diff --git a/.gitignore b/.gitignore
index f2ae1102ba8b2bf060abea69901ef2a583f271d6..e76966fae0e2663403c0546db4a4b616ace52d0b 100755
--- a/.gitignore
+++ b/.gitignore
@@ -5,7 +5,6 @@ __pycache__
*==*==.ipynb
stderr.txt
stdout.txt
-fidle/log/finished.json
run/
figs/
data/
diff --git a/GTSRB/00-Test.ipynb b/GTSRB/00-Test.ipynb
deleted file mode 100644
index 89bf5775b89e16754a8c43896feac8d652412bbe..0000000000000000000000000000000000000000
--- a/GTSRB/00-Test.ipynb
+++ /dev/null
@@ -1,233 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# TEST"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- "<style>\n",
- "\n",
- "div.warn { \n",
- " background-color: #fcf2f2;\n",
- " border-color: #dFb5b4;\n",
- " border-left: 5px solid #dfb5b4;\n",
- " padding: 0.5em;\n",
- " font-weight: bold;\n",
- " font-size: 1.1em;;\n",
- " }\n",
- "\n",
- "\n",
- "\n",
- "div.nota { \n",
- " background-color: #DAFFDE;\n",
- " border-left: 5px solid #92CC99;\n",
- " padding: 0.5em;\n",
- " }\n",
- "\n",
- "div.todo:before { content:url(data:image/svg+xml;base64,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);\n",
- " float:left;\n",
- " margin-right:20px;\n",
- " margin-top:-20px;\n",
- " margin-bottom:20px;\n",
- "}\n",
- "div.todo{\n",
- " font-weight: bold;\n",
- " font-size: 1.1em;\n",
- " margin-top:40px;\n",
- "}\n",
- "div.todo ul{\n",
- " margin: 0.2em;\n",
- "}\n",
- "div.todo li{\n",
- " margin-left:60px;\n",
- " margin-top:0;\n",
- " margin-bottom:0;\n",
- "}\n",
- "\n",
- "div .comment{\n",
- " font-size:0.8em;\n",
- " color:#696969;\n",
- "}\n",
- "\n",
- "\n",
- "\n",
- "</style>\n",
- "\n"
- ],
- "text/plain": [
- "<IPython.core.display.HTML object>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "data": {
- "text/markdown": [
- "<br>**FIDLE 2020 - Practical Work Module**"
- ],
- "text/plain": [
- "<IPython.core.display.Markdown object>"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Version : 1.2b1 DEV\n",
- "Notebook id : GTSRB0\n",
- "Run time : Saturday 9 January 2021, 18:01:32\n",
- "TensorFlow version : 2.2.0\n",
- "Keras version : 2.3.0-tf\n",
- "Datasets dir : /home/pjluc/datasets/fidle\n",
- "Run dir : ./run/GTSRB0\n",
- "Update keras cache : False\n",
- "Save figs : True\n",
- "Path figs : ./run/GTSRB0/figs\n"
- ]
- }
- ],
- "source": [
- "import os, time, sys\n",
- "import csv\n",
- "import math, random\n",
- "\n",
- "import numpy as np\n",
- "import pandas as pd\n",
- "import matplotlib.pyplot as plt\n",
- "import h5py\n",
- "\n",
- "from skimage.morphology import disk\n",
- "from skimage.util import img_as_ubyte\n",
- "from skimage.filters import rank\n",
- "from skimage import io, color, exposure, transform\n",
- "\n",
- "from importlib import reload\n",
- "\n",
- "sys.path.append('..')\n",
- "import fidle.pwk as pwk\n",
- "\n",
- "run_dir='./run/GTSRB0'\n",
- "datasets_dir = pwk.init('GTSRB0', run_dir)"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Step 2 - Parameters"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [],
- "source": [
- "# ---- For smart tests :\n",
- "#\n",
- "scale = 1\n",
- "output_dir = './data' \n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Override parameters (batch mode) - Just forget this cell"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [],
- "source": [
- "pwk.override('scale', 'output_dir')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "scale : 1\n",
- "output_dir : ./data\n",
- "run_dir : ./run/GTSRB0\n"
- ]
- }
- ],
- "source": [
- "print('scale : ', scale)\n",
- "print('output_dir : ', output_dir)\n",
- "print('run_dir : ', run_dir)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "'/home/pjluc/dev/fidle/GTSRB'"
- ]
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "import os\n",
- "os.getcwd()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.7.9"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/LinearReg/01-Linear-Regression.ipynb b/LinearReg/01-Linear-Regression.ipynb
index 7229a69334565407ae157efc0bc0d0166b6e85b5..d47cb0a34d401fd31208bfdb7f4a7e4cd432f0f3 100644
--- a/LinearReg/01-Linear-Regression.ipynb
+++ b/LinearReg/01-Linear-Regression.ipynb
@@ -94,7 +94,7 @@
{
"data": {
"text/markdown": [
- "**FIDLE 2020 - Practical Work Module**"
+ "<br>**FIDLE 2020 - Practical Work Module**"
],
"text/plain": [
"<IPython.core.display.Markdown object>"
@@ -107,13 +107,13 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Version : 0.6.1 DEV\n",
+ "Version : 1.2b1 DEV\n",
"Notebook id : LINR1\n",
- "Run time : Thursday 17 December 2020, 16:30:24\n",
- "TensorFlow version : 2.1.0\n",
- "Keras version : 2.2.4-tf\n",
- "Datasets dir : /gpfswork/rech/mlh/uja62cb/datasets\n",
- "Running mode : full\n",
+ "Run time : Sunday 10 January 2021, 21:51:29\n",
+ "TensorFlow version : 2.2.0\n",
+ "Keras version : 2.3.0-tf\n",
+ "Datasets dir : /home/pjluc/datasets/fidle\n",
+ "Run dir : ./run\n",
"Update keras cache : False\n"
]
}
@@ -185,7 +185,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/plain": [
"<Figure size 864x432 with 1 Axes>"
]
@@ -241,8 +241,8 @@
" [2]] \n",
"\n",
"theta hat :\n",
- " [[6.57350113]\n",
- " [1.53229674]]\n"
+ " [[3.60312881]\n",
+ " [1.99988269]]\n"
]
}
],
@@ -266,7 +266,7 @@
"outputs": [
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/plain": [
"<Figure size 864x432 with 1 Axes>"
]
@@ -299,8 +299,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "End time is : Thursday 17 December 2020, 16:30:38\n",
- "Duration is : 00:00:13 289ms\n",
+ "End time is : Sunday 10 January 2021, 21:51:29\n",
+ "Duration is : 00:00:00 308ms\n",
"This notebook ends here\n"
]
}
diff --git a/README.ipynb b/README.ipynb
index 1edfa1efcfe55cb58b6da6d7bf4889a00314a927..dd5f7df5af6a23452a9bb4ab7c2460e0b6845d5c 100644
--- a/README.ipynb
+++ b/README.ipynb
@@ -5,10 +5,10 @@
"execution_count": 1,
"metadata": {
"execution": {
- "iopub.execute_input": "2021-01-09T18:32:21.410112Z",
- "iopub.status.busy": "2021-01-09T18:32:21.409590Z",
- "iopub.status.idle": "2021-01-09T18:32:21.417639Z",
- "shell.execute_reply": "2021-01-09T18:32:21.417225Z"
+ "iopub.execute_input": "2021-01-10T20:53:42.241597Z",
+ "iopub.status.busy": "2021-01-10T20:53:42.241103Z",
+ "iopub.status.idle": "2021-01-10T20:53:42.245307Z",
+ "shell.execute_reply": "2021-01-10T20:53:42.244901Z"
},
"jupyter": {
"source_hidden": true
@@ -85,8 +85,6 @@
"An example of classification using a dense neural network for the famous MNIST dataset\n",
"\n",
"### Images classification with Convolutional Neural Networks (CNN)\n",
- "- **[??](GTSRB/00-Test.ipynb)** - [??](GTSRB/00-Test.ipynb) \n",
- "??\n",
"- **[GTSRB1](GTSRB/01-Preparation-of-data.ipynb)** - [Dataset analysis and preparation](GTSRB/01-Preparation-of-data.ipynb) \n",
"Episode 1 : Analysis of the GTSRB dataset and creation of an enhanced dataset\n",
"- **[GTSRB2](GTSRB/02-First-convolutions.ipynb)** - [First convolutions](GTSRB/02-First-convolutions.ipynb) \n",
diff --git a/README.md b/README.md
index 95fce7bd865bfa59af79f571d295cd4d4fd9c35d..1baaa8e12620e2040aebc5d8f3d45bd607233dcd 100644
--- a/README.md
+++ b/README.md
@@ -65,8 +65,6 @@ A more advanced implementation of the precedent example
An example of classification using a dense neural network for the famous MNIST dataset
### Images classification with Convolutional Neural Networks (CNN)
-- **[??](GTSRB/00-Test.ipynb)** - [??](GTSRB/00-Test.ipynb)
-??
