192.168.1.14:13785</td><td style=\"text-align: right;\">2.52124</td><td>low </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00075</td><td>RUNNING </td><td>192.168.1.14:13813</td><td style=\"text-align: right;\">2.42818</td><td>close </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00076</td><td>RUNNING </td><td>192.168.1.14:13816</td><td style=\"text-align: right;\">3.99823</td><td>high </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00082</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.08625</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00083</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.11219</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00084</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.89401</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00085</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.16614</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00086</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.62232</td><td>high </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00087</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.35735</td><td>open </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00088</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.48118</td><td>low </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 78 more trials not shown (5 RUNNING, 9 PENDING, 63 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
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||
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||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00070:\n",
|
||
" accuracy: 0.46431924882629105\n",
|
||
" date: 2022-06-01_19-36-15\n",
|
||
" done: false\n",
|
||
" experiment_id: 5e7642f093714589a4cc719b1e3c5544\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13512\n",
|
||
" time_since_restore: 15.209872961044312\n",
|
||
" time_this_iter_s: 15.209872961044312\n",
|
||
" time_total_s: 15.209872961044312\n",
|
||
" timestamp: 1654101375\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00070\n",
|
||
" warmup_time: 0.0031023025512695312\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00071:\n",
|
||
" accuracy: 0.520618556701031\n",
|
||
" date: 2022-06-01_19-36-15\n",
|
||
" done: true\n",
|
||
" experiment_id: b3bcf611a54e4ef59d5bb65e43331b74\n",
|
||
" experiment_tag: 71_k_dev=3.1259,value_type=high,window=80\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13529\n",
|
||
" time_since_restore: 14.35395884513855\n",
|
||
" time_this_iter_s: 14.35395884513855\n",
|
||
" time_total_s: 14.35395884513855\n",
|
||
" timestamp: 1654101375\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00071\n",
|
||
" warmup_time: 0.002830028533935547\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00072:\n",
|
||
" accuracy: 0.5180180180180181\n",
|
||
" date: 2022-06-01_19-36-15\n",
|
||
" done: false\n",
|
||
" experiment_id: 095fa920f2e74c348b8c19464db0ab0a\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13531\n",
|
||
" time_since_restore: 14.482828140258789\n",
|
||
" time_this_iter_s: 14.482828140258789\n",
|
||
" time_total_s: 14.482828140258789\n",
|
||
" timestamp: 1654101375\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00072\n",
|
||
" warmup_time: 0.0062177181243896484\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00070:\n",
|
||
" accuracy: 0.46431924882629105\n",
|
||
" date: 2022-06-01_19-36-15\n",
|
||
" done: true\n",
|
||
" experiment_id: 5e7642f093714589a4cc719b1e3c5544\n",
|
||
" experiment_tag: 70_k_dev=1.268,value_type=low,window=60\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13512\n",
|
||
" time_since_restore: 15.209872961044312\n",
|
||
" time_this_iter_s: 15.209872961044312\n",
|
||
" time_total_s: 15.209872961044312\n",
|
||
" timestamp: 1654101375\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00070\n",
|
||
" warmup_time: 0.0031023025512695312\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00072:\n",
|
||
" accuracy: 0.5180180180180181\n",
|
||
" date: 2022-06-01_19-36-15\n",
|
||
" done: true\n",
|
||
" experiment_id: 095fa920f2e74c348b8c19464db0ab0a\n",
|
||
" experiment_tag: 72_k_dev=3.2325,value_type=low,window=30\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13531\n",
|
||
" time_since_restore: 14.482828140258789\n",
|
||
" time_this_iter_s: 14.482828140258789\n",
|
||
" time_total_s: 14.482828140258789\n",
|
||
" timestamp: 1654101375\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00072\n",
|
||
" warmup_time: 0.0062177181243896484\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:36:17,926\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00082\n",
|
||
"2022-06-01 19:36:17,993\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00083\n",
|
||
"2022-06-01 19:36:18,036\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00084\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00076:\n",
|
||
" accuracy: 0.42424242424242425\n",
|
||
" date: 2022-06-01_19-36-22\n",
|
||
" done: false\n",
|
||
" experiment_id: a7dc5c6c509347f3971e358c338ed54c\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13816\n",
|
||
" time_since_restore: 14.288736820220947\n",
|
||
" time_this_iter_s: 14.288736820220947\n",
|
||
" time_total_s: 14.288736820220947\n",
|
||
" timestamp: 1654101382\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00076\n",
|
||
" warmup_time: 0.007698535919189453\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:36:23 (running for 00:02:32.36)<br>Memory usage on this node: 12.7/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00038 with accuracy=0.5743243243243243 and parameters={'window': 80, 'value_type': 'low', 'k_dev': 3.3368279156307263}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 100/100 (15 PENDING, 12 RUNNING, 73 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00073</td><td>RUNNING </td><td>192.168.1.14:13769</td><td style=\"text-align: right;\">1.90762</td><td>close </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00074</td><td>RUNNING </td><td>192.168.1.14:13785</td><td style=\"text-align: right;\">2.52124</td><td>low </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00075</td><td>RUNNING </td><td>192.168.1.14:13813</td><td style=\"text-align: right;\">2.42818</td><td>close </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00076</td><td>RUNNING </td><td>192.168.1.14:13816</td><td style=\"text-align: right;\">3.99823</td><td>high </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.2887</td><td style=\"text-align: right;\"> 0.424242</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00077</td><td>RUNNING </td><td>192.168.1.14:13827</td><td style=\"text-align: right;\">1.21075</td><td>high </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00078</td><td>RUNNING </td><td>192.168.1.14:13830</td><td style=\"text-align: right;\">1.62677</td><td>open </td><td style=\"text-align: right;\"> 5</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00079</td><td>RUNNING </td><td>192.168.1.14:13831</td><td style=\"text-align: right;\">3.45973</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00085</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.16614</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00086</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.62232</td><td>high </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00087</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.35735</td><td>open </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00088</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.48118</td><td>low </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00089</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.29228</td><td>open </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00090</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.59333</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00091</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.57782</td><td>low </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 80 more trials not shown (5 RUNNING, 8 PENDING, 66 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00079:\n",
|
||
" accuracy: 0.5323741007194245\n",
|
||
" date: 2022-06-01_19-36-23\n",
|
||
" done: false\n",
|
||
" experiment_id: 78f3a3c3ffc64735bd3cd00a529c00c5\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13831\n",
|
||
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|
||
" time_this_iter_s: 14.90287446975708\n",
|
||
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|
||
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|
||
" timesteps_since_restore: 0\n",
|
||
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|
||
" trial_id: 9e7a8_00079\n",
|
||
" warmup_time: 0.010467290878295898\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00076:\n",
|
||
" accuracy: 0.42424242424242425\n",
|
||
" date: 2022-06-01_19-36-22\n",
|
||
" done: true\n",
|
||
" experiment_id: a7dc5c6c509347f3971e358c338ed54c\n",
|
||
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|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13816\n",
|
||
" time_since_restore: 14.288736820220947\n",
|
||
" time_this_iter_s: 14.288736820220947\n",
|
||
" time_total_s: 14.288736820220947\n",
|
||
" timestamp: 1654101382\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00076\n",
|
||
" warmup_time: 0.007698535919189453\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00074:\n",
|
||
" accuracy: 0.5129032258064516\n",
|
||
" date: 2022-06-01_19-36-23\n",
|
||
" done: false\n",
|
||
" experiment_id: cea27b54ff4c46e48d21915a76587e3e\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13785\n",
|
||
" time_since_restore: 15.873217344284058\n",
|
||
" time_this_iter_s: 15.873217344284058\n",
|
||
" time_total_s: 15.873217344284058\n",
|
||
" timestamp: 1654101383\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00074\n",
|
||
" warmup_time: 0.008273124694824219\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00075:\n",
|
||
" accuracy: 0.5095057034220533\n",
|
||
" date: 2022-06-01_19-36-23\n",
|
||
" done: false\n",
|
||
" experiment_id: accde7b0038b4330840e4e966870fc37\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13813\n",
|
||
" time_since_restore: 15.532708168029785\n",
|
||
" time_this_iter_s: 15.532708168029785\n",
|
||
" time_total_s: 15.532708168029785\n",
|
||
