397 lines
18 KiB
Plaintext
397 lines
18 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 6,
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"outputs": [],
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"source": [
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"from collections import defaultdict\n",
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"from pathlib import Path\n",
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"from natsort import natsorted\n",
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"from pytorch_lightning.core.saving import ModelIO\n",
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"from ml_lib.utils.model_io import SavedLightningModels\n",
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"from ml_lib.utils.tools import locate_and_import_class\n",
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"\n",
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"import yaml\n",
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"\n",
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"import numpy as np\n",
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"import torch\n",
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"import pytorch_lightning as pl\n",
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"import librosa\n",
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"import pandas as pd\n",
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"import variables as v\n",
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"import seaborn as sns\n",
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"from tqdm import tqdm\n",
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"from matplotlib import pyplot as plt"
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],
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"metadata": {
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"collapsed": false,
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"pycharm": {
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"name": "#%% Imports go here\n"
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}
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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": 12,
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"outputs": [],
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"source": [
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"# Settings and Variables\n",
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"\n",
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"# This Experiment (= Model and Parameter Configuration\n",
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"_ROOT = Path('..')\n",
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"out_path = Path('..') / Path('output')\n",
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"model_name = 'VisualTransformer'\n"
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],
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"metadata": {
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"collapsed": false,
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"pycharm": {
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"name": "#%%\n"
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}
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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": 42,
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"outputs": [],
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"source": [
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"def print_stats(data_option, mean_duration, std_duration, min_duration, max_duration):\n",
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" print(f'For {data_option}; statistics are:')\n",
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" print(f'Scores - mean: {mean_duration:.3f}s\\tstd: {std_duration:.3f}s'\n",
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" f'min: {min_duration:.3f}s\\t max: {max_duration:.3f}s')\n",
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"\n",
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"def print_metrics(exp_path):\n",
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" print(f'--------------{exp_path.name}------------------')\n",
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" best_scores = []\n",
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" had_errors = []\n",
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" for run_folder in [x for x in exp_path.iterdir() if x.is_dir()]:\n",
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" # model_class = locate_and_import_class(model_name, 'models')\n",
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" # sorted_checkpoints = natsorted(run_folder.glob('*.ckpt'))\n",
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" # model = ModelIO.load_from_checkpoint(str(sorted_checkpoints[0]), strict=True)\n",
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" try:\n",