- **[GTSRB1](GTSRB/01-Preparation-of-data.ipynb)** - [Dataset analysis and preparation](GTSRB/01-Preparation-of-data.ipynb)
Episode 1 : Analysis of the GTSRB dataset and creation of an enhanced dataset
- **[GTSRB2](GTSRB/02-First-convolutions.ipynb)** - [First convolutions](GTSRB/02-First-convolutions.ipynb)
diff --git a/fidle/01 - Set and reset.ipynb b/fidle/01 - Update index.ipynb
similarity index 94%
rename from fidle/01 - Set and reset.ipynb
rename to fidle/01 - Update index.ipynb
index b5065b10011a140e508522e9e078c6681263d453..571142bd5a623a5a35d5edb576f10a361673d10e 100644
--- a/fidle/01 - Set and reset.ipynb
+++ b/fidle/01 - Update index.ipynb
@@ -8,10 +8,13 @@
"\n",
"\n",
"## Mise a jour du catalog des notebooks et des READMEs\n",
- " - Génération du **catalog des notebooks** : `./log/catalog_nb.json`\n",
- " - Génération automatique de la **table des matières**\n",
- " - Mise à jour des **README** `README.md` et `REAME.ipynb`\n",
- " - #Reset du **finihed_file**\n",
+ " - Génération du **catalog des notebooks** : [./logs/catalog.json](./logs/catalog.json) \n",
+ " Ce fichier comporte une liste détaillée de tous les notebooks et scripts.\n",
+ " \n",
+ " \n",
+ " - Génération automatique de la table des matières et mise à jour des **README**\n",
+ " - [README.md](../README.md)\n",
+ " - [README.ipynb](../README.ipynb)\n",
"\n"
]
},
@@ -42,14 +45,15 @@
"sys.path.append('..')\n",
"import fidle.pwk as pwk\n",
"import fidle.config as config\n",
- "import fidle.cooker as cooker\n"
+ "import fidle.cookindex as cookindex\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "## Step 2 - List of folders containing notebooks to be indexed :"
+ "## Step 2 - List of folders containing notebooks to be indexed :\n",
+ "Order wil be index order"
]
},
{
@@ -88,19 +92,19 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Catalog saved as ../fidle/log/catalog.json\n",
- "Entries : 37\n"
+ "Catalog saved as ../fidle/logs/catalog.json\n",
+ "Entries : 36\n"
]
}
],
"source": [
"# ---- Get the notebook list\n",
"#\n",
- "files_list = cooker.get_files(directories_to_index.keys())\n",
+ "files_list = cookindex.get_files(directories_to_index.keys())\n",
"\n",
"# ---- Get a detailled catalog for this list\n",
"#\n",
- "catalog = cooker.get_catalog(files_list)\n",
+ "catalog = cookindex.get_catalog(files_list)\n",
"\n",
"with open(config.CATALOG_FILE,'wt') as fp:\n",
" json.dump(catalog,fp,indent=4)\n",
@@ -161,8 +165,6 @@
"An example of classification using a dense neural network for the famous MNIST dataset\n",
"\n",
"### Images classification with Convolutional Neural Networks (CNN)\n",
- "- **[??](GTSRB/00-Test.ipynb)** - [??](GTSRB/00-Test.ipynb) \n",
- "??\n",
"- **[GTSRB1](GTSRB/01-Preparation-of-data.ipynb)** - [Dataset analysis and preparation](GTSRB/01-Preparation-of-data.ipynb) \n",
"Episode 1 : Analysis of the GTSRB dataset and creation of an enhanced dataset\n",
"- **[GTSRB2](GTSRB/02-First-convolutions.ipynb)** - [First convolutions](GTSRB/02-First-convolutions.ipynb) \n",
@@ -308,8 +310,8 @@
" \n",
"# ---- Update index, version\n",
"#\n",
- "readme = cooker.tag('INDEX', index_md, readme)\n",
- "readme = cooker.tag('VERSION', config.VERSION, readme)\n",
+ "readme = cookindex.tag('INDEX', index_md, readme)\n",
+ "readme = cookindex.tag('VERSION', config.VERSION, readme)\n",
"\n",
"# ---- Save it\n",
"#\n",
@@ -407,22 +409,6 @@
"print('README.ipynb built and saved')"
]
},
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Step 7 - Reset Finished_file"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [],
- "source": [
- "# pwk.reset_finished_file()"
- ]
- },
{
"cell_type": "markdown",
"metadata": {},
diff --git a/fidle/02 - Running test.ipynb b/fidle/02 - Running test.ipynb
index 0076fa2d43c32e7663e3f99b5ad0f02010d4dfa1..bce3a2538b43833362b9f35c244258243094ae60 100644
--- a/fidle/02 - Running test.ipynb
+++ b/fidle/02 - Running test.ipynb
@@ -7,14 +7,19 @@
"<img width=\"800px\" src=\"../fidle/img/00-Fidle-header-01.svg\"></img>\n",
"\n",
"\n",
- "## Continuous integration report\n",
+ "# Gestion des tests d'intégration continue\n",
"\n",
- "Each notebook indicates its start and end of execution:\n",
- " - at the beginning, with `pwk.init()`\n",
- " - at the end, with `pwk.end()` \n",
- " \n",
- "All of theses informations are saved in a json file - Final report is below and in a HTML file. \n",
- "See ./log"
+ "**La liste des notebooks a éxécuter** et de leurs paramètres (override) est définie dans un **profile**. \n",
+ " - Un profile est un fichier yaml\n",
+ " - Un profile par défaut est généré en (1).\n",
+ "\n",
+ "Lorqu'un **profile** est prêt, il peut être soumis pour **éxécution** (2)\n",
+ " - Pour chaque notebook, les paramètres sont positionnés (variables d'env.)\n",
+ " - Le notebook est lu, puis éxécuté\n",
+ " - Après éxécution, le notebook est sauvegardé sous son nom moodifié (output_tag)\n",
+ "\n",
+ "Un **rapport d'éxécution** est généré durant l'éxécution des tests : [./logs/ci_report.json](./logs/ci_report.json) \n",
+ "A la fin des tests, ce rapport peut être visualisé via le notebook : [./03-ci_report.ipynb](./03%20-%20ci_report.ipynb)\n"
]
},
{
@@ -23,46 +28,84 @@
"metadata": {},
"outputs": [],
"source": [
- "import sys,os\n",
- "import json\n",
- "import datetime, time\n",
- "import nbformat\n",
- "from nbconvert.preprocessors import ExecutePreprocessor\n",
- "import re\n",
- "import yaml\n",
- "from collections import OrderedDict\n",
- "from IPython.display import display\n",
- "sys.path.append('..')\n",
- "import fidle.config as config\n",
- "import fidle.cooker as cooker"
+ "import cookci"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Get and Save default profile\n",
+ "Génère un profile par défaut comprenant tous les notebooks du moment... \n",
+ "...en tout cas présent dans catalog.json ;-)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Catalog saved as ./ci/default.yml\n",
+ "Entries : 36\n"
+ ]
+ }
+ ],
+ "source": [
+ "profile = cookci.get_ci_profile()\n",
+ "cookci.save_profile(profile, './ci/default.yml')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Load a saved profile"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"./ci/smart.yml loaded.\n",
- "Entries : 4\n",
+ "Entries : 3\n"
+ ]
+ }
+ ],
+ "source": [
+ "smart_profile = cookci.load_profile('./ci/smart.yml')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Run this profile"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
"\n",
"Notebook : LINR1\n",
" Run notebook.....done.\n",
" Duration : 0:00:04\n",
" Saved as : 01-Linear-Regression==done==.ipynb\n",
"\n",
- "Notebook : GTSRB0\n",
- " set overrides :\n",
- " FIDLE_OVERRIDE_GTSRB0_scale = 0.7\n",
- " FIDLE_OVERRIDE_GTSRB0_output_dir = ./data/foobar\n",
- " FIDLE_OVERRIDE_GTSRB0_run_dir = ./run/xxx\n",
- " Run notebook.....done.\n",
- " Duration : 0:00:02\n",
- " Saved as : 00-Test==done==.ipynb\n",
- "\n",
"Notebook : GTSRB1\n",
" set overrides :\n",
" FIDLE_OVERRIDE_GTSRB1_scale = 0.1\n",
@@ -78,159 +121,46 @@
" FIDLE_OVERRIDE_GTSRB2_batch_size = 32\n",
" FIDLE_OVERRIDE_GTSRB2_epochs = 3\n",
" FIDLE_OVERRIDE_GTSRB2_scale = 1\n",
- " Run notebook.....done.\n",
- " Duration : 0:03:02\n",
- " Saved as : 02-First-convolutions==done==.ipynb\n"
+ " Run notebook..."
+ ]
+ },
+ {
+ "ename": "DeadKernelError",
+ "evalue": "Kernel died",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mCancelledError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/site-packages/nbclient/client.py\u001b[0m in \u001b[0;36masync_execute_cell\u001b[0;34m(self, cell, cell_index, execution_count, store_history)\u001b[0m\n\u001b[1;32m 815\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 816\u001b[0;31m \u001b[0mexec_reply\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mawait\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtask_poll_for_reply\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 817\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0masyncio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCancelledError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/asyncio/futures.py\u001b[0m in \u001b[0;36m__await__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 262\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_asyncio_future_blocking\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 263\u001b[0;31m \u001b[0;32myield\u001b[0m \u001b[0mself\u001b[0m \u001b[0;31m# This tells Task to wait for completion.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 264\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdone\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/asyncio/tasks.py\u001b[0m in \u001b[0;36m__wakeup\u001b[0;34m(self, future)\u001b[0m\n\u001b[1;32m 317\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 318\u001b[0;31m \u001b[0mfuture\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 319\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/asyncio/futures.py\u001b[0m in \u001b[0;36mresult\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 175\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_state\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0m_CANCELLED\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 176\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mCancelledError\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 177\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_state\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0m_FINISHED\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mCancelledError\u001b[0m: ",
+ "\nDuring handling of the above exception, another exception occurred:\n",
+ "\u001b[0;31mDeadKernelError\u001b[0m Traceback (most recent call last)",