" timestamp: 1654101383\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00075\n",
|
||
" warmup_time: 0.010461091995239258\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00079:\n",
|
||
" accuracy: 0.5323741007194245\n",
|
||
" date: 2022-06-01_19-36-23\n",
|
||
" done: true\n",
|
||
" experiment_id: 78f3a3c3ffc64735bd3cd00a529c00c5\n",
|
||
" experiment_tag: 79_k_dev=3.4597,value_type=open,window=90\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13831\n",
|
||
" time_since_restore: 14.90287446975708\n",
|
||
" time_this_iter_s: 14.90287446975708\n",
|
||
" time_total_s: 14.90287446975708\n",
|
||
" timestamp: 1654101383\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00079\n",
|
||
" warmup_time: 0.010467290878295898\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00074:\n",
|
||
" accuracy: 0.5129032258064516\n",
|
||
" date: 2022-06-01_19-36-23\n",
|
||
" done: true\n",
|
||
" experiment_id: cea27b54ff4c46e48d21915a76587e3e\n",
|
||
" experiment_tag: 74_k_dev=2.5212,value_type=low,window=45\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13785\n",
|
||
" time_since_restore: 15.873217344284058\n",
|
||
" time_this_iter_s: 15.873217344284058\n",
|
||
" time_total_s: 15.873217344284058\n",
|
||
" timestamp: 1654101383\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00074\n",
|
||
" warmup_time: 0.008273124694824219\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00075:\n",
|
||
" accuracy: 0.5095057034220533\n",
|
||
" date: 2022-06-01_19-36-23\n",
|
||
" done: true\n",
|
||
" experiment_id: accde7b0038b4330840e4e966870fc37\n",
|
||
" experiment_tag: 75_k_dev=2.4282,value_type=close,window=20\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13813\n",
|
||
" time_since_restore: 15.532708168029785\n",
|
||
" time_this_iter_s: 15.532708168029785\n",
|
||
" time_total_s: 15.532708168029785\n",
|
||
" timestamp: 1654101383\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00075\n",
|
||
" warmup_time: 0.010461091995239258\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00073:\n",
|
||
" accuracy: 0.4947498455836936\n",
|
||
" date: 2022-06-01_19-36-24\n",
|
||
" done: false\n",
|
||
" experiment_id: 4aacc4983775428a8cf58028fae0745e\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13769\n",
|
||
" time_since_restore: 16.100390911102295\n",
|
||
" time_this_iter_s: 16.100390911102295\n",
|
||
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|
||
" timestamp: 1654101384\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00073\n",
|
||
" warmup_time: 0.0061151981353759766\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00073:\n",
|
||
" accuracy: 0.4947498455836936\n",
|
||
" date: 2022-06-01_19-36-24\n",
|
||
" done: true\n",
|
||
" experiment_id: 4aacc4983775428a8cf58028fae0745e\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" trial_id: 9e7a8_00073\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
"2022-06-01 19:36:24,936\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00085\n",
|
||
"2022-06-01 19:36:25,000\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00086\n",
|
||
"2022-06-01 19:36:25,036\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00087\n",
|
||
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|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00078:\n",
|
||
" accuracy: 0.4585403133358808\n",
|
||
" date: 2022-06-01_19-36-25\n",
|
||
" done: false\n",
|
||
" experiment_id: 05cf4e42835d4cac825caaf30c744611\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13830\n",
|
||
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|
||
" time_this_iter_s: 17.114872217178345\n",
|
||
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|
||
" timestamp: 1654101385\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00078\n",
|
||
" warmup_time: 0.005684852600097656\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00078:\n",
|
||
" accuracy: 0.4585403133358808\n",
|
||
" date: 2022-06-01_19-36-25\n",
|
||
" done: true\n",
|
||
" experiment_id: 05cf4e42835d4cac825caaf30c744611\n",
|
||
" experiment_tag: 78_k_dev=1.6268,value_type=open,window=5\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13830\n",
|
||
" time_since_restore: 17.114872217178345\n",
|
||
" time_this_iter_s: 17.114872217178345\n",
|
||
" time_total_s: 17.114872217178345\n",
|
||
" timestamp: 1654101385\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00078\n",
|
||
" warmup_time: 0.005684852600097656\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00077:\n",
|
||
" accuracy: 0.4559561843906892\n",
|
||
" date: 2022-06-01_19-36-25\n",
|
||
" done: false\n",
|
||
" experiment_id: e4e4fa5c0a5147e584ffa27364f39209\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13827\n",
|
||
" time_since_restore: 16.75250744819641\n",
|
||
" time_this_iter_s: 16.75250744819641\n",
|
||
" time_total_s: 16.75250744819641\n",
|
||
" timestamp: 1654101385\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00077\n",
|
||
" warmup_time: 0.007216453552246094\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00077:\n",
|
||
" accuracy: 0.4559561843906892\n",
|
||
" date: 2022-06-01_19-36-25\n",
|
||
" done: true\n",
|
||
" experiment_id: e4e4fa5c0a5147e584ffa27364f39209\n",
|
||
" experiment_tag: 77_k_dev=1.2107,value_type=high,window=65\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13827\n",
|
||
" time_since_restore: 16.75250744819641\n",
|
||
" time_this_iter_s: 16.75250744819641\n",
|
||
" time_total_s: 16.75250744819641\n",
|
||
" timestamp: 1654101385\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00077\n",
|
||
" warmup_time: 0.007216453552246094\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00080:\n",
|
||
" accuracy: 0.46834892321078964\n",
|
||
" date: 2022-06-01_19-36-25\n",
|
||
" done: false\n",
|
||
" experiment_id: 5439f63b673040bf80805d6a58a7c24b\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13834\n",
|
||
" time_since_restore: 16.246959686279297\n",
|
||
" time_this_iter_s: 16.246959686279297\n",
|
||
" time_total_s: 16.246959686279297\n",
|
||
" timestamp: 1654101385\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00080\n",
|
||
" warmup_time: 0.26204538345336914\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00080:\n",
|
||
" accuracy: 0.46834892321078964\n",
|
||
" date: 2022-06-01_19-36-25\n",
|
||
" done: true\n",
|
||
" experiment_id: 5439f63b673040bf80805d6a58a7c24b\n",
|
||
" experiment_tag: 80_k_dev=1.2051,value_type=low,window=45\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 13834\n",
|
||
" time_since_restore: 16.246959686279297\n",
|
||
" time_this_iter_s: 16.246959686279297\n",
|
||
" time_total_s: 16.246959686279297\n",
|
||
" timestamp: 1654101385\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00080\n",
|
||
" warmup_time: 0.26204538345336914\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:36:25,986\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00089\n",
|
||
"2022-06-01 19:36:26,013\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00090\n",
|
||
"2022-06-01 19:36:26,046\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00091\n",
|
||
"2022-06-01 19:36:26,063\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00092\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:36:31 (running for 00:02:40.43)<br>Memory usage on this node: 12.7/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00038 with accuracy=0.5743243243243243 and parameters={'window': 80, 'value_type': 'low', 'k_dev': 3.3368279156307263}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 100/100 (7 PENDING, 12 RUNNING, 81 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00081</td><td>RUNNING </td><td>192.168.1.14:14113</td><td style=\"text-align: right;\">1.95156</td><td>close </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00082</td><td>RUNNING </td><td>192.168.1.14:14211</td><td style=\"text-align: right;\">2.08625</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00083</td><td>RUNNING </td><td>192.168.1.14:14229</td><td style=\"text-align: right;\">3.11219</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00084</td><td>RUNNING </td><td>192.168.1.14:14234</td><td style=\"text-align: right;\">2.89401</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00085</td><td>RUNNING </td><td>192.168.1.14:14412</td><td style=\"text-align: right;\">3.16614</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00086</td><td>RUNNING </td><td>192.168.1.14:14434</td><td style=\"text-align: right;\">3.62232</td><td>high </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00087</td><td>RUNNING </td><td>192.168.1.14:14447</td><td style=\"text-align: right;\">1.35735</td><td>open </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00093</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.20476</td><td>close </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00094</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.12346</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00095</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.92859</td><td>low </td><td style=\"text-align: right;\"> 100</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00096</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.09419</td><td>close </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00097</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.54937</td><td>high </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00098</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.0235 </td><td>high </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00099</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.5238 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 80 more trials not shown (5 RUNNING, 74 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00081:\n",
|
||
" accuracy: 0.4825543120473996\n",
|
||
" date: 2022-06-01_19-36-32\n",
|
||
" done: false\n",
|
||
" experiment_id: e80efddfed334791917a0bbeaeb800d9\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14113\n",
|
||
" time_since_restore: 15.734897375106812\n",
|
||
" time_this_iter_s: 15.734897375106812\n",
|
||
" time_total_s: 15.734897375106812\n",
|
||
" timestamp: 1654101392\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00081\n",
|
||
" warmup_time: 0.00399470329284668\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00081:\n",
|
||
" accuracy: 0.4825543120473996\n",
|
||