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" metrics = pd.read_csv(run_folder / 'metrics.csv')\n",
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"\n",
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" # Possible keys are:\n",
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" # -- CE - Losses:\n",
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" # val_max_vote_loss, val_mean_vote_loss, mean_val_loss\n",
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" # -- Fallback:\n",
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" # mean_loss,epoch,step,macro_f1_score, macro_roc_auc_ovr, uar_score, micro_f1_score\n",
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" # Pytorch Metrics:\n",
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" # PL_f1_score,PL_accuracy_score_score, PL_fbeta_score,PL_recall_score,PL_precision_score,\n",
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" score = metrics.PL_recall_score[-1]\n",
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" print(f'{exp_path.name} - {run_folder.name}: {score}')\n",
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" best_scores.append(score)\n",
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" had_errors.append(False)\n",
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" except (AttributeError, FileNotFoundError):\n",
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" had_errors.append(True)\n",
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" pass\n",
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" if any(had_errors):\n",
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" return\n",
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" else:\n",
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" print('\\n')\n",
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" stats = np.mean(best_scores), np.std(best_scores), np.min(best_scores), np.max(best_scores)\n",
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" print_stats(exp_path.name, *stats)\n",
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" print('--------------------------------------------')\n"
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],
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"metadata": {
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"collapsed": false,
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"pycharm": {
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"name": "#%% Util Functions\n"
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}
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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": 32,
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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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"--------------VT_259ee495ee2d2dc0e56bb23d12476f17------------------\n",
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"VT_259ee495ee2d2dc0e56bb23d12476f17 - version_1: 0.8403531908988953\n",
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"VT_259ee495ee2d2dc0e56bb23d12476f17 - version_3: 0.8312729001045227\n",
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"VT_259ee495ee2d2dc0e56bb23d12476f17 - version_0: 0.8342075347900391\n",
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"VT_259ee495ee2d2dc0e56bb23d12476f17 - version_5: 0.8459098935127258\n",
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"VT_259ee495ee2d2dc0e56bb23d12476f17 - version_2: 0.8468937277793884\n",
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"VT_259ee495ee2d2dc0e56bb23d12476f17 - version_4: 0.8404075503349304\n",
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"\n",
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"\n",
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"For VT_259ee495ee2d2dc0e56bb23d12476f17; statistics are:\n",
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"Scores - mean: 0.840s\tstd: 0.006smin: 0.831s\t max: 0.847s\n",
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"--------------------------------------------\n",
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"--------------VT_012aff7c1c667073aedafcbebfa35ec7------------------\n",
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"VT_012aff7c1c667073aedafcbebfa35ec7 - version_6: 0.8637051582336426\n",
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"VT_012aff7c1c667073aedafcbebfa35ec7 - version_1: 0.864475429058075\n",
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"VT_012aff7c1c667073aedafcbebfa35ec7 - version_3: 0.854859471321106\n",
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"VT_012aff7c1c667073aedafcbebfa35ec7 - version_0: 0.8631429672241211\n",
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"VT_012aff7c1c667073aedafcbebfa35ec7 - version_8: 0.8484407663345337\n",
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"VT_012aff7c1c667073aedafcbebfa35ec7 - version_5: 0.8564963340759277\n",
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"VT_012aff7c1c667073aedafcbebfa35ec7 - version_7: 0.8519455194473267\n",