+ "\u001b[0;32m<ipython-input-4-36d9a3afb9e4>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mcookci\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_profile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msmart_profile\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+ "\u001b[0;32m~/dev/fidle/fidle/cookci.py\u001b[0m in \u001b[0;36mrun_profile\u001b[0;34m(profile, top_dir)\u001b[0m\n\u001b[1;32m 165\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m' Run notebook...'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mend\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m''\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 166\u001b[0m \u001b[0mep\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mExecutePreprocessor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m600\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkernel_name\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"python3\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 167\u001b[0;31m \u001b[0mep\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpreprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnotebook\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 168\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'..done.'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 169\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/site-packages/nbconvert/preprocessors/execute.py\u001b[0m in \u001b[0;36mpreprocess\u001b[0;34m(self, nb, resources, km)\u001b[0m\n\u001b[1;32m 77\u001b[0m \u001b[0mNotebookClient\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkm\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 78\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_assign_resources\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresources\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 79\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexecute\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 80\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresources\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 81\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/site-packages/nbclient/util.py\u001b[0m in \u001b[0;36mwrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 72\u001b[0m \"\"\"\n\u001b[1;32m 73\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mwrapped\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 74\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mjust_run\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcoro\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 75\u001b[0m \u001b[0mwrapped\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcoro\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 76\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mwrapped\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/site-packages/nbclient/util.py\u001b[0m in \u001b[0;36mjust_run\u001b[0;34m(coro)\u001b[0m\n\u001b[1;32m 51\u001b[0m \u001b[0mnest_asyncio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 52\u001b[0m \u001b[0mcheck_patch_tornado\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 53\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mloop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_until_complete\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcoro\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 54\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 55\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/site-packages/nest_asyncio.py\u001b[0m in \u001b[0;36mrun_until_complete\u001b[0;34m(self, future)\u001b[0m\n\u001b[1;32m 96\u001b[0m raise RuntimeError(\n\u001b[1;32m 97\u001b[0m 'Event loop stopped before Future completed.')\n\u001b[0;32m---> 98\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 99\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 100\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_thread_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mold_thread_id\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/asyncio/futures.py\u001b[0m in \u001b[0;36mresult\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 179\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__log_traceback\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 180\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_exception\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 181\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_exception\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 182\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_result\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 183\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/asyncio/tasks.py\u001b[0m in \u001b[0;36m__step\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m 247\u001b[0m \u001b[0;31m# We use the `send` method directly, because coroutines\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 248\u001b[0m \u001b[0;31m# don't have `__iter__` and `__next__` methods.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 249\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcoro\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 250\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 251\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcoro\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mthrow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/site-packages/nbclient/client.py\u001b[0m in \u001b[0;36masync_execute\u001b[0;34m(self, reset_kc, **kwargs)\u001b[0m\n\u001b[1;32m 539\u001b[0m \u001b[0;31m# when store_history is False\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 540\u001b[0m await self.async_execute_cell(\n\u001b[0;32m--> 541\u001b[0;31m \u001b[0mcell\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexecution_count\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcode_cells_executed\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 542\u001b[0m )\n\u001b[1;32m 543\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_widgets_metadata\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/site-packages/nbconvert/preprocessors/execute.py\u001b[0m in \u001b[0;36masync_execute_cell\u001b[0;34m(self, cell, cell_index, execution_count, store_history)\u001b[0m\n\u001b[1;32m 121\u001b[0m \u001b[0;31m# Copied and intercepted to allow for custom preprocess_cell contracts to be fullfilled\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 122\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstore_history\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstore_history\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 123\u001b[0;31m \u001b[0mcell\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresources\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpreprocess_cell\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcell\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresources\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcell_index\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 124\u001b[0m \u001b[0;31m# Apply rules from nbclient for where to apply execution counts\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 125\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mexecution_count\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mcell\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcell_type\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'code'\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mcell\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msource\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/site-packages/nbconvert/preprocessors/execute.py\u001b[0m in \u001b[0;36mpreprocess_cell\u001b[0;34m(self, cell, resources, index, **kwargs)\u001b[0m\n\u001b[1;32m 144\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_assign_resources\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresources\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 145\u001b[0m \u001b[0;31m# Because nbclient is an async library, we need to wrap the parent async call to generate a syncronous version.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 146\u001b[0;31m \u001b[0mcell\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrun_sync\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mNotebookClient\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masync_execute_cell\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcell\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstore_history\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstore_history\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 147\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mcell\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresources\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/site-packages/nbclient/util.py\u001b[0m in \u001b[0;36mwrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 72\u001b[0m \"\"\"\n\u001b[1;32m 73\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mwrapped\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 74\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mjust_run\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcoro\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 75\u001b[0m \u001b[0mwrapped\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcoro\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 76\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mwrapped\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/site-packages/nbclient/util.py\u001b[0m in \u001b[0;36mjust_run\u001b[0;34m(coro)\u001b[0m\n\u001b[1;32m 51\u001b[0m \u001b[0mnest_asyncio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 52\u001b[0m \u001b[0mcheck_patch_tornado\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 53\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mloop\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_until_complete\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcoro\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 54\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 55\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/site-packages/nest_asyncio.py\u001b[0m in \u001b[0;36mrun_until_complete\u001b[0;34m(self, future)\u001b[0m\n\u001b[1;32m 96\u001b[0m raise RuntimeError(\n\u001b[1;32m 97\u001b[0m 'Event loop stopped before Future completed.')