" date: 2022-06-01_19-36-32\n",
|
||
" done: true\n",
|
||
" experiment_id: e80efddfed334791917a0bbeaeb800d9\n",
|
||
" experiment_tag: 81_k_dev=1.9516,value_type=close,window=70\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14113\n",
|
||
" time_since_restore: 15.734897375106812\n",
|
||
" time_this_iter_s: 15.734897375106812\n",
|
||
" time_total_s: 15.734897375106812\n",
|
||
" timestamp: 1654101392\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00081\n",
|
||
" warmup_time: 0.00399470329284668\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:36:33,959\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00093\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00083:\n",
|
||
" accuracy: 0.5508021390374331\n",
|
||
" date: 2022-06-01_19-36-37\n",
|
||
" done: false\n",
|
||
" experiment_id: 68e194714d394037802509fc73bf3341\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14229\n",
|
||
" time_since_restore: 14.196528196334839\n",
|
||
" time_this_iter_s: 14.196528196334839\n",
|
||
" time_total_s: 14.196528196334839\n",
|
||
" timestamp: 1654101397\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00083\n",
|
||
" warmup_time: 0.00455474853515625\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:36:39 (running for 00:02:48.31)<br>Memory usage on this node: 12.8/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00038 with accuracy=0.5743243243243243 and parameters={'window': 80, 'value_type': 'low', 'k_dev': 3.3368279156307263}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 100/100 (6 PENDING, 12 RUNNING, 82 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00082</td><td>RUNNING </td><td>192.168.1.14:14211</td><td style=\"text-align: right;\">2.08625</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00083</td><td>RUNNING </td><td>192.168.1.14:14229</td><td style=\"text-align: right;\">3.11219</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.1965</td><td style=\"text-align: right;\"> 0.550802</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00084</td><td>RUNNING </td><td>192.168.1.14:14234</td><td style=\"text-align: right;\">2.89401</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00085</td><td>RUNNING </td><td>192.168.1.14:14412</td><td style=\"text-align: right;\">3.16614</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00086</td><td>RUNNING </td><td>192.168.1.14:14434</td><td style=\"text-align: right;\">3.62232</td><td>high </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00087</td><td>RUNNING </td><td>192.168.1.14:14447</td><td style=\"text-align: right;\">1.35735</td><td>open </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00088</td><td>RUNNING </td><td>192.168.1.14:14450</td><td style=\"text-align: right;\">3.48118</td><td>low </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00094</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.12346</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00095</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">3.92859</td><td>low </td><td style=\"text-align: right;\"> 100</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00096</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.09419</td><td>close </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00097</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.54937</td><td>high </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00098</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.0235 </td><td>high </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00099</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.5238 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 80 more trials not shown (5 RUNNING, 75 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00084:\n",
|
||
" accuracy: 0.5492537313432836\n",
|
||
" date: 2022-06-01_19-36-38\n",
|
||
" done: false\n",
|
||
" experiment_id: a1285ddec35b4d6fb17e3cf15b0e8c70\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14234\n",
|
||
" time_since_restore: 15.186134576797485\n",
|
||
" time_this_iter_s: 15.186134576797485\n",
|
||
" time_total_s: 15.186134576797485\n",
|
||
" timestamp: 1654101398\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00084\n",
|
||
" warmup_time: 0.004622220993041992\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00083:\n",
|
||
" accuracy: 0.5508021390374331\n",
|
||
" date: 2022-06-01_19-36-37\n",
|
||
" done: true\n",
|
||
" experiment_id: 68e194714d394037802509fc73bf3341\n",
|
||
" experiment_tag: 83_k_dev=3.1122,value_type=close,window=85\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14229\n",
|
||
" time_since_restore: 14.196528196334839\n",
|
||
" time_this_iter_s: 14.196528196334839\n",
|
||
" time_total_s: 14.196528196334839\n",
|
||
" timestamp: 1654101397\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00083\n",
|
||
" warmup_time: 0.00455474853515625\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00084:\n",
|
||
" accuracy: 0.5492537313432836\n",
|
||
" date: 2022-06-01_19-36-38\n",
|
||
" done: true\n",
|
||
" experiment_id: a1285ddec35b4d6fb17e3cf15b0e8c70\n",
|
||
" experiment_tag: 84_k_dev=2.894,value_type=low,window=80\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14234\n",
|
||
" time_since_restore: 15.186134576797485\n",
|
||
" time_this_iter_s: 15.186134576797485\n",
|
||
" time_total_s: 15.186134576797485\n",
|
||
" timestamp: 1654101398\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00084\n",
|
||
" warmup_time: 0.004622220993041992\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00082:\n",
|
||
" accuracy: 0.488822652757079\n",
|
||
" date: 2022-06-01_19-36-38\n",
|
||
" done: false\n",
|
||
" experiment_id: f3e2537da0a3458eafb56c4c958f161a\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14211\n",
|
||
" time_since_restore: 15.285579681396484\n",
|
||
" time_this_iter_s: 15.285579681396484\n",
|
||
" time_total_s: 15.285579681396484\n",
|
||
" timestamp: 1654101398\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00082\n",
|
||
" warmup_time: 0.008325338363647461\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00082:\n",
|
||
" accuracy: 0.488822652757079\n",
|
||
" date: 2022-06-01_19-36-38\n",
|
||
" done: true\n",
|
||
" experiment_id: f3e2537da0a3458eafb56c4c958f161a\n",
|
||
" experiment_tag: 82_k_dev=2.0863,value_type=low,window=70\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14211\n",
|
||
" time_since_restore: 15.285579681396484\n",
|
||
" time_this_iter_s: 15.285579681396484\n",
|
||
" time_total_s: 15.285579681396484\n",
|
||
" timestamp: 1654101398\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00082\n",
|
||
" warmup_time: 0.008325338363647461\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:36:40,962\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00094\n",
|
||
"2022-06-01 19:36:40,999\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00095\n",
|
||
"2022-06-01 19:36:41,059\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00096\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00086:\n",
|
||
" accuracy: 0.527027027027027\n",
|
||
" date: 2022-06-01_19-36-43\n",
|
||
" done: false\n",
|
||
" experiment_id: 4d1bc112963146f6aaa3e1c553df81c6\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14434\n",
|
||
" time_since_restore: 14.395161628723145\n",
|
||
" time_this_iter_s: 14.395161628723145\n",
|
||
" time_total_s: 14.395161628723145\n",
|
||
" timestamp: 1654101403\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00086\n",
|
||
" warmup_time: 0.012499094009399414\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:36:45 (running for 00:02:54.93)<br>Memory usage on this node: 12.8/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 12.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00038 with accuracy=0.5743243243243243 and parameters={'window': 80, 'value_type': 'low', 'k_dev': 3.3368279156307263}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 100/100 (3 PENDING, 12 RUNNING, 85 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00085</td><td>RUNNING </td><td>192.168.1.14:14412</td><td style=\"text-align: right;\">3.16614</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00086</td><td>RUNNING </td><td>192.168.1.14:14434</td><td style=\"text-align: right;\">3.62232</td><td>high </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.3952</td><td style=\"text-align: right;\"> 0.527027</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00087</td><td>RUNNING </td><td>192.168.1.14:14447</td><td style=\"text-align: right;\">1.35735</td><td>open </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00088</td><td>RUNNING </td><td>192.168.1.14:14450</td><td style=\"text-align: right;\">3.48118</td><td>low </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00089</td><td>RUNNING </td><td>192.168.1.14:14456</td><td style=\"text-align: right;\">3.29228</td><td>open </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00090</td><td>RUNNING </td><td>192.168.1.14:14466</td><td style=\"text-align: right;\">1.59333</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00091</td><td>RUNNING </td><td>192.168.1.14:14490</td><td style=\"text-align: right;\">1.57782</td><td>low </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00092</td><td>RUNNING </td><td>192.168.1.14:14497</td><td style=\"text-align: right;\">2.69285</td><td>close </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00093</td><td>RUNNING </td><td>192.168.1.14:14747</td><td style=\"text-align: right;\">2.20476</td><td>close </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00097</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">1.54937</td><td>high </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00098</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.0235 </td><td>high </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00099</td><td>PENDING </td><td> </td><td style=\"text-align: right;\">2.5238 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00007</td><td>TERMINATED</td><td>192.168.1.14:10031</td><td style=\"text-align: right;\">2.04865</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5712</td><td style=\"text-align: right;\"> 0.490678</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00008</td><td>TERMINATED</td><td>192.168.1.14:10033</td><td style=\"text-align: right;\">2.38263</td><td>high </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.9762</td><td style=\"text-align: right;\"> 0.460823</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 80 more trials not shown (3 RUNNING, 76 TERMINATED)<br><br>"