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"VT_012aff7c1c667073aedafcbebfa35ec7 - version_2: 0.8683117032051086\n",
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"VT_012aff7c1c667073aedafcbebfa35ec7 - version_9: 0.8730489611625671\n",
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"VT_012aff7c1c667073aedafcbebfa35ec7 - version_4: 0.8658838272094727\n",
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"\n",
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"\n",
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"For VT_012aff7c1c667073aedafcbebfa35ec7; statistics are:\n",
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"Scores - mean: 0.861s\tstd: 0.007smin: 0.848s\t max: 0.873s\n",
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"--------------------------------------------\n",
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"--------------VT_fdf2a86085b508c1325b181c830a4cf7------------------\n",
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"VT_fdf2a86085b508c1325b181c830a4cf7 - version_6: 0.854997456073761\n",
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"VT_fdf2a86085b508c1325b181c830a4cf7 - version_1: 0.8609604835510254\n",
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"VT_fdf2a86085b508c1325b181c830a4cf7 - version_3: 0.8558254837989807\n",
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"VT_fdf2a86085b508c1325b181c830a4cf7 - version_0: 0.8728921413421631\n",
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"VT_fdf2a86085b508c1325b181c830a4cf7 - version_8: 0.8631933927536011\n",
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"VT_fdf2a86085b508c1325b181c830a4cf7 - version_5: 0.8612215518951416\n",
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"VT_fdf2a86085b508c1325b181c830a4cf7 - version_7: 0.8661960959434509\n",
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"VT_fdf2a86085b508c1325b181c830a4cf7 - version_2: 0.8636621832847595\n",
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"VT_fdf2a86085b508c1325b181c830a4cf7 - version_9: 0.8614727258682251\n",
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"VT_fdf2a86085b508c1325b181c830a4cf7 - version_4: 0.8657329082489014\n",
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"\n",
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"\n",
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"For VT_fdf2a86085b508c1325b181c830a4cf7; statistics are:\n",
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"Scores - mean: 0.863s\tstd: 0.005smin: 0.855s\t max: 0.873s\n",
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"--------------------------------------------\n",
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"--------------VT_cc64c06847a7ca26f5ea4d465f9cc5bc------------------\n",
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"VT_cc64c06847a7ca26f5ea4d465f9cc5bc - version_6: 0.8572231531143188\n",
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"VT_cc64c06847a7ca26f5ea4d465f9cc5bc - version_1: 0.8442623615264893\n",
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"VT_cc64c06847a7ca26f5ea4d465f9cc5bc - version_3: 0.8498414754867554\n",
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"VT_cc64c06847a7ca26f5ea4d465f9cc5bc - version_0: 0.8569087982177734\n",
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"VT_cc64c06847a7ca26f5ea4d465f9cc5bc - version_8: 0.8455194234848022\n",
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"VT_cc64c06847a7ca26f5ea4d465f9cc5bc - version_5: 0.8435630798339844\n",
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"VT_cc64c06847a7ca26f5ea4d465f9cc5bc - version_7: 0.845982551574707\n",
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"VT_cc64c06847a7ca26f5ea4d465f9cc5bc - version_2: 0.8571171164512634\n",
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"VT_cc64c06847a7ca26f5ea4d465f9cc5bc - version_9: 0.8448543548583984\n",
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"VT_cc64c06847a7ca26f5ea4d465f9cc5bc - version_4: 0.845399022102356\n",
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"\n",
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"\n",
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"For VT_cc64c06847a7ca26f5ea4d465f9cc5bc; statistics are:\n",
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"Scores - mean: 0.849s\tstd: 0.005smin: 0.844s\t max: 0.857s\n",
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"--------------------------------------------\n",
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"--------------VT_2c7afd50e127f5a2339db0ddfd6bfd7c------------------\n",
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"VT_2c7afd50e127f5a2339db0ddfd6bfd7c - version_6: 0.8630585670471191\n",
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"VT_2c7afd50e127f5a2339db0ddfd6bfd7c - version_1: 0.8686699271202087\n",
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"VT_2c7afd50e127f5a2339db0ddfd6bfd7c - version_3: 0.8729345798492432\n",