\n\u001b[0;32m---> 98\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 99\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 100\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_thread_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mold_thread_id\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/asyncio/futures.py\u001b[0m in \u001b[0;36mresult\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 179\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__log_traceback\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 180\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_exception\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 181\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_exception\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 182\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_result\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 183\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/asyncio/tasks.py\u001b[0m in \u001b[0;36m__step\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m 249\u001b[0m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcoro\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 250\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 251\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcoro\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mthrow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 252\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 253\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_must_cancel\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;32m~/anaconda3/envs/fidle/lib/python3.7/site-packages/nbclient/client.py\u001b[0m in \u001b[0;36masync_execute_cell\u001b[0;34m(self, cell, cell_index, execution_count, store_history)\u001b[0m\n\u001b[1;32m 818\u001b[0m \u001b[0;31m# can only be cancelled by task_poll_kernel_alive when the kernel is dead\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 819\u001b[0m \u001b[0mtask_poll_output_msg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcancel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 820\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mDeadKernelError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Kernel died\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 821\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 822\u001b[0m \u001b[0;31m# Best effort to cancel request if it hasn't been resolved\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+ "\u001b[0;31mDeadKernelError\u001b[0m: Kernel died"
]
}
],
"source": [
- "\n",
- "_start_time=None\n",
- "\n",
- "def get_profile(existant_config=None, output_tag='==done==', save_figs=True):\n",
- " \n",
- " catalog = cooker.read_catalog()\n",
- "\n",
- " config = {'version':'1.0', 'output_tag':output_tag, 'save_figs':save_figs}\n",
- " profile = { 'config':config }\n",
- " for id, about in catalog.items():\n",
- " \n",
- " id = about['id']\n",
- " title = about['title']\n",
- " dirname = about['dirname']\n",
- " basename = about['basename']\n",
- " overrides = about.get('overrides',None)\n",
- " \n",
- " notebook = {}\n",
- " notebook['notebook_dir'] = dirname\n",
- " notebook['notebook_src'] = basename\n",
- " notebook['notebook_out'] = 'default'\n",
- " if len(overrides)>0:\n",
- " notebook['overrides']={ name:'default' for name in overrides }\n",
- " \n",
- " profile[id]=notebook\n",
- " \n",
- " return profile\n",
- "\n",
- "\n",
- "def save_profile(profile, filename):\n",
- " with open(filename,'wt') as fp:\n",
- " yaml.dump(profile, fp, sort_keys=False)\n",
- " print(f'Catalog saved as {filename}')\n",
- " print('Entries : ',len(profile)-1)\n",
- "\n",
- "def load_profile(filename):\n",
- " with open(filename,'r') as fp:\n",
- " profile=yaml.load(fp, Loader=yaml.FullLoader)\n",
- " print(f'{filename} loaded.')\n",
- " print('Entries : ',len(profile)-1)\n",
- " return profile\n",
- " \n",
- "def chrono_start():\n",
- " global _start_time\n",
- " _start_time = time.time()\n",
- "\n",
- "def chrono_hdelay():\n",
- " global _start_time\n",
- " delay=int( time.time() - _start_time )\n",
- " return str(datetime.timedelta(seconds=delay))\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "def run_profile(profile, top_dir='..'):\n",
- "\n",
- " # ---- My place\n",
- " #\n",
- " home = os.getcwd()\n",
- " \n",
- " # ---- Read profile\n",
- " #\n",
- " config = profile['config']\n",
- " notebooks = profile\n",
- " del notebooks['config']\n",
- " \n",
- " # ---- Save figs or not ?\n",
- " #\n",
- " os.environ['FIDLE_SAVE_FIGS']=str(config['save_figs'])\n",
- "\n",
- " # ---- For each notebook\n",
- " #\n",
- " for id,about in notebooks.items():\n",
- " \n",
- " print(f'\\nNotebook : {id}')\n",
- "\n",
- " # ---- Get notebook infos ---------------------------------------------\n",
- " #\n",
- " notebook_dir = about['notebook_dir']\n",
- " notebook_src = about['notebook_src']\n",
- " notebook_out = about['notebook_out']\n",
- " overrides = about.get('overrides',None)\n",
- "\n",
- " # ---- notebook_out (Default)\n",
- " #\n",
- " if notebook_out=='default':\n",
- " notebook_out = notebook_src.replace('.ipynb', config['output_tag']+'.ipynb')\n",
- " \n",
- " # ---- Override ------------------------------------------------------- \n",
- " \n",
- " to_unset=[]\n",
- " if isinstance(overrides,dict):\n",
- " print(' set overrides :')\n",
- " for name,value in overrides.items():\n",
- " # ---- Default : no nothing\n",
- " if value=='default' : continue\n",
- " # ---- Set env\n",
- " env_name = f'FIDLE_OVERRIDE_{id.upper()}_{name}'\n",
- " env_value = str(value)\n",
- " os.environ[env_name] = env_value\n",
- " # ---- For cleaning\n",
- " to_unset.append(env_name)\n",
- " # ---- Fine :(-)\n",
- " print(f' {env_name:38s} = {env_value}')\n",
- " \n",
- " # ---- Run it ! -------------------------------------------------------\n",
- " \n",
- " # ---- Go to the right place\n",
- " #\n",
- " os.chdir(f'{top_dir}/{notebook_dir}')\n",
- " notebook = nbformat.read( f'{notebook_src}', nbformat.NO_CONVERT)\n",
- "\n",
- " print(' Run notebook...',end='')\n",
- " ep = ExecutePreprocessor(timeout=600, kernel_name=\"python3\")\n",
- " chrono_start()\n",
- " ep.preprocess(notebook)\n",
- " print('..done.')\n",
- " print(' Duration : ',chrono_hdelay() )\n",
- " \n",
- " # ---- Save it\n",
- " #\n",
- " with open( f'{notebook_out}', mode=\"w\", encoding='utf-8') as fp:\n",
- " nbformat.write(notebook, fp)\n",
- " print(' Saved as : ',notebook_out)\n",
- " \n",
- " # ---- Back to home and clean\n",
- " #\n",
- " os.chdir(home)\n",
- " for env_name in to_unset:\n",
- " del os.environ[env_name] \n",
- " \n",
- " \n",
- "# ---- Save profile\n",
- " \n",
- "# profile = get_profile()\n",
- "# save_profile(profile, './ci/default.yml')\n",
- "# profile=load_profile('./ci/default.yml')\n",
- " \n",
- " \n",
- "# ---- Run profile \n",
- " \n",
- "profile = load_profile('./ci/smart.yml')\n",
- "\n",
- "run_profile(profile)\n",
- "\n"
+ "cookci.run_profile(smart_profile)"
]
},
{
@@ -240,20 +170,6 @@
"---\n",
"<img width=\"80px\" src=\"../fidle/img/00-Fidle-logo-01.svg\"></img>"
]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
}
],
"metadata": {
diff --git a/fidle/03 - Finished report.ipynb b/fidle/03 - ci_report.ipynb
similarity index 57%
rename from fidle/03 - Finished report.ipynb
rename to fidle/03 - ci_report.ipynb
index f397cbc5c449bad0c3e2ed44baf276b8ffc04bb6..6403c5a2cd155a2d48faebf348ed97e1e261d0da 100644
--- a/fidle/03 - Finished report.ipynb
+++ b/fidle/03 - ci_report.ipynb
@@ -17,16 +17,6 @@
"See ./log"
]
},
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [],
- "source": [
- "import sys\n",
- "import cooker as cooker"
- ]
- },
{
"cell_type": "code",
"execution_count": 2,
@@ -36,142 +26,142 @@
"data": {
"text/html": [
"<style type=\"text/css\" >\n",
- " #T_8a68a_ td {\n",
+ " #T_15a01_ td {\n",
" font-size: 110%;\n",
" text-align: left;\n",
- " } #T_8a68a_ th {\n",
+ " } #T_15a01_ th {\n",
" font-size: 110%;\n",
" text-align: left;\n",
- " }#T_8a68a_row13_col5,#T_8a68a_row14_col5{\n",
+ " }#T_15a01_row4_col5,#T_15a01_row13_col5,#T_15a01_row14_col5{\n",
" background-color: OrangeRed;\n",
" color: white;\n",
" background-color: OrangeRed;\n",
" color: white;\n",
- " }</style><table id=\"T_8a68a_\" ><thead> <tr> <th class=\"col_heading level0 col0\" >id</th> <th class=\"col_heading level0 col1\" >Repo</th> <th class=\"col_heading level0 col2\" >Name</th> <th class=\"col_heading level0 col3\" >Start</th> <th class=\"col_heading level0 col4\" >End</th> <th class=\"col_heading level0 col5\" >Duration</th> </tr></thead><tbody>\n",
+ " }</style><table id=\"T_15a01_\" ><thead> <tr> <th class=\"col_heading level0 col0\" >id</th> <th class=\"col_heading level0 col1\" >Repo</th> <th class=\"col_heading level0 col2\" >Name</th> <th class=\"col_heading level0 col3\" >Start</th> <th class=\"col_heading level0 col4\" >End</th> <th class=\"col_heading level0 col5\" >Duration</th> </tr></thead><tbody>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row0_col0\" class=\"data row0 col0\" ><a href=\"../LinearReg/01-Linear-Regression.ipynb\">LINR1</a></td>\n",
- " <td id=\"T_8a68a_row0_col1\" class=\"data row0 col1\" >LinearReg</td>\n",
- " <td id=\"T_8a68a_row0_col2\" class=\"data row0 col2\" ><a href=\"../LinearReg/01-Linear-Regression.ipynb\"><b>01-Linear-Regression.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row0_col3\" class=\"data row0 col3\" >Saturday 9 January 2021, 19:34:10</td>\n",
- " <td id=\"T_8a68a_row0_col4\" class=\"data row0 col4\" >Saturday 9 January 2021, 19:34:11</td>\n",
- " <td id=\"T_8a68a_row0_col5\" class=\"data row0 col5\" >00:00:01 667ms</td>\n",
+ " <td id=\"T_15a01_row0_col0\" class=\"data row0 col0\" ><a href=\"../LinearReg/01-Linear-Regression.ipynb\">LINR1</a></td>\n",
+ " <td id=\"T_15a01_row0_col1\" class=\"data row0 col1\" >LinearReg</td>\n",
+ " <td id=\"T_15a01_row0_col2\" class=\"data row0 col2\" ><a href=\"../LinearReg/01-Linear-Regression.ipynb\"><b>01-Linear-Regression.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row0_col3\" class=\"data row0 col3\" >Sunday 10 January 2021, 22:54:49</td>\n",
+ " <td id=\"T_15a01_row0_col4\" class=\"data row0 col4\" >Sunday 10 January 2021, 22:54:53</td>\n",
+ " <td id=\"T_15a01_row0_col5\" class=\"data row0 col5\" >0:00:04</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row1_col0\" class=\"data row1 col0\" ><a href=\"../BHPD/01-DNN-Regression.ipynb\">BHPD1</a></td>\n",
- " <td id=\"T_8a68a_row1_col1\" class=\"data row1 col1\" >BHPD</td>\n",
- " <td id=\"T_8a68a_row1_col2\" class=\"data row1 col2\" ><a href=\"../BHPD/01-DNN-Regression.ipynb\"><b>01-DNN-Regression.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row1_col3\" class=\"data row1 col3\" >Friday 8 January 2021, 01:09:13</td>\n",
- " <td id=\"T_8a68a_row1_col4\" class=\"data row1 col4\" >Friday 8 January 2021, 01:09:24</td>\n",
- " <td id=\"T_8a68a_row1_col5\" class=\"data row1 col5\" >00:00:11 984ms</td>\n",
+ " <td id=\"T_15a01_row1_col0\" class=\"data row1 col0\" ><a href=\"../BHPD/01-DNN-Regression.ipynb\">BHPD1</a></td>\n",
+ " <td id=\"T_15a01_row1_col1\" class=\"data row1 col1\" >BHPD</td>\n",
+ " <td id=\"T_15a01_row1_col2\" class=\"data row1 col2\" ><a href=\"../BHPD/01-DNN-Regression.ipynb\"><b>01-DNN-Regression.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row1_col3\" class=\"data row1 col3\" >Friday 8 January 2021, 01:09:13</td>\n",