|
||
],
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00085:\n",
|
||
" accuracy: 0.49828178694158076\n",
|
||
" date: 2022-06-01_19-36-44\n",
|
||
" done: false\n",
|
||
" experiment_id: 915dbecc6e4743ed8d6b6ceea4045389\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14412\n",
|
||
" time_since_restore: 14.416006565093994\n",
|
||
" time_this_iter_s: 14.416006565093994\n",
|
||
" time_total_s: 14.416006565093994\n",
|
||
" timestamp: 1654101404\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00085\n",
|
||
" warmup_time: 0.004936695098876953\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00088:\n",
|
||
" accuracy: 0.5288461538461539\n",
|
||
" date: 2022-06-01_19-36-44\n",
|
||
" done: false\n",
|
||
" experiment_id: 5ccbea3fe82a42128fe3ca5a8c190016\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14450\n",
|
||
" time_since_restore: 14.747365713119507\n",
|
||
" time_this_iter_s: 14.747365713119507\n",
|
||
" time_total_s: 14.747365713119507\n",
|
||
" timestamp: 1654101404\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00088\n",
|
||
" warmup_time: 0.006840944290161133\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00087:\n",
|
||
" accuracy: 0.4624463519313305\n",
|
||
" date: 2022-06-01_19-36-45\n",
|
||
" done: false\n",
|
||
" experiment_id: 64eb60eb42bd4252b19e8b6232e15c35\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14447\n",
|
||
" time_since_restore: 16.504238843917847\n",
|
||
" time_this_iter_s: 16.504238843917847\n",
|
||
" time_total_s: 16.504238843917847\n",
|
||
" timestamp: 1654101405\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00087\n",
|
||
" warmup_time: 0.004414796829223633\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00092:\n",
|
||
" accuracy: 0.5157384987893463\n",
|
||
" date: 2022-06-01_19-36-45\n",
|
||
" done: false\n",
|
||
" experiment_id: c54a3677155c463ba1f2454ab57e7e78\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14497\n",
|
||
" time_since_restore: 14.131156206130981\n",
|
||
" time_this_iter_s: 14.131156206130981\n",
|
||
" time_total_s: 14.131156206130981\n",
|
||
" timestamp: 1654101405\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00092\n",
|
||
" warmup_time: 0.00782012939453125\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00085:\n",
|
||
" accuracy: 0.49828178694158076\n",
|
||
" date: 2022-06-01_19-36-44\n",
|
||
" done: true\n",
|
||
" experiment_id: 915dbecc6e4743ed8d6b6ceea4045389\n",
|
||
" experiment_tag: 85_k_dev=3.1661,value_type=high,window=20\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14412\n",
|
||
" time_since_restore: 14.416006565093994\n",
|
||
" time_this_iter_s: 14.416006565093994\n",
|
||
" time_total_s: 14.416006565093994\n",
|
||
" timestamp: 1654101404\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00085\n",
|
||
" warmup_time: 0.004936695098876953\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00086:\n",
|
||
" accuracy: 0.527027027027027\n",
|
||
" date: 2022-06-01_19-36-43\n",
|
||
" done: true\n",
|
||
" experiment_id: 4d1bc112963146f6aaa3e1c553df81c6\n",
|
||
" experiment_tag: 86_k_dev=3.6223,value_type=high,window=65\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14434\n",
|
||
" time_since_restore: 14.395161628723145\n",
|
||
" time_this_iter_s: 14.395161628723145\n",
|
||
" time_total_s: 14.395161628723145\n",
|
||
" timestamp: 1654101403\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00086\n",
|
||
" warmup_time: 0.012499094009399414\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00089:\n",
|
||
" accuracy: 0.5414012738853503\n",
|
||
" date: 2022-06-01_19-36-46\n",
|
||
" done: false\n",
|
||
" experiment_id: d4576f90f68c4b06b281b20e907bba08\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14456\n",
|
||
" time_since_restore: 14.836263418197632\n",
|
||
" time_this_iter_s: 14.836263418197632\n",
|
||
" time_total_s: 14.836263418197632\n",
|
||
" timestamp: 1654101406\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00089\n",
|
||
" warmup_time: 0.005787372589111328\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00088:\n",
|
||
" accuracy: 0.5288461538461539\n",
|
||
" date: 2022-06-01_19-36-44\n",
|
||
" done: true\n",
|
||
" experiment_id: 5ccbea3fe82a42128fe3ca5a8c190016\n",
|
||
" experiment_tag: 88_k_dev=3.4812,value_type=low,window=50\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14450\n",
|
||
" time_since_restore: 14.747365713119507\n",
|
||
" time_this_iter_s: 14.747365713119507\n",
|
||
" time_total_s: 14.747365713119507\n",
|
||
" timestamp: 1654101404\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00088\n",
|
||
" warmup_time: 0.006840944290161133\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00092:\n",
|
||
" accuracy: 0.5157384987893463\n",
|
||
" date: 2022-06-01_19-36-45\n",
|
||
" done: true\n",
|
||
" experiment_id: c54a3677155c463ba1f2454ab57e7e78\n",
|
||
" experiment_tag: 92_k_dev=2.6929,value_type=close,window=95\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14497\n",
|
||
" time_since_restore: 14.131156206130981\n",
|
||
" time_this_iter_s: 14.131156206130981\n",
|
||
" time_total_s: 14.131156206130981\n",
|
||
" timestamp: 1654101405\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00092\n",
|
||
" warmup_time: 0.00782012939453125\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00089:\n",
|
||
" accuracy: 0.5414012738853503\n",
|
||
" date: 2022-06-01_19-36-46\n",
|
||
" done: true\n",
|
||
" experiment_id: d4576f90f68c4b06b281b20e907bba08\n",
|
||
" experiment_tag: 89_k_dev=3.2923,value_type=open,window=60\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14456\n",
|
||
" time_since_restore: 14.836263418197632\n",
|
||
" time_this_iter_s: 14.836263418197632\n",
|
||
" time_total_s: 14.836263418197632\n",
|
||
" timestamp: 1654101406\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00089\n",
|
||
" warmup_time: 0.005787372589111328\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00087:\n",
|
||
" accuracy: 0.4624463519313305\n",
|
||
" date: 2022-06-01_19-36-45\n",
|
||
" done: true\n",
|
||
" experiment_id: 64eb60eb42bd4252b19e8b6232e15c35\n",
|
||
" experiment_tag: 87_k_dev=1.3573,value_type=open,window=95\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14447\n",
|
||
" time_since_restore: 16.504238843917847\n",
|
||
" time_this_iter_s: 16.504238843917847\n",
|
||
" time_total_s: 16.504238843917847\n",
|
||
" timestamp: 1654101405\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00087\n",
|
||
" warmup_time: 0.004414796829223633\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00091:\n",
|
||
" accuracy: 0.47282796815507094\n",
|
||
" date: 2022-06-01_19-36-46\n",
|
||
" done: false\n",
|
||
" experiment_id: aa2302db24f14f77971fdc4e76f12d09\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14490\n",
|
||
" time_since_restore: 15.525084257125854\n",
|
||
" time_this_iter_s: 15.525084257125854\n",
|
||
" time_total_s: 15.525084257125854\n",
|
||
" timestamp: 1654101406\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00091\n",
|
||
" warmup_time: 0.005910396575927734\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00091:\n",
|
||
" accuracy: 0.47282796815507094\n",
|
||
" date: 2022-06-01_19-36-46\n",
|
||
" done: true\n",
|
||
" experiment_id: aa2302db24f14f77971fdc4e76f12d09\n",
|
||
" experiment_tag: 91_k_dev=1.5778,value_type=low,window=85\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14490\n",
|
||
" time_since_restore: 15.525084257125854\n",
|
||
" time_this_iter_s: 15.525084257125854\n",
|
||
" time_total_s: 15.525084257125854\n",
|
||
" timestamp: 1654101406\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00091\n",
|
||
" warmup_time: 0.005910396575927734\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00090:\n",
|
||
" accuracy: 0.47183098591549294\n",
|
||
" date: 2022-06-01_19-36-46\n",
|
||
" done: false\n",
|
||
" experiment_id: df305c8632e04c71914de8098c07048b\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14466\n",
|
||
" time_since_restore: 15.784619331359863\n",
|
||
" time_this_iter_s: 15.784619331359863\n",
|
||
" time_total_s: 15.784619331359863\n",
|
||
" timestamp: 1654101406\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00090\n",
|
||
" warmup_time: 0.004984378814697266\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00090:\n",
|
||
" accuracy: 0.47183098591549294\n",
|
||
" date: 2022-06-01_19-36-46\n",
|
||
" done: true\n",
|
||
" experiment_id: df305c8632e04c71914de8098c07048b\n",
|
||
" experiment_tag: 90_k_dev=1.5933,value_type=close,window=85\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14466\n",
|
||
" time_since_restore: 15.784619331359863\n",
|
||
" time_this_iter_s: 15.784619331359863\n",
|
||
" time_total_s: 15.784619331359863\n",
|
||
" timestamp: 1654101406\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00090\n",
|
||
" warmup_time: 0.004984378814697266\n",
|
||
" \n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:36:47,794\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00097\n",
|
||
"2022-06-01 19:36:47,803\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00098\n",
|
||
"2022-06-01 19:36:47,835\tINFO trial_runner.py:803 -- starting trainable_9e7a8_00099\n",
|
||
"IOPub data rate exceeded.\n",
|
||
"The notebook server will temporarily stop sending output\n",
|
||
"to the client in order to avoid crashing it.\n",
|
||
"To change this limit, set the config variable\n",
|
||
"`--NotebookApp.iopub_data_rate_limit`.\n",
|
||
"\n",
|
||
"Current values:\n",
|
||
"NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
|
||
"NotebookApp.rate_limit_window=3.0 (secs)\n",
|
||
"\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/html": [
|
||