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"VT_2c7afd50e127f5a2339db0ddfd6bfd7c - version_0: 0.8636038899421692\n",
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"VT_2c7afd50e127f5a2339db0ddfd6bfd7c - version_8: 0.8558077812194824\n",
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"VT_2c7afd50e127f5a2339db0ddfd6bfd7c - version_5: 0.8710847496986389\n",
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"VT_2c7afd50e127f5a2339db0ddfd6bfd7c - version_7: 0.8619015216827393\n",
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"VT_2c7afd50e127f5a2339db0ddfd6bfd7c - version_2: 0.8499867916107178\n",
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"VT_2c7afd50e127f5a2339db0ddfd6bfd7c - version_9: 0.8507344722747803\n",
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"VT_2c7afd50e127f5a2339db0ddfd6bfd7c - version_4: 0.8555077314376831\n",
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"\n",
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"\n",
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"For VT_2c7afd50e127f5a2339db0ddfd6bfd7c; statistics are:\n",
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"Scores - mean: 0.861s\tstd: 0.008smin: 0.850s\t max: 0.873s\n",
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"--------------------------------------------\n",
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"--------------VT_63b9fee765cdda91756af1f35cd320a3------------------\n",
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"VT_63b9fee765cdda91756af1f35cd320a3 - version_6: 0.8663593530654907\n",
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"VT_63b9fee765cdda91756af1f35cd320a3 - version_1: 0.8519773483276367\n",
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"VT_63b9fee765cdda91756af1f35cd320a3 - version_3: 0.8519774675369263\n",
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"VT_63b9fee765cdda91756af1f35cd320a3 - version_0: 0.8603388071060181\n",
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"VT_63b9fee765cdda91756af1f35cd320a3 - version_8: 0.8614517450332642\n",
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"VT_63b9fee765cdda91756af1f35cd320a3 - version_5: 0.8558711409568787\n",
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"VT_63b9fee765cdda91756af1f35cd320a3 - version_7: 0.8537712097167969\n",
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"VT_63b9fee765cdda91756af1f35cd320a3 - version_2: 0.8558205962181091\n",
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"VT_63b9fee765cdda91756af1f35cd320a3 - version_9: 0.8647329211235046\n",
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"VT_63b9fee765cdda91756af1f35cd320a3 - version_4: 0.8546129465103149\n",
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"\n",
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"\n",
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"For VT_63b9fee765cdda91756af1f35cd320a3; statistics are:\n",
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"Scores - mean: 0.858s\tstd: 0.005smin: 0.852s\t max: 0.866s\n",
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"--------------------------------------------\n",
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"--------------VT_aca900a5b9566af61c91aea6525190e6------------------\n",
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"VT_aca900a5b9566af61c91aea6525190e6 - version_6: 0.8575441241264343\n",
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"VT_aca900a5b9566af61c91aea6525190e6 - version_1: 0.8453981280326843\n",
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"VT_aca900a5b9566af61c91aea6525190e6 - version_3: 0.8621359467506409\n",
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"VT_aca900a5b9566af61c91aea6525190e6 - version_0: 0.8547767400741577\n",
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"VT_aca900a5b9566af61c91aea6525190e6 - version_8: 0.8613359928131104\n",
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"VT_aca900a5b9566af61c91aea6525190e6 - version_5: 0.8667657375335693\n",
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"VT_aca900a5b9566af61c91aea6525190e6 - version_7: 0.8474754095077515\n",
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"VT_aca900a5b9566af61c91aea6525190e6 - version_2: 0.8628634214401245\n",
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"VT_aca900a5b9566af61c91aea6525190e6 - version_9: 0.8585749268531799\n",
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"VT_aca900a5b9566af61c91aea6525190e6 - version_4: 0.8380126357078552\n",
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"\n",
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"\n",
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"For VT_aca900a5b9566af61c91aea6525190e6; statistics are:\n",
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"Scores - mean: 0.855s\tstd: 0.009smin: 0.838s\t max: 0.867s\n",
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"--------------------------------------------\n",