+ " <td id=\"T_15a01_row1_col4\" class=\"data row1 col4\" >Friday 8 January 2021, 01:09:24</td>\n",
+ " <td id=\"T_15a01_row1_col5\" class=\"data row1 col5\" >00:00:11 984ms</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row2_col0\" class=\"data row2 col0\" ><a href=\"../BHPD/02-DNN-Regression-Premium.ipynb\">BHPD2</a></td>\n",
- " <td id=\"T_8a68a_row2_col1\" class=\"data row2 col1\" >BHPD</td>\n",
- " <td id=\"T_8a68a_row2_col2\" class=\"data row2 col2\" ><a href=\"../BHPD/02-DNN-Regression-Premium.ipynb\"><b>02-DNN-Regression-Premium.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row2_col3\" class=\"data row2 col3\" >Friday 8 January 2021, 01:10:28</td>\n",
- " <td id=\"T_8a68a_row2_col4\" class=\"data row2 col4\" >Friday 8 January 2021, 01:10:39</td>\n",
- " <td id=\"T_8a68a_row2_col5\" class=\"data row2 col5\" >00:00:12 582ms</td>\n",
+ " <td id=\"T_15a01_row2_col0\" class=\"data row2 col0\" ><a href=\"../BHPD/02-DNN-Regression-Premium.ipynb\">BHPD2</a></td>\n",
+ " <td id=\"T_15a01_row2_col1\" class=\"data row2 col1\" >BHPD</td>\n",
+ " <td id=\"T_15a01_row2_col2\" class=\"data row2 col2\" ><a href=\"../BHPD/02-DNN-Regression-Premium.ipynb\"><b>02-DNN-Regression-Premium.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row2_col3\" class=\"data row2 col3\" >Friday 8 January 2021, 01:10:28</td>\n",
+ " <td id=\"T_15a01_row2_col4\" class=\"data row2 col4\" >Friday 8 January 2021, 01:10:39</td>\n",
+ " <td id=\"T_15a01_row2_col5\" class=\"data row2 col5\" >00:00:12 582ms</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row3_col0\" class=\"data row3 col0\" ><a href=\"../GTSRB/01-Preparation-of-data.ipynb\">GTSRB1</a></td>\n",
- " <td id=\"T_8a68a_row3_col1\" class=\"data row3 col1\" >GTSRB</td>\n",
- " <td id=\"T_8a68a_row3_col2\" class=\"data row3 col2\" ><a href=\"../GTSRB/01-Preparation-of-data.ipynb\"><b>01-Preparation-of-data.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row3_col3\" class=\"data row3 col3\" >Saturday 9 January 2021, 19:34:16</td>\n",
- " <td id=\"T_8a68a_row3_col4\" class=\"data row3 col4\" >Saturday 9 January 2021, 19:36:14</td>\n",
- " <td id=\"T_8a68a_row3_col5\" class=\"data row3 col5\" >00:01:58 919ms</td>\n",
+ " <td id=\"T_15a01_row3_col0\" class=\"data row3 col0\" ><a href=\"../GTSRB/01-Preparation-of-data.ipynb\">GTSRB1</a></td>\n",
+ " <td id=\"T_15a01_row3_col1\" class=\"data row3 col1\" >GTSRB</td>\n",
+ " <td id=\"T_15a01_row3_col2\" class=\"data row3 col2\" ><a href=\"../GTSRB/01-Preparation-of-data.ipynb\"><b>01-Preparation-of-data.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row3_col3\" class=\"data row3 col3\" >Sunday 10 January 2021, 22:54:53</td>\n",
+ " <td id=\"T_15a01_row3_col4\" class=\"data row3 col4\" >Sunday 10 January 2021, 22:56:54</td>\n",
+ " <td id=\"T_15a01_row3_col5\" class=\"data row3 col5\" >0:02:00</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row4_col0\" class=\"data row4 col0\" ><a href=\"../GTSRB/02-First-convolutions.ipynb\">GTSRB2</a></td>\n",
- " <td id=\"T_8a68a_row4_col1\" class=\"data row4 col1\" >GTSRB</td>\n",
- " <td id=\"T_8a68a_row4_col2\" class=\"data row4 col2\" ><a href=\"../GTSRB/02-First-convolutions.ipynb\"><b>02-First-convolutions.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row4_col3\" class=\"data row4 col3\" >Saturday 9 January 2021, 19:36:17</td>\n",
- " <td id=\"T_8a68a_row4_col4\" class=\"data row4 col4\" >Saturday 9 January 2021, 19:39:16</td>\n",
- " <td id=\"T_8a68a_row4_col5\" class=\"data row4 col5\" >00:02:59 895ms</td>\n",
+ " <td id=\"T_15a01_row4_col0\" class=\"data row4 col0\" ><a href=\"../GTSRB/02-First-convolutions.ipynb\">GTSRB2</a></td>\n",
+ " <td id=\"T_15a01_row4_col1\" class=\"data row4 col1\" >GTSRB</td>\n",
+ " <td id=\"T_15a01_row4_col2\" class=\"data row4 col2\" ><a href=\"../GTSRB/02-First-convolutions.ipynb\"><b>02-First-convolutions.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row4_col3\" class=\"data row4 col3\" >Sunday 10 January 2021, 22:56:54</td>\n",
+ " <td id=\"T_15a01_row4_col4\" class=\"data row4 col4\" ></td>\n",
+ " <td id=\"T_15a01_row4_col5\" class=\"data row4 col5\" >Unfinished...</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row5_col0\" class=\"data row5 col0\" ><a href=\"../GTSRB/03-Tracking-and-visualizing.ipynb\">GTSRB3</a></td>\n",
- " <td id=\"T_8a68a_row5_col1\" class=\"data row5 col1\" >GTSRB</td>\n",
- " <td id=\"T_8a68a_row5_col2\" class=\"data row5 col2\" ><a href=\"../GTSRB/03-Tracking-and-visualizing.ipynb\"><b>03-Tracking-and-visualizing.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row5_col3\" class=\"data row5 col3\" >Thursday 7 January 2021, 12:15:52</td>\n",
- " <td id=\"T_8a68a_row5_col4\" class=\"data row5 col4\" >Thursday 7 January 2021, 12:20:01</td>\n",
- " <td id=\"T_8a68a_row5_col5\" class=\"data row5 col5\" >00:04:09 711ms</td>\n",
+ " <td id=\"T_15a01_row5_col0\" class=\"data row5 col0\" ><a href=\"../GTSRB/03-Tracking-and-visualizing.ipynb\">GTSRB3</a></td>\n",
+ " <td id=\"T_15a01_row5_col1\" class=\"data row5 col1\" >GTSRB</td>\n",
+ " <td id=\"T_15a01_row5_col2\" class=\"data row5 col2\" ><a href=\"../GTSRB/03-Tracking-and-visualizing.ipynb\"><b>03-Tracking-and-visualizing.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row5_col3\" class=\"data row5 col3\" >Thursday 7 January 2021, 12:15:52</td>\n",
+ " <td id=\"T_15a01_row5_col4\" class=\"data row5 col4\" >Thursday 7 January 2021, 12:20:01</td>\n",
+ " <td id=\"T_15a01_row5_col5\" class=\"data row5 col5\" >00:04:09 711ms</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row6_col0\" class=\"data row6 col0\" ><a href=\"../GTSRB/04-Data-augmentation.ipynb\">GTSRB4</a></td>\n",
- " <td id=\"T_8a68a_row6_col1\" class=\"data row6 col1\" >GTSRB</td>\n",
- " <td id=\"T_8a68a_row6_col2\" class=\"data row6 col2\" ><a href=\"../GTSRB/04-Data-augmentation.ipynb\"><b>04-Data-augmentation.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row6_col3\" class=\"data row6 col3\" >Thursday 7 January 2021, 13:40:52</td>\n",
- " <td id=\"T_8a68a_row6_col4\" class=\"data row6 col4\" >Thursday 7 January 2021, 13:41:31</td>\n",
- " <td id=\"T_8a68a_row6_col5\" class=\"data row6 col5\" >00:00:39 161ms</td>\n",
+ " <td id=\"T_15a01_row6_col0\" class=\"data row6 col0\" ><a href=\"../GTSRB/04-Data-augmentation.ipynb\">GTSRB4</a></td>\n",
+ " <td id=\"T_15a01_row6_col1\" class=\"data row6 col1\" >GTSRB</td>\n",
+ " <td id=\"T_15a01_row6_col2\" class=\"data row6 col2\" ><a href=\"../GTSRB/04-Data-augmentation.ipynb\"><b>04-Data-augmentation.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row6_col3\" class=\"data row6 col3\" >Thursday 7 January 2021, 13:40:52</td>\n",
+ " <td id=\"T_15a01_row6_col4\" class=\"data row6 col4\" >Thursday 7 January 2021, 13:41:31</td>\n",
+ " <td id=\"T_15a01_row6_col5\" class=\"data row6 col5\" >00:00:39 161ms</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row7_col0\" class=\"data row7 col0\" ><a href=\"../GTSRB/05-Full-convolutions.ipynb\">GTSRB5</a></td>\n",
- " <td id=\"T_8a68a_row7_col1\" class=\"data row7 col1\" >GTSRB</td>\n",
- " <td id=\"T_8a68a_row7_col2\" class=\"data row7 col2\" ><a href=\"../GTSRB/05-Full-convolutions.ipynb\"><b>05-Full-convolutions.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row7_col3\" class=\"data row7 col3\" >Thursday 7 January 2021, 14:47:12</td>\n",
- " <td id=\"T_8a68a_row7_col4\" class=\"data row7 col4\" >Thursday 7 January 2021, 14:48:44</td>\n",
- " <td id=\"T_8a68a_row7_col5\" class=\"data row7 col5\" >00:01:32 269ms</td>\n",
+ " <td id=\"T_15a01_row7_col0\" class=\"data row7 col0\" ><a href=\"../GTSRB/05-Full-convolutions.ipynb\">GTSRB5</a></td>\n",
+ " <td id=\"T_15a01_row7_col1\" class=\"data row7 col1\" >GTSRB</td>\n",
+ " <td id=\"T_15a01_row7_col2\" class=\"data row7 col2\" ><a href=\"../GTSRB/05-Full-convolutions.ipynb\"><b>05-Full-convolutions.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row7_col3\" class=\"data row7 col3\" >Thursday 7 January 2021, 14:47:12</td>\n",
+ " <td id=\"T_15a01_row7_col4\" class=\"data row7 col4\" >Thursday 7 January 2021, 14:48:44</td>\n",
+ " <td id=\"T_15a01_row7_col5\" class=\"data row7 col5\" >00:01:32 269ms</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row8_col0\" class=\"data row8 col0\" ><a href=\"../GTSRB/06-Notebook-as-a-batch.ipynb\">GTSRB6</a></td>\n",
- " <td id=\"T_8a68a_row8_col1\" class=\"data row8 col1\" >GTSRB</td>\n",
- " <td id=\"T_8a68a_row8_col2\" class=\"data row8 col2\" ><a href=\"../GTSRB/06-Notebook-as-a-batch.ipynb\"><b>06-Notebook-as-a-batch.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row8_col3\" class=\"data row8 col3\" >Thursday 7 January 2021, 15:41:17</td>\n",
- " <td id=\"T_8a68a_row8_col4\" class=\"data row8 col4\" >Thursday 7 January 2021, 15:41:18</td>\n",
- " <td id=\"T_8a68a_row8_col5\" class=\"data row8 col5\" >00:00:01 101ms</td>\n",
+ " <td id=\"T_15a01_row8_col0\" class=\"data row8 col0\" ><a href=\"../GTSRB/06-Notebook-as-a-batch.ipynb\">GTSRB6</a></td>\n",
+ " <td id=\"T_15a01_row8_col1\" class=\"data row8 col1\" >GTSRB</td>\n",
+ " <td id=\"T_15a01_row8_col2\" class=\"data row8 col2\" ><a href=\"../GTSRB/06-Notebook-as-a-batch.ipynb\"><b>06-Notebook-as-a-batch.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row8_col3\" class=\"data row8 col3\" >Thursday 7 January 2021, 15:41:17</td>\n",
+ " <td id=\"T_15a01_row8_col4\" class=\"data row8 col4\" >Thursday 7 January 2021, 15:41:18</td>\n",
+ " <td id=\"T_15a01_row8_col5\" class=\"data row8 col5\" >00:00:01 101ms</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row9_col0\" class=\"data row9 col0\" ><a href=\"../GTSRB/07-Show-report.ipynb\">GTSRB7</a></td>\n",
- " <td id=\"T_8a68a_row9_col1\" class=\"data row9 col1\" >GTSRB</td>\n",
- " <td id=\"T_8a68a_row9_col2\" class=\"data row9 col2\" ><a href=\"../GTSRB/07-Show-report.ipynb\"><b>07-Show-report.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row9_col3\" class=\"data row9 col3\" >Thursday 7 January 2021, 15:16:05</td>\n",
- " <td id=\"T_8a68a_row9_col4\" class=\"data row9 col4\" >Thursday 7 January 2021, 15:16:06</td>\n",
- " <td id=\"T_8a68a_row9_col5\" class=\"data row9 col5\" >00:00:00 116ms</td>\n",
+ " <td id=\"T_15a01_row9_col0\" class=\"data row9 col0\" ><a href=\"../GTSRB/07-Show-report.ipynb\">GTSRB7</a></td>\n",
+ " <td id=\"T_15a01_row9_col1\" class=\"data row9 col1\" >GTSRB</td>\n",