"== Status ==<br>Current time: 2022-06-01 19:36:51 (running for 00:03:00.87)<br>Memory usage on this node: 12.3/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 7.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00038 with accuracy=0.5743243243243243 and parameters={'window': 80, 'value_type': 'low', 'k_dev': 3.3368279156307263}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 100/100 (7 RUNNING, 93 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00093</td><td>RUNNING </td><td>192.168.1.14:14747</td><td style=\"text-align: right;\">2.20476</td><td>close </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 11.525 </td><td style=\"text-align: right;\"> 0.488419</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00094</td><td>RUNNING </td><td>192.168.1.14:14858</td><td style=\"text-align: right;\">3.12346</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00095</td><td>RUNNING </td><td>192.168.1.14:14861</td><td style=\"text-align: right;\">3.92859</td><td>low </td><td style=\"text-align: right;\"> 100</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00096</td><td>RUNNING </td><td>192.168.1.14:14872</td><td style=\"text-align: right;\">2.09419</td><td>close </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00097</td><td>RUNNING </td><td>192.168.1.14:15039</td><td style=\"text-align: right;\">1.54937</td><td>high </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00098</td><td>RUNNING </td><td>192.168.1.14:15042</td><td style=\"text-align: right;\">2.0235 </td><td>high </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00099</td><td>RUNNING </td><td>192.168.1.14:15053</td><td style=\"text-align: right;\">2.5238 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399</td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833</td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379</td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834</td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791</td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243</td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00007</td><td>TERMINATED</td><td>192.168.1.14:10031</td><td style=\"text-align: right;\">2.04865</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5712</td><td style=\"text-align: right;\"> 0.490678</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00008</td><td>TERMINATED</td><td>192.168.1.14:10033</td><td style=\"text-align: right;\">2.38263</td><td>high </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.9762</td><td style=\"text-align: right;\"> 0.460823</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00009</td><td>TERMINATED</td><td>192.168.1.14:10035</td><td style=\"text-align: right;\">2.9824 </td><td>low </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.9972</td><td style=\"text-align: right;\"> 0.546099</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00010</td><td>TERMINATED</td><td>192.168.1.14:10036</td><td style=\"text-align: right;\">1.96683</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.459 </td><td style=\"text-align: right;\"> 0.488717</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00011</td><td>TERMINATED</td><td>192.168.1.14:10038</td><td style=\"text-align: right;\">1.36129</td><td>low </td><td style=\"text-align: right;\"> 5</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.2408</td><td style=\"text-align: right;\"> 0.467798</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00012</td><td>TERMINATED</td><td>192.168.1.14:10448</td><td style=\"text-align: right;\">3.81256</td><td>open </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.0255</td><td style=\"text-align: right;\"> 0.512111</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 80 more trials not shown (80 TERMINATED)<br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Result for trainable_9e7a8_00093:\n",
|
||
" accuracy: 0.48841893252769386\n",
|
||
" date: 2022-06-01_19-36-50\n",
|
||
" done: true\n",
|
||
" experiment_id: a055b602ae964ee4b83749c84beb8ceb\n",
|
||
" experiment_tag: 93_k_dev=2.2048,value_type=close,window=90\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14747\n",
|
||
" time_since_restore: 11.524987936019897\n",
|
||
" time_this_iter_s: 11.524987936019897\n",
|
||
" time_total_s: 11.524987936019897\n",
|
||
" timestamp: 1654101410\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
" trial_id: 9e7a8_00093\n",
|
||
" warmup_time: 0.004125833511352539\n",
|
||
" \n",
|
||
"Result for trainable_9e7a8_00095:\n",
|
||
" accuracy: 0.5932203389830508\n",
|
||
" date: 2022-06-01_19-36-52\n",
|
||
" done: false\n",
|
||
" experiment_id: 07e454d618834c0f8b1dc16cd1beeb67\n",
|
||
" hostname: parf\n",
|
||
" iterations_since_restore: 1\n",
|
||
" node_ip: 192.168.1.14\n",
|
||
" pid: 14861\n",
|
||
" time_since_restore: 7.350056171417236\n",
|
||
" time_this_iter_s: 7.350056171417236\n",
|
||
" time_total_s: 7.350056171417236\n",
|
||
" timestamp: 1654101412\n",
|
||
" timesteps_since_restore: 0\n",
|
||
" training_iteration: 1\n",
|
||
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|
||
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|
||
" \n",
|
||
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|
||
" accuracy: 0.5932203389830508\n",
|
||
" date: 2022-06-01_19-36-52\n",
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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||
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|
||
" \n",
|
||
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|
||
" accuracy: 0.47588717015468607\n",
|
||
" date: 2022-06-01_19-36-53\n",
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||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" accuracy: 0.5436507936507936\n",
|
||
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|
||
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|
||
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|
||
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|
||
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|
||
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|
||
" date: 2022-06-01_19-36-57\n",
|
||
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"== Status ==<br>Current time: 2022-06-01 19:36:57 (running for 00:03:06.68)<br>Memory usage on this node: 11.8/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 3.0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00095 with accuracy=0.5932203389830508 and parameters={'window': 100, 'value_type': 'low', 'k_dev': 3.9285854094927943}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 100/100 (3 RUNNING, 97 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00097</td><td>RUNNING </td><td>192.168.1.14:15039</td><td style=\"text-align: right;\">1.54937</td><td>high </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00098</td><td>RUNNING </td><td>192.168.1.14:15042</td><td style=\"text-align: right;\">2.0235 </td><td>high </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td><td style=\"text-align: right;\"> </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00099</td><td>RUNNING </td><td>192.168.1.14:15053</td><td style=\"text-align: right;\">2.5238 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 6.57313</td><td style=\"text-align: right;\"> 0.50361 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399 </td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833 </td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379 </td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834 </td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791 </td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243 </td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00007</td><td>TERMINATED</td><td>192.168.1.14:10031</td><td style=\"text-align: right;\">2.04865</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5712 </td><td style=\"text-align: right;\"> 0.490678</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00008</td><td>TERMINATED</td><td>192.168.1.14:10033</td><td style=\"text-align: right;\">2.38263</td><td>high </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.9762 </td><td style=\"text-align: right;\"> 0.460823</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00009</td><td>TERMINATED</td><td>192.168.1.14:10035</td><td style=\"text-align: right;\">2.9824 </td><td>low </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.9972 </td><td style=\"text-align: right;\"> 0.546099</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00010</td><td>TERMINATED</td><td>192.168.1.14:10036</td><td style=\"text-align: right;\">1.96683</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.459 </td><td style=\"text-align: right;\"> 0.488717</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00011</td><td>TERMINATED</td><td>192.168.1.14:10038</td><td style=\"text-align: right;\">1.36129</td><td>low </td><td style=\"text-align: right;\"> 5</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.2408 </td><td style=\"text-align: right;\"> 0.467798</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00012</td><td>TERMINATED</td><td>192.168.1.14:10448</td><td style=\"text-align: right;\">3.81256</td><td>open </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.0255 </td><td style=\"text-align: right;\"> 0.512111</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00013</td><td>TERMINATED</td><td>192.168.1.14:10694</td><td style=\"text-align: right;\">1.80733</td><td>high </td><td style=\"text-align: right;\"> 35</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.5294 </td><td style=\"text-align: right;\"> 0.469178</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00014</td><td>TERMINATED</td><td>192.168.1.14:10705</td><td style=\"text-align: right;\">1.52009</td><td>low </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 16.2017 </td><td style=\"text-align: right;\"> 0.477317</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00015</td><td>TERMINATED</td><td>192.168.1.14:10718</td><td style=\"text-align: right;\">1.5003 </td><td>high </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 17.1894 </td><td style=\"text-align: right;\"> 0.463359</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00016</td><td>TERMINATED</td><td>192.168.1.14:10738</td><td style=\"text-align: right;\">3.82771</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.3816 </td><td style=\"text-align: right;\"> 0.555556</td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br>... 80 more trials not shown (80 TERMINATED)<br><br>"
|
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|
||
"Result for trainable_9e7a8_00099:\n",
|
||
" accuracy: 0.5036101083032491\n",
|
||
" date: 2022-06-01_19-36-57\n",
|
||
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|
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|
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|
||
