Add visualize dropout
This commit is contained in:
parent
0e2dd13762
commit
5f2ba0a8e7
@ -18,10 +18,10 @@
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[61765:MainThread](2021-04-11 21:23:06,638) INFO - qlib.Initialization - [config.py:276] - default_conf: client.\n",
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"[61765:MainThread](2021-04-11 21:23:06,641) WARNING - qlib.Initialization - [config.py:291] - redis connection failed(host=127.0.0.1 port=6379), cache will not be used!\n",
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"[61765:MainThread](2021-04-11 21:23:06,643) INFO - qlib.Initialization - [__init__.py:46] - qlib successfully initialized based on client settings.\n",
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"[61765:MainThread](2021-04-11 21:23:06,644) INFO - qlib.Initialization - [__init__.py:47] - data_path=/Users/xuanyidong/.qlib/qlib_data/cn_data\n"
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"[68147:MainThread](2021-04-12 13:09:24,409) INFO - qlib.Initialization - [config.py:276] - default_conf: client.\n",
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"[68147:MainThread](2021-04-12 13:09:24,411) WARNING - qlib.Initialization - [config.py:291] - redis connection failed(host=127.0.0.1 port=6379), cache will not be used!\n",
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"[68147:MainThread](2021-04-12 13:09:24,414) INFO - qlib.Initialization - [__init__.py:46] - qlib successfully initialized based on client settings.\n",
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"[68147:MainThread](2021-04-12 13:09:24,417) INFO - qlib.Initialization - [__init__.py:47] - data_path=/Users/xuanyidong/.qlib/qlib_data/cn_data\n"
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]
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}
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],
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@ -142,7 +142,7 @@
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[61765:MainThread](2021-04-11 21:23:07,182) INFO - qlib.workflow - [expm.py:290] - <mlflow.tracking.client.MlflowClient object at 0x7fabbfe8aeb0>\n"
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"[68147:MainThread](2021-04-12 13:09:25,066) INFO - qlib.workflow - [expm.py:290] - <mlflow.tracking.client.MlflowClient object at 0x7fd449277a30>\n"
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]
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},
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{
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@ -181,7 +181,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 40,
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"execution_count": 6,
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"id": "supreme-basis",
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"metadata": {},
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"outputs": [],
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@ -207,9 +207,9 @@
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" depths.append(float(name.split('x')[0]))\n",
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" channels.append(float(name.split('x')[1]))\n",
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" if train_or_test:\n",
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" ic_values.append(qresult['ICIR (train)'] * 100)\n",
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" ic_values.append(qresult['IC (train)'])\n",
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" else:\n",
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" ic_values.append(qresult['ICIR (valid)'] * 100)\n",
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" ic_values.append(qresult['IC (valid)'])\n",
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" xmaps[(depths[-1], channels[-1])] = ic_values[-1]\n",
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" # cur_ax.scatter(depths, channels, ic_values, marker='o', c=\"tab:orange\")\n",
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" raw_depths = np.arange(1, 9, dtype=np.int32)\n",
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@ -263,7 +263,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 41,
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"execution_count": 7,
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"id": "shared-envelope",
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"metadata": {},
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"outputs": [
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311
notebooks/TOT/ES-Model-Drop.ipynb
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311
notebooks/TOT/ES-Model-Drop.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "afraid-minutes",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The root path: /Users/xuanyidong/Desktop/AutoDL-Projects\n",
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"The library path: /Users/xuanyidong/Desktop/AutoDL-Projects/lib\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[64660:MainThread](2021-04-11 23:57:38,079) INFO - qlib.Initialization - [config.py:276] - default_conf: client.\n",
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"[64660:MainThread](2021-04-11 23:57:38,081) WARNING - qlib.Initialization - [config.py:291] - redis connection failed(host=127.0.0.1 port=6379), cache will not be used!\n",
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"[64660:MainThread](2021-04-11 23:57:38,083) INFO - qlib.Initialization - [__init__.py:46] - qlib successfully initialized based on client settings.\n",
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"[64660:MainThread](2021-04-11 23:57:38,084) INFO - qlib.Initialization - [__init__.py:47] - data_path=/Users/xuanyidong/.qlib/qlib_data/cn_data\n"
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]
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}
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],
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"source": [
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"#\n",
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"# Exhaustive Search Results\n",
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"#\n",
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"import os\n",
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"import re\n",
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"import sys\n",
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"import qlib\n",
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"import pprint\n",
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"import numpy as np\n",
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"import pandas as pd\n",
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"\n",
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"from pathlib import Path\n",
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"\n",
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"__file__ = os.path.dirname(os.path.realpath(\"__file__\"))\n",
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"root_dir = (Path(__file__).parent / \"..\").resolve()\n",
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"lib_dir = (root_dir / \"lib\").resolve()\n",
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"print(\"The root path: {:}\".format(root_dir))\n",
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"print(\"The library path: {:}\".format(lib_dir))\n",
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"assert lib_dir.exists(), \"{:} does not exist\".format(lib_dir)\n",
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"if str(lib_dir) not in sys.path:\n",
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" sys.path.insert(0, str(lib_dir))\n",
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"\n",
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"import qlib\n",
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"from qlib import config as qconfig\n",
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"from qlib.workflow import R\n",
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"qlib.init(provider_uri='~/.qlib/qlib_data/cn_data', region=qconfig.REG_CN)"
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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": 2,
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"id": "hidden-exemption",
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"metadata": {},
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"outputs": [],