+ " <td id=\"T_15a01_row9_col2\" class=\"data row9 col2\" ><a href=\"../GTSRB/07-Show-report.ipynb\"><b>07-Show-report.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row9_col3\" class=\"data row9 col3\" >Thursday 7 January 2021, 15:16:05</td>\n",
+ " <td id=\"T_15a01_row9_col4\" class=\"data row9 col4\" >Thursday 7 January 2021, 15:16:06</td>\n",
+ " <td id=\"T_15a01_row9_col5\" class=\"data row9 col5\" >00:00:00 116ms</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row10_col0\" class=\"data row10 col0\" ><a href=\"../SYNOP/01-Preparation-of-data.ipynb\">SYNOP1</a></td>\n",
- " <td id=\"T_8a68a_row10_col1\" class=\"data row10 col1\" >SYNOP</td>\n",
- " <td id=\"T_8a68a_row10_col2\" class=\"data row10 col2\" ><a href=\"../SYNOP/01-Preparation-of-data.ipynb\"><b>01-Preparation-of-data.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row10_col3\" class=\"data row10 col3\" >Saturday 9 January 2021, 10:04:28</td>\n",
- " <td id=\"T_8a68a_row10_col4\" class=\"data row10 col4\" >Saturday 9 January 2021, 10:04:34</td>\n",
- " <td id=\"T_8a68a_row10_col5\" class=\"data row10 col5\" >00:00:05 236ms</td>\n",
+ " <td id=\"T_15a01_row10_col0\" class=\"data row10 col0\" ><a href=\"../SYNOP/01-Preparation-of-data.ipynb\">SYNOP1</a></td>\n",
+ " <td id=\"T_15a01_row10_col1\" class=\"data row10 col1\" >SYNOP</td>\n",
+ " <td id=\"T_15a01_row10_col2\" class=\"data row10 col2\" ><a href=\"../SYNOP/01-Preparation-of-data.ipynb\"><b>01-Preparation-of-data.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row10_col3\" class=\"data row10 col3\" >Saturday 9 January 2021, 10:04:28</td>\n",
+ " <td id=\"T_15a01_row10_col4\" class=\"data row10 col4\" >Saturday 9 January 2021, 10:04:34</td>\n",
+ " <td id=\"T_15a01_row10_col5\" class=\"data row10 col5\" >00:00:05 236ms</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row11_col0\" class=\"data row11 col0\" ><a href=\"../SYNOP/02-First-predictions.ipynb\">SYNOP2</a></td>\n",
- " <td id=\"T_8a68a_row11_col1\" class=\"data row11 col1\" >SYNOP</td>\n",
- " <td id=\"T_8a68a_row11_col2\" class=\"data row11 col2\" ><a href=\"../SYNOP/02-First-predictions.ipynb\"><b>02-First-predictions.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row11_col3\" class=\"data row11 col3\" >Saturday 9 January 2021, 10:30:55</td>\n",
- " <td id=\"T_8a68a_row11_col4\" class=\"data row11 col4\" >Saturday 9 January 2021, 10:31:11</td>\n",
- " <td id=\"T_8a68a_row11_col5\" class=\"data row11 col5\" >00:00:16 248ms</td>\n",
+ " <td id=\"T_15a01_row11_col0\" class=\"data row11 col0\" ><a href=\"../SYNOP/02-First-predictions.ipynb\">SYNOP2</a></td>\n",
+ " <td id=\"T_15a01_row11_col1\" class=\"data row11 col1\" >SYNOP</td>\n",
+ " <td id=\"T_15a01_row11_col2\" class=\"data row11 col2\" ><a href=\"../SYNOP/02-First-predictions.ipynb\"><b>02-First-predictions.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row11_col3\" class=\"data row11 col3\" >Saturday 9 January 2021, 10:30:55</td>\n",
+ " <td id=\"T_15a01_row11_col4\" class=\"data row11 col4\" >Saturday 9 January 2021, 10:31:11</td>\n",
+ " <td id=\"T_15a01_row11_col5\" class=\"data row11 col5\" >00:00:16 248ms</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row12_col0\" class=\"data row12 col0\" ><a href=\"../SYNOP/03-12h-predictions.ipynb\">SYNOP3</a></td>\n",
- " <td id=\"T_8a68a_row12_col1\" class=\"data row12 col1\" >SYNOP</td>\n",
- " <td id=\"T_8a68a_row12_col2\" class=\"data row12 col2\" ><a href=\"../SYNOP/03-12h-predictions.ipynb\"><b>03-12h-predictions.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row12_col3\" class=\"data row12 col3\" >Saturday 9 January 2021, 10:27:54</td>\n",
- " <td id=\"T_8a68a_row12_col4\" class=\"data row12 col4\" >Saturday 9 January 2021, 10:27:59</td>\n",
- " <td id=\"T_8a68a_row12_col5\" class=\"data row12 col5\" >00:00:05 249ms</td>\n",
+ " <td id=\"T_15a01_row12_col0\" class=\"data row12 col0\" ><a href=\"../SYNOP/03-12h-predictions.ipynb\">SYNOP3</a></td>\n",
+ " <td id=\"T_15a01_row12_col1\" class=\"data row12 col1\" >SYNOP</td>\n",
+ " <td id=\"T_15a01_row12_col2\" class=\"data row12 col2\" ><a href=\"../SYNOP/03-12h-predictions.ipynb\"><b>03-12h-predictions.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row12_col3\" class=\"data row12 col3\" >Saturday 9 January 2021, 10:27:54</td>\n",
+ " <td id=\"T_15a01_row12_col4\" class=\"data row12 col4\" >Saturday 9 January 2021, 10:27:59</td>\n",
+ " <td id=\"T_15a01_row12_col5\" class=\"data row12 col5\" >00:00:05 249ms</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row13_col0\" class=\"data row13 col0\" ><a href=\"../VAE/01-VAE-with-MNIST.ipynb\">VAE1</a></td>\n",
- " <td id=\"T_8a68a_row13_col1\" class=\"data row13 col1\" >VAE</td>\n",
- " <td id=\"T_8a68a_row13_col2\" class=\"data row13 col2\" ><a href=\"../VAE/01-VAE-with-MNIST.ipynb\"><b>01-VAE-with-MNIST.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row13_col3\" class=\"data row13 col3\" >Thursday 7 January 2021, 09:37:44</td>\n",
- " <td id=\"T_8a68a_row13_col4\" class=\"data row13 col4\" ></td>\n",
- " <td id=\"T_8a68a_row13_col5\" class=\"data row13 col5\" >Unfinished...</td>\n",
+ " <td id=\"T_15a01_row13_col0\" class=\"data row13 col0\" ><a href=\"../VAE/01-VAE-with-MNIST.ipynb\">VAE1</a></td>\n",
+ " <td id=\"T_15a01_row13_col1\" class=\"data row13 col1\" >VAE</td>\n",
+ " <td id=\"T_15a01_row13_col2\" class=\"data row13 col2\" ><a href=\"../VAE/01-VAE-with-MNIST.ipynb\"><b>01-VAE-with-MNIST.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row13_col3\" class=\"data row13 col3\" >Thursday 7 January 2021, 09:37:44</td>\n",
+ " <td id=\"T_15a01_row13_col4\" class=\"data row13 col4\" ></td>\n",
+ " <td id=\"T_15a01_row13_col5\" class=\"data row13 col5\" >Unfinished...</td>\n",
" </tr>\n",
" <tr>\n",
- " <td id=\"T_8a68a_row14_col0\" class=\"data row14 col0\" ><a href=\"../VAE/08-VAE-with-CelebA.ipynb\">VAE8</a></td>\n",
- " <td id=\"T_8a68a_row14_col1\" class=\"data row14 col1\" >VAE</td>\n",
- " <td id=\"T_8a68a_row14_col2\" class=\"data row14 col2\" ><a href=\"../VAE/08-VAE-with-CelebA.ipynb\"><b>08-VAE-with-CelebA.ipynb</b></a></td>\n",
- " <td id=\"T_8a68a_row14_col3\" class=\"data row14 col3\" >Wednesday 6 January 2021, 22:17:12</td>\n",
- " <td id=\"T_8a68a_row14_col4\" class=\"data row14 col4\" ></td>\n",
- " <td id=\"T_8a68a_row14_col5\" class=\"data row14 col5\" >Unfinished...</td>\n",
+ " <td id=\"T_15a01_row14_col0\" class=\"data row14 col0\" ><a href=\"../VAE/08-VAE-with-CelebA.ipynb\">VAE8</a></td>\n",
+ " <td id=\"T_15a01_row14_col1\" class=\"data row14 col1\" >VAE</td>\n",
+ " <td id=\"T_15a01_row14_col2\" class=\"data row14 col2\" ><a href=\"../VAE/08-VAE-with-CelebA.ipynb\"><b>08-VAE-with-CelebA.ipynb</b></a></td>\n",
+ " <td id=\"T_15a01_row14_col3\" class=\"data row14 col3\" >Wednesday 6 January 2021, 22:17:12</td>\n",
+ " <td id=\"T_15a01_row14_col4\" class=\"data row14 col4\" ></td>\n",
+ " <td id=\"T_15a01_row14_col5\" class=\"data row14 col5\" >Unfinished...</td>\n",
" </tr>\n",
" </tbody></table>"
],
"text/plain": [
- "<pandas.io.formats.style.Styler at 0x7f9920e2ded0>"
+ "<pandas.io.formats.style.Styler at 0x7ff03f60f5d0>"
]
},
"metadata": {},
@@ -179,7 +169,8 @@
}
],
"source": [
- "cooker.build_finished_report()"
+ "import cookci\n",
+ "cookci.build_ci_report()"
]
},
{
diff --git a/fidle/ci/default.yml b/fidle/ci/default.yml
index 31d334b8c5bb4e5ea191f4d22c4a8ffc8bba872c..9853a84605bec890afc3aad6509bb74fd358e8cb 100644
--- a/fidle/ci/default.yml
+++ b/fidle/ci/default.yml
@@ -4,7 +4,7 @@ config:
save_figs: true
LINR1:
notebook_dir: LinearReg
- notebook_src: 01-Linear-Regression==ci==.ipynb
+ notebook_src: 01-Linear-Regression.ipynb
notebook_out: default
GRAD1:
notebook_dir: LinearReg
@@ -34,17 +34,9 @@ MNIST1:
notebook_dir: MNIST
notebook_src: 01-DNN-MNIST.ipynb
notebook_out: default
-??:
- notebook_dir: GTSRB
- notebook_src: 00-Test==done==.ipynb
- notebook_out: default
- overrides:
- run_dir: default
- scale: default
- output_dir: default
GTSRB1:
notebook_dir: GTSRB
- notebook_src: 01-Preparation-of-data==ci==.ipynb
+ notebook_src: 01-Preparation-of-data.ipynb
notebook_out: default
overrides:
scale: default
diff --git a/fidle/ci/smart.yml b/fidle/ci/smart.yml
index 57ff0f4adb2a7af93bf81d9dce05cef14fd5fe3c..8f970289e363e3084928180e80b1b438b6eb8849 100644
--- a/fidle/ci/smart.yml
+++ b/fidle/ci/smart.yml
@@ -6,14 +6,6 @@ LINR1:
notebook_dir: LinearReg
notebook_src: 01-Linear-Regression.ipynb
notebook_out: default
-GTSRB0:
- notebook_dir: GTSRB
- notebook_src: 00-Test.ipynb
- notebook_out: default
- overrides:
- scale: 0.7
- output_dir: ./data/foobar
- run_dir: ./run/xxx
GTSRB1:
notebook_dir: GTSRB
notebook_src: 01-Preparation-of-data.ipynb
@@ -30,4 +22,4 @@ GTSRB2:
dataset_name: set-24x24-L
batch_size: 32
epochs: 3
- scale: 1
\ No newline at end of file
+ scale: 0.1
\ No newline at end of file
diff --git a/fidle/config.py b/fidle/config.py
index 5bf592b52f5dff13354236c9181a335fe83907ff..76fb1911443f9c825516adb54694b18fb146dd45 100644
--- a/fidle/config.py
+++ b/fidle/config.py
@@ -32,14 +32,10 @@ SAVE_FIGS = False
# ---- Catalog file, a json description of all notebooks ------------
#
-CATALOG_FILE = '../fidle/log/catalog.json'
+CATALOG_FILE = '../fidle/logs/catalog.json'
-# ---- CI Done files, to keep track of finished notebooks -----------
-# Used for continous integration
+# ---- CI report files ----------------------------------------------
#
-FINISHED_FILE = '../fidle/log/finished.json'
-
-# ---- CI Report ----------------------------------------------------
-#
-FINISHED_REPORT = '../fidle/log/finished_report.html'
+CI_REPORT_JSON = '../fidle/logs/ci_report.json'
+CI_REPORT_HTML = '../fidle/logs/ci_report.html'
diff --git a/fidle/cookci.py b/fidle/cookci.py
new file mode 100644
index 0000000000000000000000000000000000000000..7cc8d22e0f01dc49ac60ff0e17d7fcc69c8d830c
--- /dev/null
+++ b/fidle/cookci.py
@@ -0,0 +1,342 @@
+
+# -----------------------------------------------------------------------------
+# ____ _ ____ _
+# / ___|___ ___ ___| | __ / ___(_)
+# | | / _ \ / _ \ / __| |/ / | | | |
+# | |__| (_) | (_) | (__| < | |___| |
+# \____\___/ \___/ \___|_|\_\ \____|_|
+#
+# Fidle mod for continous integration
+# -----------------------------------------------------------------------------
+#
+# A simple module to run all notebooks with parameters overriding
+# Jean-Luc Parouty 2021
+
+import sys,os
+import json
+import datetime, time
+import nbformat
+from nbconvert.preprocessors import ExecutePreprocessor
+import re
+import yaml
+from collections import OrderedDict
+from IPython.display import display
+import pandas as pd
+
+sys.path.append('..')