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"--------------VT_fb6b96a190455106d29f0630f002ac6f------------------\n",
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"VT_fb6b96a190455106d29f0630f002ac6f - version_6: 0.8635155558586121\n",
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"VT_fb6b96a190455106d29f0630f002ac6f - version_1: 0.8261691927909851\n",
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"VT_fb6b96a190455106d29f0630f002ac6f - version_3: 0.8444902896881104\n",
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"VT_fb6b96a190455106d29f0630f002ac6f - version_0: 0.865719735622406\n",
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"VT_fb6b96a190455106d29f0630f002ac6f - version_8: 0.8533784747123718\n",
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"VT_fb6b96a190455106d29f0630f002ac6f - version_5: 0.8555656671524048\n",
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"VT_fb6b96a190455106d29f0630f002ac6f - version_7: 0.837948739528656\n",
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"VT_fb6b96a190455106d29f0630f002ac6f - version_2: 0.8545827865600586\n",
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"VT_fb6b96a190455106d29f0630f002ac6f - version_9: 0.8541560769081116\n",
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"VT_fb6b96a190455106d29f0630f002ac6f - version_4: 0.85297691822052\n",
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"\n",
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"\n",
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"For VT_fb6b96a190455106d29f0630f002ac6f; statistics are:\n",
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"Scores - mean: 0.851s\tstd: 0.011smin: 0.826s\t max: 0.866s\n",
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"--------------------------------------------\n",
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"--------------VT_378971720b930050ad7662bb96699e20------------------\n",
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"VT_378971720b930050ad7662bb96699e20 - version_6: 0.8388294577598572\n",
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"VT_378971720b930050ad7662bb96699e20 - version_1: 0.8333806395530701\n",
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"VT_378971720b930050ad7662bb96699e20 - version_3: 0.847841203212738\n",
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"VT_378971720b930050ad7662bb96699e20 - version_0: 0.8287097811698914\n",
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"VT_378971720b930050ad7662bb96699e20 - version_8: 0.8436978459358215\n",
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"VT_378971720b930050ad7662bb96699e20 - version_5: 0.8392724990844727\n",
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"VT_378971720b930050ad7662bb96699e20 - version_7: 0.8410612344741821\n",
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"VT_378971720b930050ad7662bb96699e20 - version_2: 0.8407015204429626\n",
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"VT_378971720b930050ad7662bb96699e20 - version_9: 0.8334627151489258\n",
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"VT_378971720b930050ad7662bb96699e20 - version_4: 0.8400266766548157\n",
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"\n",
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"\n",
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"For VT_378971720b930050ad7662bb96699e20; statistics are:\n",
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"Scores - mean: 0.839s\tstd: 0.005smin: 0.829s\t max: 0.848s\n",
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"--------------------------------------------\n",
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"--------------VT_d55f1492ff29a3cd1026013948ce7fa7------------------\n",
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"VT_d55f1492ff29a3cd1026013948ce7fa7 - version_6: 0.8385945558547974\n",
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"VT_d55f1492ff29a3cd1026013948ce7fa7 - version_1: 0.8324360251426697\n",
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"VT_d55f1492ff29a3cd1026013948ce7fa7 - version_3: 0.8386826515197754\n",
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"VT_d55f1492ff29a3cd1026013948ce7fa7 - version_0: 0.8366813063621521\n",
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"VT_d55f1492ff29a3cd1026013948ce7fa7 - version_8: 0.8460721969604492\n",
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"VT_d55f1492ff29a3cd1026013948ce7fa7 - version_5: 0.8374781608581543\n",
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"VT_d55f1492ff29a3cd1026013948ce7fa7 - version_7: 0.8320286273956299\n",
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"VT_d55f1492ff29a3cd1026013948ce7fa7 - version_2: 0.8370164632797241\n",
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"VT_d55f1492ff29a3cd1026013948ce7fa7 - version_9: 0.8495808839797974\n",
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"VT_d55f1492ff29a3cd1026013948ce7fa7 - version_4: 0.8332125544548035\n",