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|
||
"Result for trainable_9e7a8_00098:\n",
|
||
" accuracy: 0.47390396659707723\n",
|
||
" date: 2022-06-01_19-36-58\n",
|
||
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|
||
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|
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|
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|
||
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|
||
" accuracy: 0.47390396659707723\n",
|
||
" date: 2022-06-01_19-36-58\n",
|
||
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|
||
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|
||
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|
||
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|
||
" accuracy: 0.46994160082445896\n",
|
||
" date: 2022-06-01_19-36-58\n",
|
||
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|
||
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|
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|
||
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|
||
" accuracy: 0.46994160082445896\n",
|
||
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|
||
"== Status ==<br>Current time: 2022-06-01 19:36:58 (running for 00:03:07.45)<br>Memory usage on this node: 11.5/15.5 GiB<br>Using FIFO scheduling algorithm.<br>Resources requested: 0/12 CPUs, 0/1 GPUs, 0.0/4.27 GiB heap, 0.0/2.13 GiB objects (0.0/1.0 accelerator_type:G)<br>Current best trial: 9e7a8_00095 with accuracy=0.5932203389830508 and parameters={'window': 100, 'value_type': 'low', 'k_dev': 3.9285854094927943}<br>Result logdir: /home/parf/ray_results/trainable_2022-06-01_19-33-51<br>Number of trials: 100/100 (100 TERMINATED)<br><table>\n",
|
||
"<thead>\n",
|
||
"<tr><th>Trial name </th><th>status </th><th>loc </th><th style=\"text-align: right;\"> k_dev</th><th>value_type </th><th style=\"text-align: right;\"> window</th><th style=\"text-align: right;\"> iter</th><th style=\"text-align: right;\"> total time (s)</th><th style=\"text-align: right;\"> accuracy</th></tr>\n",
|
||
"</thead>\n",
|
||
"<tbody>\n",
|
||
"<tr><td>trainable_9e7a8_00000</td><td>TERMINATED</td><td>192.168.1.14:9985 </td><td style=\"text-align: right;\">3.58725</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7399 </td><td style=\"text-align: right;\"> 0.461538</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00001</td><td>TERMINATED</td><td>192.168.1.14:10019</td><td style=\"text-align: right;\">2.9955 </td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5833 </td><td style=\"text-align: right;\"> 0.507092</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00002</td><td>TERMINATED</td><td>192.168.1.14:10021</td><td style=\"text-align: right;\">3.91286</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0379 </td><td style=\"text-align: right;\"> 0.504348</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00003</td><td>TERMINATED</td><td>192.168.1.14:10023</td><td style=\"text-align: right;\">2.40783</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5834 </td><td style=\"text-align: right;\"> 0.497368</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00004</td><td>TERMINATED</td><td>192.168.1.14:10025</td><td style=\"text-align: right;\">2.83742</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6791 </td><td style=\"text-align: right;\"> 0.485861</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00005</td><td>TERMINATED</td><td>192.168.1.14:10026</td><td style=\"text-align: right;\">2.78332</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7243 </td><td style=\"text-align: right;\"> 0.517321</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00006</td><td>TERMINATED</td><td>192.168.1.14:10029</td><td style=\"text-align: right;\">2.02252</td><td>low </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.946 </td><td style=\"text-align: right;\"> 0.488022</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00007</td><td>TERMINATED</td><td>192.168.1.14:10031</td><td style=\"text-align: right;\">2.04865</td><td>close </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.5712 </td><td style=\"text-align: right;\"> 0.490678</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00008</td><td>TERMINATED</td><td>192.168.1.14:10033</td><td style=\"text-align: right;\">2.38263</td><td>high </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.9762 </td><td style=\"text-align: right;\"> 0.460823</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00009</td><td>TERMINATED</td><td>192.168.1.14:10035</td><td style=\"text-align: right;\">2.9824 </td><td>low </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.9972 </td><td style=\"text-align: right;\"> 0.546099</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00010</td><td>TERMINATED</td><td>192.168.1.14:10036</td><td style=\"text-align: right;\">1.96683</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.459 </td><td style=\"text-align: right;\"> 0.488717</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00011</td><td>TERMINATED</td><td>192.168.1.14:10038</td><td style=\"text-align: right;\">1.36129</td><td>low </td><td style=\"text-align: right;\"> 5</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.2408 </td><td style=\"text-align: right;\"> 0.467798</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00012</td><td>TERMINATED</td><td>192.168.1.14:10448</td><td style=\"text-align: right;\">3.81256</td><td>open </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.0255 </td><td style=\"text-align: right;\"> 0.512111</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00013</td><td>TERMINATED</td><td>192.168.1.14:10694</td><td style=\"text-align: right;\">1.80733</td><td>high </td><td style=\"text-align: right;\"> 35</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.5294 </td><td style=\"text-align: right;\"> 0.469178</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00014</td><td>TERMINATED</td><td>192.168.1.14:10705</td><td style=\"text-align: right;\">1.52009</td><td>low </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 16.2017 </td><td style=\"text-align: right;\"> 0.477317</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00015</td><td>TERMINATED</td><td>192.168.1.14:10718</td><td style=\"text-align: right;\">1.5003 </td><td>high </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 17.1894 </td><td style=\"text-align: right;\"> 0.463359</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00016</td><td>TERMINATED</td><td>192.168.1.14:10738</td><td style=\"text-align: right;\">3.82771</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.3816 </td><td style=\"text-align: right;\"> 0.555556</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00017</td><td>TERMINATED</td><td>192.168.1.14:10791</td><td style=\"text-align: right;\">2.9332 </td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.4006 </td><td style=\"text-align: right;\"> 0.488746</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00018</td><td>TERMINATED</td><td>192.168.1.14:10820</td><td style=\"text-align: right;\">1.97031</td><td>open </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.1525 </td><td style=\"text-align: right;\"> 0.485556</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00019</td><td>TERMINATED</td><td>192.168.1.14:10826</td><td style=\"text-align: right;\">3.3669 </td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7738 </td><td style=\"text-align: right;\"> 0.513043</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00020</td><td>TERMINATED</td><td>192.168.1.14:10827</td><td style=\"text-align: right;\">1.2511 </td><td>high </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 17.4874 </td><td style=\"text-align: right;\"> 0.454133</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00021</td><td>TERMINATED</td><td>192.168.1.14:10832</td><td style=\"text-align: right;\">1.18569</td><td>open </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 17.3648 </td><td style=\"text-align: right;\"> 0.459429</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00022</td><td>TERMINATED</td><td>192.168.1.14:10851</td><td style=\"text-align: right;\">2.9816 </td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 16.078 </td><td style=\"text-align: right;\"> 0.523297</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00023</td><td>TERMINATED</td><td>192.168.1.14:10853</td><td style=\"text-align: right;\">1.12381</td><td>close </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 17.483 </td><td style=\"text-align: right;\"> 0.45294 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00024</td><td>TERMINATED</td><td>192.168.1.14:11212</td><td style=\"text-align: right;\">2.37796</td><td>open </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.0993 </td><td style=\"text-align: right;\"> 0.495187</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00025</td><td>TERMINATED</td><td>192.168.1.14:11277</td><td style=\"text-align: right;\">3.76634</td><td>open </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.2495 </td><td style=\"text-align: right;\"> 0.539474</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00026</td><td>TERMINATED</td><td>192.168.1.14:11278</td><td style=\"text-align: right;\">1.58155</td><td>low </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.2918 </td><td style=\"text-align: right;\"> 0.472512</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00027</td><td>TERMINATED</td><td>192.168.1.14:11283</td><td style=\"text-align: right;\">2.00967</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.2923 </td><td style=\"text-align: right;\"> 0.496306</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00028</td><td>TERMINATED</td><td>192.168.1.14:11286</td><td style=\"text-align: right;\">3.50349</td><td>low </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.5072 </td><td style=\"text-align: right;\"> 0.520408</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00029</td><td>TERMINATED</td><td>192.168.1.14:11365</td><td style=\"text-align: right;\">3.12407</td><td>open </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.4316 </td><td style=\"text-align: right;\"> 0.528926</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00030</td><td>TERMINATED</td><td>192.168.1.14:11367</td><td style=\"text-align: right;\">2.93617</td><td>high </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.8449 </td><td style=\"text-align: right;\"> 0.482072</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00031</td><td>TERMINATED</td><td>192.168.1.14:11369</td><td style=\"text-align: right;\">2.56237</td><td>high </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.6788 </td><td style=\"text-align: right;\"> 0.45229 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00032</td><td>TERMINATED</td><td>192.168.1.14:11542</td><td style=\"text-align: right;\">2.71263</td><td>close </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.4148 </td><td style=\"text-align: right;\"> 0.505119</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00033</td><td>TERMINATED</td><td>192.168.1.14:11545</td><td style=\"text-align: right;\">1.61494</td><td>close </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.1469 </td><td style=\"text-align: right;\"> 0.482875</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00034</td><td>TERMINATED</td><td>192.168.1.14:11548</td><td style=\"text-align: right;\">2.25605</td><td>open </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.9088 </td><td style=\"text-align: right;\"> 0.496572</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00035</td><td>TERMINATED</td><td>192.168.1.14:11549</td><td style=\"text-align: right;\">1.19443</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 17.696 </td><td style=\"text-align: right;\"> 0.455859</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00036</td><td>TERMINATED</td><td>192.168.1.14:11705</td><td style=\"text-align: right;\">2.10051</td><td>open </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.7228 </td><td style=\"text-align: right;\"> 0.479073</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00037</td><td>TERMINATED</td><td>192.168.1.14:11803</td><td style=\"text-align: right;\">2.1924 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.1245 </td><td style=\"text-align: right;\"> 0.487052</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00038</td><td>TERMINATED</td><td>192.168.1.14:11820</td><td style=\"text-align: right;\">3.33683</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.9513 </td><td style=\"text-align: right;\"> 0.574324</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00039</td><td>TERMINATED</td><td>192.168.1.14:11834</td><td style=\"text-align: right;\">2.42366</td><td>open </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0165 </td><td style=\"text-align: right;\"> 0.511318</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00040</td><td>TERMINATED</td><td>192.168.1.14:11842</td><td style=\"text-align: right;\">3.82909</td><td>low </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.4795 </td><td style=\"text-align: right;\"> 0.527132</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00041</td><td>TERMINATED</td><td>192.168.1.14:11844</td><td style=\"text-align: right;\">1.00435</td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 17.1685 </td><td style=\"text-align: right;\"> 0.455942</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00042</td><td>TERMINATED</td><td>192.168.1.14:11858</td><td style=\"text-align: right;\">2.13066</td><td>close </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.049 </td><td style=\"text-align: right;\"> 0.487709</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00043</td><td>TERMINATED</td><td>192.168.1.14:11860</td><td style=\"text-align: right;\">3.78005</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7974 </td><td style=\"text-align: right;\"> 0.55 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00044</td><td>TERMINATED</td><td>192.168.1.14:12123</td><td style=\"text-align: right;\">1.43104</td><td>close </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.7972 </td><td style=\"text-align: right;\"> 0.470256</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00045</td><td>TERMINATED</td><td>192.168.1.14:12141</td><td style=\"text-align: right;\">2.24024</td><td>open </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 12.4284 </td><td style=\"text-align: right;\"> 0.48528 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00046</td><td>TERMINATED</td><td>192.168.1.14:12145</td><td style=\"text-align: right;\">2.34936</td><td>open </td><td style=\"text-align: right;\"> 5</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.9976 </td><td style=\"text-align: right;\"> 0.469972</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00047</td><td>TERMINATED</td><td>192.168.1.14:12223</td><td style=\"text-align: right;\">3.95935</td><td>open </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 11.8977 </td><td style=\"text-align: right;\"> 0.559322</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00048</td><td>TERMINATED</td><td>192.168.1.14:12304</td><td style=\"text-align: right;\">2.62893</td><td>high </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 11.2398 </td><td style=\"text-align: right;\"> 0.499044</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00049</td><td>TERMINATED</td><td>192.168.1.14:12364</td><td style=\"text-align: right;\">2.98399</td><td>close </td><td style=\"text-align: right;\"> 55</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.6483 </td><td style=\"text-align: right;\"> 0.485876</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00050</td><td>TERMINATED</td><td>192.168.1.14:12456</td><td style=\"text-align: right;\">3.40408</td><td>close </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 12.2509 </td><td style=\"text-align: right;\"> 0.125 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00051</td><td>TERMINATED</td><td>192.168.1.14:12458</td><td style=\"text-align: right;\">1.63469</td><td>open </td><td style=\"text-align: right;\"> 15</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.8535 </td><td style=\"text-align: right;\"> 0.473944</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00052</td><td>TERMINATED</td><td>192.168.1.14:12459</td><td style=\"text-align: right;\">1.55978</td><td>close </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.8552 </td><td style=\"text-align: right;\"> 0.47585 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00053</td><td>TERMINATED</td><td>192.168.1.14:12461</td><td style=\"text-align: right;\">2.58736</td><td>high </td><td style=\"text-align: right;\"> 35</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.8318 </td><td style=\"text-align: right;\"> 0.443564</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00054</td><td>TERMINATED</td><td>192.168.1.14:12466</td><td style=\"text-align: right;\">1.46559</td><td>low </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.2653 </td><td style=\"text-align: right;\"> 0.47148 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00055</td><td>TERMINATED</td><td>192.168.1.14:12468</td><td style=\"text-align: right;\">2.74483</td><td>high </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 12.6813 </td><td style=\"text-align: right;\"> 0.489247</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00056</td><td>TERMINATED</td><td>192.168.1.14:12471</td><td style=\"text-align: right;\">2.93169</td><td>open </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.4231 </td><td style=\"text-align: right;\"> 0.516569</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00057</td><td>TERMINATED</td><td>192.168.1.14:12776</td><td style=\"text-align: right;\">3.34213</td><td>high </td><td style=\"text-align: right;\"> 10</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.1506 </td><td style=\"text-align: right;\"> 0.477745</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00058</td><td>TERMINATED</td><td>192.168.1.14:12847</td><td style=\"text-align: right;\">1.98504</td><td>high </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 16.3026 </td><td style=\"text-align: right;\"> 0.468586</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00059</td><td>TERMINATED</td><td>192.168.1.14:12849</td><td style=\"text-align: right;\">2.80529</td><td>open </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.4235 </td><td style=\"text-align: right;\"> 0.525424</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00060</td><td>TERMINATED</td><td>192.168.1.14:12852</td><td style=\"text-align: right;\">1.24152</td><td>close </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 17.0097 </td><td style=\"text-align: right;\"> 0.460865</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00061</td><td>TERMINATED</td><td>192.168.1.14:13083</td><td style=\"text-align: right;\">2.58144</td><td>close </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.886 </td><td style=\"text-align: right;\"> 0.510373</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00062</td><td>TERMINATED</td><td>192.168.1.14:13089</td><td style=\"text-align: right;\">1.61595</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.6194 </td><td style=\"text-align: right;\"> 0.47546 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00063</td><td>TERMINATED</td><td>192.168.1.14:13106</td><td style=\"text-align: right;\">1.88298</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.9946 </td><td style=\"text-align: right;\"> 0.484632</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00064</td><td>TERMINATED</td><td>192.168.1.14:13128</td><td style=\"text-align: right;\">2.87921</td><td>high </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.3861 </td><td style=\"text-align: right;\"> 0.501416</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00065</td><td>TERMINATED</td><td>192.168.1.14:13130</td><td style=\"text-align: right;\">3.3177 </td><td>low </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7332 </td><td style=\"text-align: right;\"> 0.54902 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00066</td><td>TERMINATED</td><td>192.168.1.14:13132</td><td style=\"text-align: right;\">1.65135</td><td>close </td><td style=\"text-align: right;\"> 75</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.9992 </td><td style=\"text-align: right;\"> 0.474268</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00067</td><td>TERMINATED</td><td>192.168.1.14:13133</td><td style=\"text-align: right;\">2.71342</td><td>low </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.0508 </td><td style=\"text-align: right;\"> 0.532895</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00068</td><td>TERMINATED</td><td>192.168.1.14:13135</td><td