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"source": [
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"from utils.qlib_utils import QResult"
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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": 3,
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"id": "continental-drain",
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"metadata": {},
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"outputs": [],
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"source": [
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"def filter_finished(recorders):\n",
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" returned_recorders = dict()\n",
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" not_finished = 0\n",
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" for key, recorder in recorders.items():\n",
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" if recorder.status == \"FINISHED\":\n",
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" returned_recorders[key] = recorder\n",
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" else:\n",
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" not_finished += 1\n",
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" return returned_recorders, not_finished\n",
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"\n",
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"def query_info(save_dir, verbose, name_filter, key_map):\n",
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" if isinstance(save_dir, list):\n",
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" results = []\n",
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" for x in save_dir:\n",
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" x = query_info(x, verbose, name_filter, key_map)\n",
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" results.extend(x)\n",
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" return results\n",
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" # Here, the save_dir must be a string\n",
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" R.set_uri(str(save_dir))\n",
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" experiments = R.list_experiments()\n",
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"\n",
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" if verbose:\n",
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" print(\"There are {:} experiments.\".format(len(experiments)))\n",
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" qresults = []\n",
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" for idx, (key, experiment) in enumerate(experiments.items()):\n",
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" if experiment.id == \"0\":\n",
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" continue\n",
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" if name_filter is not None and re.fullmatch(name_filter, experiment.name) is None:\n",
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" continue\n",
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" recorders = experiment.list_recorders()\n",
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" recorders, not_finished = filter_finished(recorders)\n",
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" if verbose:\n",
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" print(\n",
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" \"====>>>> {:02d}/{:02d}-th experiment {:9s} has {:02d}/{:02d} finished recorders.\".format(\n",
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" idx + 1,\n",
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" len(experiments),\n",
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" experiment.name,\n",
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" len(recorders),\n",
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" len(recorders) + not_finished,\n",
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" )\n",
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" )\n",
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" result = QResult(experiment.name)\n",
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" for recorder_id, recorder in recorders.items():\n",
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" result.update(recorder.list_metrics(), key_map)\n",
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" result.append_path(\n",
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" os.path.join(recorder.uri, recorder.experiment_id, recorder.id)\n",
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" )\n",
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" if not len(result):\n",
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" print(\"There are no valid recorders for {:}\".format(experiment))\n",
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" continue\n",
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" else:\n",
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" if verbose:\n",
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" print(\n",
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" \"There are {:} valid recorders for {:}\".format(\n",
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" len(recorders), experiment.name\n",
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" )\n",
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" )\n",
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" qresults.append(result)\n",
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" return qresults"
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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": 4,
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"id": "filled-multiple",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[64660:MainThread](2021-04-11 23:57:38,469) INFO - qlib.workflow - [expm.py:290] - <mlflow.tracking.client.MlflowClient object at 0x7fba2bc7df70>\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[PosixPath('/Users/xuanyidong/Desktop/AutoDL-Projects/outputs/qlib-baselines-csi300')]\n"
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]
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}
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],
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"source": [
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"paths = [root_dir / 'outputs' / 'qlib-baselines-csi300']\n",
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"paths = [path.resolve() for path in paths]\n",
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"print(paths)\n",
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"\n",
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"key_map = dict()\n",
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"for xset in (\"train\", \"valid\", \"test\"):\n",
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" key_map[\"{:}-mean-IC\".format(xset)] = \"IC ({:})\".format(xset)\n",
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" key_map[\"{:}-mean-ICIR\".format(xset)] = \"ICIR ({:})\".format(xset)\n",
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"\n",
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"qresults = query_info(paths, False, 'TSF-.*', key_map)"
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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": 5,
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"id": "intimate-approval",
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"metadata": {},
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"outputs": [],
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"source": [
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"import matplotlib\n",
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"from matplotlib import cm\n",
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"matplotlib.use(\"agg\")\n",
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"import matplotlib.pyplot as plt\n",
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"import matplotlib.ticker as ticker"
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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": 27,
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"id": "supreme-basis",
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"metadata": {},
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"outputs": [],
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"source": [
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"def vis_dropouts(qresults, basenames, name2suffix, save_path):\n",