+import fidle.config as config
+import fidle.cookindex as cookindex
+
+start_time = None
+end_time = None
+
+def get_ci_profile(catalog=None, output_tag='==done==', save_figs=True):
+ '''
+ Return a profile for continous integration.
+ Ce profile contient une liste des notebooks avec les paramètres modifiables.
+ Il peut être modifié et sauvegardé, puis être utilisé pour lancer l'éxécution
+ des notebooks.
+ params:
+ catalog : Notebooks catalog. if None (default), load config.CATALOG_FILE
+ output_tag : tag name of generated notebook
+ save_figs : save figs or not for generated notebooks (True)
+ return:
+ profile : dict with run parameters
+ '''
+
+ if catalog is None:
+ catalog = cookindex.read_catalog()
+
+ config = {'version':'1.0', 'output_tag':output_tag, 'save_figs':save_figs}
+ profile = { 'config':config }
+ for id, about in catalog.items():
+
+ id = about['id']
+ title = about['title']
+ dirname = about['dirname']
+ basename = about['basename']
+ overrides = about.get('overrides',None)
+
+ notebook = {}
+ notebook['notebook_dir'] = dirname
+ notebook['notebook_src'] = basename
+ notebook['notebook_out'] = 'default'
+ if len(overrides)>0:
+ notebook['overrides']={ name:'default' for name in overrides }
+
+ profile[id]=notebook
+
+ return profile
+
+
+def save_profile(profile, filename):
+ '''Save profile in yaml format'''
+ with open(filename,'wt') as fp:
+ yaml.dump(profile, fp, sort_keys=False)
+ print(f'Catalog saved as {filename}')
+ print('Entries : ',len(profile)-1)
+
+
+def load_profile(filename):
+ '''Load yaml profile'''
+ with open(filename,'r') as fp:
+ profile=yaml.load(fp, Loader=yaml.FullLoader)
+ print(f'{filename} loaded.')
+ print('Entries : ',len(profile)-1)
+ return profile
+
+
+def run_profile(profile, top_dir='..'):
+ '''
+ Récupère la liste des notebooks et des paramètres associés,
+ décrit dans le profile, et pour chaque notebook :
+ Positionner les variables d'environnement pour l'override
+ Charger le notebook
+ Exécuter celui-ci
+ Sauvegarder le notebook résultat, avec son nom taggé.
+ Params:
+ profile : dict, profile d'éxécution
+ top_dir : chemin relatif vers la racine fidle (..)
+ '''
+
+ # ---- My place
+ #
+ home = os.getcwd()
+
+ # ---- Read profile
+ #
+ config = profile['config']
+ notebooks = profile
+ del notebooks['config']
+
+ # ---- Save figs or not ?
+ #
+ os.environ['FIDLE_SAVE_FIGS']=str(config['save_figs'])
+
+ # ---- For each notebook
+ #
+ for id,about in notebooks.items():
+
+ print(f'\nNotebook : {id}')
+
+ # ---- Get notebook infos ---------------------------------------------
+ #
+ notebook_dir = about['notebook_dir']
+ notebook_src = about['notebook_src']
+ notebook_out = about['notebook_out']
+ overrides = about.get('overrides',None)
+
+ # ---- notebook_out (Default)
+ #
+ if notebook_out=='default':
+ notebook_out = notebook_src.replace('.ipynb', config['output_tag']+'.ipynb')
+
+ # ---- Override -------------------------------------------------------
+
+ to_unset=[]
+ if isinstance(overrides,dict):
+ print(' set overrides :')
+ for name,value in overrides.items():
+ # ---- Default : no nothing
+ if value=='default' : continue
+ # ---- Set env
+ env_name = f'FIDLE_OVERRIDE_{id.upper()}_{name}'
+ env_value = str(value)
+ os.environ[env_name] = env_value
+ # ---- For cleaning
+ to_unset.append(env_name)
+ # ---- Fine :(-)
+ print(f' {env_name:38s} = {env_value}')
+
+ # ---- Run it ! -------------------------------------------------------
+
+ # ---- Go to the right place
+ #
+ os.chdir(f'{top_dir}/{notebook_dir}')
+ notebook = nbformat.read( f'{notebook_src}', nbformat.NO_CONVERT)
+
+ # ---- Top chrono
+ #
+ chrono_start()
+ update_ci_report(id, start=True)
+
+ # ---- Run, run, run...
+ #
+ print(' Run notebook...',end='')
+ ep = ExecutePreprocessor(timeout=600, kernel_name="python3")
+ ep.preprocess(notebook)
+ print('..done.')
+
+ # ---- Top chrono
+ #
+ chrono_stop()
+ update_ci_report(id, end=True)
+ print(' Duration : ',chrono_delay() )
+
+ # ---- Save notebook
+ #
+ with open( f'{notebook_out}', mode="w", encoding='utf-8') as fp:
+ nbformat.write(notebook, fp)
+ print(' Saved as : ',notebook_out)
+
+ # ---- Back to home and clean
+ #
+ os.chdir(home)
+ for env_name in to_unset:
+ del os.environ[env_name]
+
+
+def chrono_start():
+ global start_time
+ start_time = datetime.datetime.now()
+
+def chrono_stop():
+ global end_time
+ end_time = datetime.datetime.now()
+
+def chrono_delay(in_seconds=False):
+ global start_time, end_time
+ delta = end_time - start_time
+ if in_seconds:
+ return round(delta.total_seconds(),2)
+ else:
+ delta = delta - datetime.timedelta(microseconds=delta.microseconds)
+ return str(delta)
+
+
+
+def reset_ci_report(verbose=True):
+ data={}
+ with open(config.CI_REPORT_JSON,'wt') as fp:
+ json.dump(data,fp,indent=4)
+ if verbose : print(f'Finished file has been reset.\n')
+
+
+def update_ci_report(notebook_id, start=False, end=False):
+ global start_time, end_time
+
+ if not os.access(config.CI_REPORT_JSON, os.W_OK):
+ reset_ci_report(verbose=True)
+
+ # ---- Load it
+ with open(config.CI_REPORT_JSON) as fp:
+ data = json.load(fp)
+
+ # ---- Update as a start
+ if start is True:
+ data[notebook_id] = {}
+ data[notebook_id]['path'] = os.getcwd()
+ data[notebook_id]['start'] = start_time.strftime("%A %-d %B %Y, %H:%M:%S")
+ data[notebook_id]['end'] = ''
+ data[notebook_id]['duration'] = 'Unfinished...'
+
+ # ---- Update as an end
+ if end is True:
+ data[notebook_id]['end'] = end_time.strftime("%A %-d %B %Y, %H:%M:%S")
+ data[notebook_id]['duration'] = chrono_delay()
+
+ # ---- Save it
+ with open(config.CI_REPORT_JSON,'wt') as fp:
+ json.dump(data,fp,indent=4)
+
+
+
+def build_ci_report(display_output=True, save_html=True):
+
+ # ---- Load catalog (notebooks descriptions)
+ #
+ with open(config.CATALOG_FILE) as fp:
+ catalog = json.load(fp)
+
+ # ---- Load ci report
+ #
+ with open(config.CI_REPORT_JSON) as infile:
+ ci_report = json.load( infile )
+
+ # ---- For each entry
+ #
+ col_id, col_repo, col_name, col_start, col_end, col_dur = [],[],[],[],[],[]
+ for id,about in catalog.items():
+ if id in ci_report.keys():
+ ci_entry = ci_report[id]
+ dirname = about['dirname']
+ basename = about['basename']
+
+ col_id.append( f'<a href="../{dirname}/{basename}">{id}</a>' )
+ col_repo.append( dirname )
+ col_name.append( f'<a href="../{dirname}/{basename}"><b>{basename}</b></a>' )
+ col_start.append( ci_entry['start'] )
+ col_end.append( ci_entry['end'] )
+ col_dur.append( ci_entry['duration'] )
+
+ df = pd.DataFrame( {'id':col_id, 'Repo':col_repo, 'Name':col_name, 'Start':col_start, 'End':col_end, 'Duration':col_dur} )
+
+ # ---- Add styles to be nice
+ #
+ styles = [
+ dict(selector="td", props=[("font-size", "110%"), ("text-align", "left")]),
+ dict(selector="th", props=[("font-size", "110%"), ("text-align", "left")])
+ ]
+ def still_pending(v):
+ return 'background-color: OrangeRed; color:white' if v == 'Unfinished...' else ''
+
+ output = df[df.columns.values].style.set_table_styles(styles).hide_index().applymap(still_pending)
+
+ # ---- html report
+ #
+ if save_html:
+ html = _get_html_report(output)
+ with open(config.CI_REPORT_HTML, "wt") as fp:
+ fp.write(html)
+
+ # ---- display output
+ #
+ if display_output:
+ display(output)
+
+
+
+
+def _get_html_report(output):
+ with open('./img/00-Fidle-logo-01-80px.svg','r') as fp:
+ logo = fp.read()
+
+ now = datetime.datetime.now().strftime("%A %-d %B %Y, %H:%M:%S")
+ html = f"""\
+ <html>
+ <head><title>FIDLE - CI Report</title></head>
+ <style>
+ body{{
+ font-family: sans-serif;
+ }}
+ a{{
+ color: SteelBlue;
+ text-decoration:none;
+ }}
+ table{{
+ border-collapse : collapse;
+ font-size : 80%
+ }}
+ td{{
+ border-style: solid;
+ border-width: thin;
+ border-color: lightgrey;
+ padding: 5px;
+ }}
+ .header{{ padding:20px 0px 0px 30px; }}
+ .result{{ padding:10px 0px 20px 30px; }}
+ </style>
+ <body>
+ <br>Hi,
+ <p>Below is the result of the continuous integration tests of the Fidle project:</p>
+ <div class="header"><b>Report date :</b> {now}</div>
+ <div class="result">
+ {output.render()}
+ </div>
+
+ {logo}
+
+ </body>
+ </html>
+ """
+ return html
\ No newline at end of file
diff --git a/fidle/cooker.py b/fidle/cookindex.py
similarity index 58%
rename from fidle/cooker.py
rename to fidle/cookindex.py
index e634cfb6d0c9d565529195129160780fdf1eea36..4e71a444ad16c9992d03d15ab9982ef611715858 100644