style=\"text-align: right;\">2.35478</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.3029 </td><td style=\"text-align: right;\"> 0.500579</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00069</td><td>TERMINATED</td><td>192.168.1.14:13414</td><td style=\"text-align: right;\">3.82523</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 13.3848 </td><td style=\"text-align: right;\"> 0.555556</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00070</td><td>TERMINATED</td><td>192.168.1.14:13512</td><td style=\"text-align: right;\">1.268 </td><td>low </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.2099 </td><td style=\"text-align: right;\"> 0.464319</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00071</td><td>TERMINATED</td><td>192.168.1.14:13529</td><td style=\"text-align: right;\">3.12592</td><td>high </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.354 </td><td style=\"text-align: right;\"> 0.520619</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00072</td><td>TERMINATED</td><td>192.168.1.14:13531</td><td style=\"text-align: right;\">3.23254</td><td>low </td><td style=\"text-align: right;\"> 30</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.4828 </td><td style=\"text-align: right;\"> 0.518018</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00073</td><td>TERMINATED</td><td>192.168.1.14:13769</td><td style=\"text-align: right;\">1.90762</td><td>close </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 16.1004 </td><td style=\"text-align: right;\"> 0.49475 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00074</td><td>TERMINATED</td><td>192.168.1.14:13785</td><td style=\"text-align: right;\">2.52124</td><td>low </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.8732 </td><td style=\"text-align: right;\"> 0.512903</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00075</td><td>TERMINATED</td><td>192.168.1.14:13813</td><td style=\"text-align: right;\">2.42818</td><td>close </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.5327 </td><td style=\"text-align: right;\"> 0.509506</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00076</td><td>TERMINATED</td><td>192.168.1.14:13816</td><td style=\"text-align: right;\">3.99823</td><td>high </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.2887 </td><td style=\"text-align: right;\"> 0.424242</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00077</td><td>TERMINATED</td><td>192.168.1.14:13827</td><td style=\"text-align: right;\">1.21075</td><td>high </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 16.7525 </td><td style=\"text-align: right;\"> 0.455956</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00078</td><td>TERMINATED</td><td>192.168.1.14:13830</td><td style=\"text-align: right;\">1.62677</td><td>open </td><td style=\"text-align: right;\"> 5</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 17.1149 </td><td style=\"text-align: right;\"> 0.45854 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00079</td><td>TERMINATED</td><td>192.168.1.14:13831</td><td style=\"text-align: right;\">3.45973</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.9029 </td><td style=\"text-align: right;\"> 0.532374</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00080</td><td>TERMINATED</td><td>192.168.1.14:13834</td><td style=\"text-align: right;\">1.20507</td><td>low </td><td style=\"text-align: right;\"> 45</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 16.247 </td><td style=\"text-align: right;\"> 0.468349</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00081</td><td>TERMINATED</td><td>192.168.1.14:14113</td><td style=\"text-align: right;\">1.95156</td><td>close </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.7349 </td><td style=\"text-align: right;\"> 0.482554</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00082</td><td>TERMINATED</td><td>192.168.1.14:14211</td><td style=\"text-align: right;\">2.08625</td><td>low </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.2856 </td><td style=\"text-align: right;\"> 0.488823</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00083</td><td>TERMINATED</td><td>192.168.1.14:14229</td><td style=\"text-align: right;\">3.11219</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.1965 </td><td style=\"text-align: right;\"> 0.550802</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00084</td><td>TERMINATED</td><td>192.168.1.14:14234</td><td style=\"text-align: right;\">2.89401</td><td>low </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.1861 </td><td style=\"text-align: right;\"> 0.549254</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00085</td><td>TERMINATED</td><td>192.168.1.14:14412</td><td style=\"text-align: right;\">3.16614</td><td>high </td><td style=\"text-align: right;\"> 20</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.416 </td><td style=\"text-align: right;\"> 0.498282</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00086</td><td>TERMINATED</td><td>192.168.1.14:14434</td><td style=\"text-align: right;\">3.62232</td><td>high </td><td style=\"text-align: right;\"> 65</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.3952 </td><td style=\"text-align: right;\"> 0.527027</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00087</td><td>TERMINATED</td><td>192.168.1.14:14447</td><td style=\"text-align: right;\">1.35735</td><td>open </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 16.5042 </td><td style=\"text-align: right;\"> 0.462446</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00088</td><td>TERMINATED</td><td>192.168.1.14:14450</td><td style=\"text-align: right;\">3.48118</td><td>low </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.7474 </td><td style=\"text-align: right;\"> 0.528846</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00089</td><td>TERMINATED</td><td>192.168.1.14:14456</td><td style=\"text-align: right;\">3.29228</td><td>open </td><td style=\"text-align: right;\"> 60</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.8363 </td><td style=\"text-align: right;\"> 0.541401</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00090</td><td>TERMINATED</td><td>192.168.1.14:14466</td><td style=\"text-align: right;\">1.59333</td><td>close </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.7846 </td><td style=\"text-align: right;\"> 0.471831</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00091</td><td>TERMINATED</td><td>192.168.1.14:14490</td><td style=\"text-align: right;\">1.57782</td><td>low </td><td style=\"text-align: right;\"> 85</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 15.5251 </td><td style=\"text-align: right;\"> 0.472828</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00092</td><td>TERMINATED</td><td>192.168.1.14:14497</td><td style=\"text-align: right;\">2.69285</td><td>close </td><td style=\"text-align: right;\"> 95</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 14.1312 </td><td style=\"text-align: right;\"> 0.515738</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00093</td><td>TERMINATED</td><td>192.168.1.14:14747</td><td style=\"text-align: right;\">2.20476</td><td>close </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 11.525 </td><td style=\"text-align: right;\"> 0.488419</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00094</td><td>TERMINATED</td><td>192.168.1.14:14858</td><td style=\"text-align: right;\">3.12346</td><td>open </td><td style=\"text-align: right;\"> 90</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 8.46505</td><td style=\"text-align: right;\"> 0.543651</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00095</td><td>TERMINATED</td><td>192.168.1.14:14861</td><td style=\"text-align: right;\">3.92859</td><td>low </td><td style=\"text-align: right;\"> 100</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 7.35006</td><td style=\"text-align: right;\"> 0.59322 </td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00096</td><td>TERMINATED</td><td>192.168.1.14:14872</td><td style=\"text-align: right;\">2.09419</td><td>close </td><td style=\"text-align: right;\"> 40</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 8.1103 </td><td style=\"text-align: right;\"> 0.475887</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00097</td><td>TERMINATED</td><td>192.168.1.14:15039</td><td style=\"text-align: right;\">1.54937</td><td>high </td><td style=\"text-align: right;\"> 50</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 7.58081</td><td style=\"text-align: right;\"> 0.469942</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00098</td><td>TERMINATED</td><td>192.168.1.14:15042</td><td style=\"text-align: right;\">2.0235 </td><td>high </td><td style=\"text-align: right;\"> 70</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 6.61541</td><td style=\"text-align: right;\"> 0.473904</td></tr>\n",
|
||
"<tr><td>trainable_9e7a8_00099</td><td>TERMINATED</td><td>192.168.1.14:15053</td><td style=\"text-align: right;\">2.5238 </td><td>close </td><td style=\"text-align: right;\"> 80</td><td style=\"text-align: right;\"> 1</td><td style=\"text-align: right;\"> 6.57313</td><td style=\"text-align: right;\"> 0.50361 </td></tr>\n",
|
||
"</tbody>\n",
|
||
"</table><br><br>"
|
||
],
|
||
"text/plain": [
|
||
"<IPython.core.display.HTML object>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"2022-06-01 19:36:58,602\tINFO tune.py:701 -- Total run time: 187.59 seconds (187.44 seconds for the tuning loop).\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"analysis = tune.run(trainable, config=config, num_samples=100, mode='max', metric='accuracy')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "c274a392",
|
||
"metadata": {},
|
||
"source": [
|
||
"Let's see who was the best"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 31,
|
||
"id": "b59aca0f",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": [
|
||
"{'window': 100, 'value_type': 'low', 'k_dev': 3.9285854094927943}"
|
||
]
|
||
},
|
||
"execution_count": 31,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"analysis.best_config"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Kernel for market trade lib",
|
||
"language": "python",
|
||
"name": "markettrade_kernel"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.9.12"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|