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" save_dir = (save_path / '..').resolve()\n",
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" save_dir.mkdir(parents=True, exist_ok=True)\n",
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" print('There are {:} qlib-results'.format(len(qresults)))\n",
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" \n",
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" name2qresult = dict()\n",
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" for qresult in qresults:\n",
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" name2qresult[qresult.name] = qresult\n",
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" # sort architectures\n",
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" accuracies = []\n",
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" for basename in basenames:\n",
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" qresult = name2qresult[basename + '-drop0_0']\n",
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" accuracies.append(qresult['ICIR (train)'])\n",
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" sorted_basenames = sorted(basenames, key=lambda x: accuracies[basenames.index(x)])\n",
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" \n",
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" dpi, width, height = 200, 4000, 2000\n",
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" figsize = width / float(dpi), height / float(dpi)\n",
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" LabelSize, LegendFontsize = 22, 18\n",
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" font_gap = 5\n",
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" colors = ['k', 'r']\n",
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" markers = ['*', 'o']\n",
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" \n",
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" fig = plt.figure(figsize=figsize)\n",
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" \n",
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" def plot_ax(cur_ax, train_or_test):\n",
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" for idx, (legend, suffix) in enumerate(name2suffix.items()):\n",
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" x_values = list(range(len(sorted_basenames)))\n",
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" y_values = []\n",
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" for i, name in enumerate(sorted_basenames):\n",
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" name = '{:}{:}'.format(name, suffix)\n",
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" qresult = name2qresult[name]\n",
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" if train_or_test:\n",
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" value = qresult['IC (train)']\n",
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" else:\n",
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" value = qresult['IC (valid)']\n",
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" y_values.append(value)\n",
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" cur_ax.plot(x_values, y_values, c=colors[idx])\n",
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" cur_ax.scatter(x_values, y_values,\n",
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" marker=markers[idx], s=3, c=colors[idx], alpha=0.9,\n",
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" label=legend)\n",
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" cur_ax.set_xlabel(\"sorted architectures\", fontsize=LabelSize)\n",
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" cur_ax.set_ylabel(\"{:} IC (%)\".format('training' if train_or_test else 'validation'), fontsize=LabelSize)\n",
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" for tick in cur_ax.xaxis.get_major_ticks():\n",
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" tick.label.set_fontsize(LabelSize - font_gap)\n",
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" for tick in cur_ax.yaxis.get_major_ticks():\n",
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" tick.label.set_fontsize(LabelSize - font_gap)\n",
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" cur_ax.legend(loc=4, fontsize=LegendFontsize)\n",
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" ax = fig.add_subplot(1, 2, 1)\n",
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" plot_ax(ax, True)\n",
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" ax = fig.add_subplot(1, 2, 2)\n",
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" plot_ax(ax, False)\n",
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" # fig.tight_layout()\n",
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" # plt.subplots_adjust(wspace=0.05)#, hspace=0.4)\n",
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" fig.savefig(save_path, dpi=dpi, bbox_inches=\"tight\", format=\"pdf\")\n",
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" plt.close(\"all\")"
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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": 28,
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"id": "shared-envelope",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"{'TSF-8x6', 'TSF-6x6', 'TSF-4x24', 'TSF-3x32', 'TSF-7x6', 'TSF-4x12', 'TSF-2x12', 'TSF-1x24', 'TSF-1x32', 'TSF-6x32', 'TSF-7x48', 'TSF-4x6', 'TSF-5x32', 'TSF-6x24', 'TSF-8x24', 'TSF-5x6', 'TSF-3x24', 'TSF-6x12', 'TSF-3x12', 'TSF-5x64', 'TSF-5x12', 'TSF-7x32', 'TSF-6x48', 'TSF-3x64', 'TSF-5x48', 'TSF-7x24', 'TSF-4x32', 'TSF-4x64', 'TSF-2x64', 'TSF-8x12', 'TSF-7x64', 'TSF-3x6', 'TSF-1x6', 'TSF-8x64', 'TSF-2x6', 'TSF-6x64', 'TSF-7x12', 'TSF-2x24', 'TSF-8x48', 'TSF-1x64', 'TSF-4x48', 'TSF-8x32', 'TSF-2x48', 'TSF-1x12', 'TSF-5x24', 'TSF-3x48', 'TSF-2x32', 'TSF-1x48'}\n",
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"The Desktop is at: /Users/xuanyidong/Desktop\n",
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"There are 104 qlib-results\n"
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]
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}
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],
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"source": [
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"# Visualization\n",
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"names = [qresult.name for qresult in qresults]\n",
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"base_names = set()\n",
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"for name in names:\n",
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" base_name = name.split('-drop')[0]\n",
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" base_names.add(base_name)\n",
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"print(base_names)\n",
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"# filter\n",
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"filtered_base_names = set()\n",
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"for base_name in base_names:\n",
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" if (base_name + '-drop0_0') in names and (base_name + '-drop0.1_0') in names:\n",
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" filtered_base_names.add(base_name)\n",
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" else:\n",
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" print('Cannot find all names for {:}'.format(base_name))\n",
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"# print(filtered_base_names)\n",
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"home_dir = Path.home()\n",
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"desktop_dir = home_dir / 'Desktop'\n",
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"print('The Desktop is at: {:}'.format(desktop_dir))\n",
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"\n",
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"vis_dropouts(qresults, list(filtered_base_names),\n",
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" {'No-dropout': '-drop0_0',\n",
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" 'Ratio=0.1' : '-drop0.1_0'},\n",
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" desktop_dir / 'es_csi300_drop.pdf')"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.8"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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Loading…
Reference in New Issue
Block a user