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"\n",
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"\n",
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"For VT_d55f1492ff29a3cd1026013948ce7fa7; statistics are:\n",
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"Scores - mean: 0.838s\tstd: 0.005smin: 0.832s\t max: 0.850s\n",
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"--------------------------------------------\n",
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"--------------VT_15cbb349b2b50dbb97beec16af2bedab------------------\n",
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"VT_15cbb349b2b50dbb97beec16af2bedab - version_6: 0.8407894372940063\n",
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"VT_15cbb349b2b50dbb97beec16af2bedab - version_1: 0.836580216884613\n",
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"VT_15cbb349b2b50dbb97beec16af2bedab - version_3: 0.8312996029853821\n",
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"VT_15cbb349b2b50dbb97beec16af2bedab - version_0: 0.8336991667747498\n",
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"VT_15cbb349b2b50dbb97beec16af2bedab - version_8: 0.8231534957885742\n",
|
|
"VT_15cbb349b2b50dbb97beec16af2bedab - version_5: 0.8243923187255859\n",
|
|
"VT_15cbb349b2b50dbb97beec16af2bedab - version_7: 0.8342592120170593\n",
|
|
"VT_15cbb349b2b50dbb97beec16af2bedab - version_2: 0.8349334001541138\n",
|
|
"VT_15cbb349b2b50dbb97beec16af2bedab - version_9: 0.8382810950279236\n",
|
|
"VT_15cbb349b2b50dbb97beec16af2bedab - version_4: 0.8381868600845337\n",
|
|
"\n",
|
|
"\n",
|
|
"For VT_15cbb349b2b50dbb97beec16af2bedab; statistics are:\n",
|
|
"Scores - mean: 0.834s\tstd: 0.006smin: 0.823s\t max: 0.841s\n",
|
|
"--------------------------------------------\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"for model_configuration in [x for x in (out_path / model_name).iterdir() if x.is_dir()]:\n",
|
|
" # Print metrics\n",
|
|
" print_metrics(model_configuration)"
|
|
],
|
|
"metadata": {
|
|
"collapsed": false,
|
|
"pycharm": {
|
|
"name": "#%% Mass - Load Model and read Metrics\n"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 15,
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"--------------VT_fdf2a86085b508c1325b181c830a4cf7------------------\n",
|
|
"--------------VT_fdf2a86085b508c1325b181c830a4cf7------------------\n",
|
|
"VT_fdf2a86085b508c1325b181c830a4cf7 - version_6: 0.854997456073761\n",
|
|
"VT_fdf2a86085b508c1325b181c830a4cf7 - version_1: 0.8609604835510254\n",
|
|
"VT_fdf2a86085b508c1325b181c830a4cf7 - version_3: 0.8558254837989807\n",
|
|
"VT_fdf2a86085b508c1325b181c830a4cf7 - version_0: 0.8728921413421631\n",
|
|
"VT_fdf2a86085b508c1325b181c830a4cf7 - version_8: 0.8631933927536011\n",
|
|
"VT_fdf2a86085b508c1325b181c830a4cf7 - version_5: 0.8612215518951416\n",
|
|
"VT_fdf2a86085b508c1325b181c830a4cf7 - version_7: 0.8661960959434509\n",
|
|
"VT_fdf2a86085b508c1325b181c830a4cf7 - version_2: 0.8636621832847595\n",
|
|
"VT_fdf2a86085b508c1325b181c830a4cf7 - version_9: 0.8614727258682251\n",
|
|
"VT_fdf2a86085b508c1325b181c830a4cf7 - version_4: 0.8657329082489014\n",
|
|
"--------------------------------------------\n",
|
|
"--------------------------------------------\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"# fingerprint = '012aff7c1c667073aedafcbebfa35ec7'\n",
|
|
"fingerprint = 'fdf2a86085b508c1325b181c830a4cf7'\n",
|
|
"exp_name = f'{\"\".join([x for x in model_name if x.isupper()])}_{fingerprint}'\n",
|
|
"\n",
|
|
"# Print metrics\n",
|
|
"print_metrics(out_path/model_name/exp_name)\n",
|
|
"\n"
|
|
],
|
|
"metadata": {
|
|
"collapsed": false,
|
|
"pycharm": {
|
|
"name": "#%% Single - Load Model and read Metrics\n"
|
|
}
|
|
}
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 39,
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
" filenames prediction prediction_named\n",
|
|
"0 test_00001 1 chimpanze\n",
|
|
"1 test_00002 0 background\n",
|
|
"2 test_00003 0 background\n",
|
|
"3 test_00004 1 chimpanze\n",
|
|
"4 test_00005 4 redcap\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"predictions_file = out_path/model_name/'VT_15cbb349b2b50dbb97beec16af2bedab'/'version_9'/'predictions.csv'\n",
|
|
"df_predictions = pd.read_csv(predictions_file)\n",
|
|
"print(df_predictions.head())\n",
|
|
"df_predictions = df_predictions[['filenames', 'prediction_named']]\n",
|
|
"df_predictions.columns = ['filename', 'prediction']\n",
|
|
"df_predictions['filename'] = df_predictions['filename'] + '.wav'\n",
|
|
"predictions_file_new = predictions_file.parent / 'prediction_final.csv'\n",
|
|
"df_predictions.to_csv(index=False, path_or_buf=predictions_file_new)\n",
|
|
"\n",
|
|
"\n"
|
|
],
|
|
"metadata": {
|
|
"collapsed": false,
|
|
"pycharm": {
|
|
"name": "#%% Combine Predictions#\n"
|
|
}
|
|
}
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 2
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython2",
|
|
"version": "2.7.6"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 0
|
|
} |