--- a/fidle/cooker.py
+++ b/fidle/cookindex.py
@@ -1,14 +1,17 @@
# -----------------------------------------------------------------------------
-# ____ _ _ ____ _ _ _
-# / ___|__ _| |_ __ _| | ___ __ _ | __ ) _ _(_) | __| | ___ _ __
-# | | / _` | __/ _` | |/ _ \ / _` | | _ \| | | | | |/ _` |/ _ \ '__|
-# | |__| (_| | || (_| | | (_) | (_| | | |_) | |_| | | | (_| | __/ |
-# \____\__,_|\__\__,_|_|\___/ \__, | |____/ \__,_|_|_|\__,_|\___|_|
-# |___/ Module catalog_builder
+# ____ _ ___ _
+# / ___|___ ___ ___| | __ |_ _|_ __ __| | _____ __
+# | | / _ \ / _ \ / __| |/ / | || '_ \ / _` |/ _ \ \/ /
+# | |__| (_) | (_) | (__| < | || | | | (_| | __/> <
+# \____\___/ \___/ \___|_|\_\ |___|_| |_|\__,_|\___/_/\_\
+#
+# Fidle mod for index cooking
# -----------------------------------------------------------------------------
#
# A simple module to build the notebook catalog and update the README.
+# Jean-Luc Parouty 2021
+
import nbformat
from nbconvert.preprocessors import ExecutePreprocessor
@@ -190,109 +193,3 @@ def read_catalog():
catalog = json.load(fp)
return catalog
-# -----------------------------------------------------------------------------
-# To built : CI Report
-# -----------------------------------------------------------------------------
-# get_ci_report : Get report of finished files
-# -----------------------------------------------------------------------------
-
-
-def build_finished_report(display_output=True, save_html=True):
-
- # ---- Load catalog (notebooks descriptions)
- #
- with open(config.CATALOG_FILE) as fp:
- catalog = json.load(fp)
-
- # ---- Load finished file
- #
- with open(config.FINISHED_FILE) as infile:
- finished_files = json.load( infile )
-
- # ---- For each entry
- #
- col_id, col_repo, col_name, col_start, col_end, col_dur = [],[],[],[],[],[]
- for id,about in catalog.items():
- if id in finished_files.keys():
- finished = finished_files[id]
- dirname = about['dirname']
- basename = about['basename']
-
- col_id.append( f'<a href="../{dirname}/{basename}">{id}</a>' )
- col_repo.append( dirname )
- col_name.append( f'<a href="../{dirname}/{basename}"><b>{basename}</b></a>' )
- col_start.append( finished['start'] )
- col_end.append( finished['end'] )
- col_dur.append( finished['duration'] )
-
- df = pd.DataFrame( {'id':col_id, 'Repo':col_repo, 'Name':col_name, 'Start':col_start, 'End':col_end, 'Duration':col_dur} )
-
- # ---- Add styles to be nice
- #
- styles = [
- dict(selector="td", props=[("font-size", "110%"), ("text-align", "left")]),
- dict(selector="th", props=[("font-size", "110%"), ("text-align", "left")])
- ]
- def still_pending(v):
- return 'background-color: OrangeRed; color:white' if v == 'Unfinished...' else ''
-
- output = df[df.columns.values].style.set_table_styles(styles).hide_index().applymap(still_pending)
-
- # ---- html report
- #
- if save_html:
- html = _get_html_report(output)
- with open(config.FINISHED_REPORT, "wt") as fp:
- fp.write(html)
-
- # ---- display output
- #
- if display_output:
- display(output)
-
-
-
-
-def _get_html_report(output):
- with open('./img/00-Fidle-logo-01-80px.svg','r') as fp:
- logo = fp.read()
-
- now = datetime.now().strftime("%A %-d %B %Y, %H:%M:%S")
- html = f"""\
- <html>
- <head><title>FIDLE - CI Report</title></head>
- <style>
- body{{
- font-family: sans-serif;
- }}
- a{{
- color: SteelBlue;
- text-decoration:none;
- }}
- table{{
- border-collapse : collapse;
- font-size : 80%
- }}
- td{{
- border-style: solid;
- border-width: thin;
- border-color: lightgrey;
- padding: 5px;
- }}
- .header{{ padding:20px 0px 0px 30px; }}
- .result{{ padding:10px 0px 20px 30px; }}
- </style>
- <body>
- <br>Hi,
- <p>Below is the result of the continuous integration tests of the Fidle project:</p>
- <div class="header"><b>Report date :</b> {now}</div>
- <div class="result">
- {output.render()}
- </div>
-
- {logo}
-
- </body>
- </html>
- """
- return html
\ No newline at end of file
diff --git a/fidle/log/catalog.json b/fidle/logs/catalog.json
similarity index 97%
rename from fidle/log/catalog.json
rename to fidle/logs/catalog.json
index 95b1e63865209aa908ebd0f49a8be390ac6b655d..e4712bc924675e76d2f4aed2cbadfb268a6e3396 100644
--- a/fidle/log/catalog.json
+++ b/fidle/logs/catalog.json
@@ -63,18 +63,6 @@
"description": "An example of classification using a dense neural network for the famous MNIST dataset",
"overrides": []
},
- "??": {
- "id": "??",
- "dirname": "GTSRB",
- "basename": "00-Test.ipynb",
- "title": "??",
- "description": "??",
- "overrides": [
- "run_dir",
- "scale",
- "output_dir"
- ]
- },
"GTSRB1": {
"id": "GTSRB1",
"dirname": "GTSRB",
diff --git a/fidle/log/finished_report.html b/fidle/logs/ci_report.html
similarity index 59%
rename from fidle/log/finished_report.html
rename to fidle/logs/ci_report.html
index e5a4bf309920b500dd43cde5e83e062a9486d900..374544b2c422fb1ea75e6e151f0f33f2188c677f 100644
--- a/fidle/log/finished_report.html
+++ b/fidle/logs/ci_report.html
@@ -24,138 +24,138 @@
<body>
<br>Hi,
<p>Below is the result of the continuous integration tests of the Fidle project:</p>
- <div class="header"><b>Report date :</b> Saturday 9 January 2021, 22:56:56</div>
+ <div class="header"><b>Report date :</b> Sunday 10 January 2021, 22:58:46</div>
<div class="result">
<style type="text/css" >
- #T_8a68a_ td {
+ #T_15a01_ td {
font-size: 110%;
text-align: left;
- } #T_8a68a_ th {
+ } #T_15a01_ th {
font-size: 110%;
text-align: left;
- }#T_8a68a_row13_col5,#T_8a68a_row14_col5{
+ }#T_15a01_row4_col5,#T_15a01_row13_col5,#T_15a01_row14_col5{
background-color: OrangeRed;
color: white;
- }</style><table id="T_8a68a_" ><thead> <tr> <th class="col_heading level0 col0" >id</th> <th class="col_heading level0 col1" >Repo</th> <th class="col_heading level0 col2" >Name</th> <th class="col_heading level0 col3" >Start</th> <th class="col_heading level0 col4" >End</th> <th class="col_heading level0 col5" >Duration</th> </tr></thead><tbody>
+ }</style><table id="T_15a01_" ><thead> <tr> <th class="col_heading level0 col0" >id</th> <th class="col_heading level0 col1" >Repo</th> <th class="col_heading level0 col2" >Name</th> <th class="col_heading level0 col3" >Start</th> <th class="col_heading level0 col4" >End</th> <th class="col_heading level0 col5" >Duration</th> </tr></thead><tbody>
<tr>
- <td id="T_8a68a_row0_col0" class="data row0 col0" ><a href="../LinearReg/01-Linear-Regression.ipynb">LINR1</a></td>
- <td id="T_8a68a_row0_col1" class="data row0 col1" >LinearReg</td>
- <td id="T_8a68a_row0_col2" class="data row0 col2" ><a href="../LinearReg/01-Linear-Regression.ipynb"><b>01-Linear-Regression.ipynb</b></a></td>
- <td id="T_8a68a_row0_col3" class="data row0 col3" >Saturday 9 January 2021, 19:34:10</td>
- <td id="T_8a68a_row0_col4" class="data row0 col4" >Saturday 9 January 2021, 19:34:11</td>
- <td id="T_8a68a_row0_col5" class="data row0 col5" >00:00:01 667ms</td>
+ <td id="T_15a01_row0_col0" class="data row0 col0" ><a href="../LinearReg/01-Linear-Regression.ipynb">LINR1</a></td>
+ <td id="T_15a01_row0_col1" class="data row0 col1" >LinearReg</td>
+ <td id="T_15a01_row0_col2" class="data row0 col2" ><a href="../LinearReg/01-Linear-Regression.ipynb"><b>01-Linear-Regression.ipynb</b></a></td>
+ <td id="T_15a01_row0_col3" class="data row0 col3" >Sunday 10 January 2021, 22:54:49</td>
+ <td id="T_15a01_row0_col4" class="data row0 col4" >Sunday 10 January 2021, 22:54:53</td>
+ <td id="T_15a01_row0_col5" class="data row0 col5" >0:00:04</td>
</tr>
<tr>
- <td id="T_8a68a_row1_col0" class="data row1 col0" ><a href="../BHPD/01-DNN-Regression.ipynb">BHPD1</a></td>
- <td id="T_8a68a_row1_col1" class="data row1 col1" >BHPD</td>
- <td id="T_8a68a_row1_col2" class="data row1 col2" ><a href="../BHPD/01-DNN-Regression.ipynb"><b>01-DNN-Regression.ipynb</b></a></td>
- <td id="T_8a68a_row1_col3" class="data row1 col3" >Friday 8 January 2021, 01:09:13</td>
- <td id="T_8a68a_row1_col4" class="data row1 col4" >Friday 8 January 2021, 01:09:24</td>
- <td id="T_8a68a_row1_col5" class="data row1 col5" >00:00:11 984ms</td>
+ <td id="T_15a01_row1_col0" class="data row1 col0" ><a href="../BHPD/01-DNN-Regression.ipynb">BHPD1</a></td>
+ <td id="T_15a01_row1_col1" class="data row1 col1" >BHPD</td>
+ <td id="T_15a01_row1_col2" class="data row1 col2" ><a href="../BHPD/01-DNN-Regression.ipynb"><b>01-DNN-Regression.ipynb</b></a></td>
+ <td id="T_15a01_row1_col3" class="data row1 col3" >Friday 8 January 2021, 01:09:13</td>
+ <td id="T_15a01_row1_col4" class="data row1 col4" >Friday 8 January 2021, 01:09:24</td>
+ <td id="T_15a01_row1_col5" class="data row1 col5" >00:00:11 984ms</td>
</tr>
<tr>
- <td id="T_8a68a_row2_col0" class="data row2 col0" ><a href="../BHPD/02-DNN-Regression-Premium.ipynb">BHPD2</a></td>
- <td id="T_8a68a_row2_col1" class="data row2 col1" >BHPD</td>
- <td id="T_8a68a_row2_col2" class="data row2 col2" ><a href="../BHPD/02-DNN-Regression-Premium.ipynb"><b>02-DNN-Regression-Premium.ipynb</b></a></td>
- <td id="T_8a68a_row2_col3" class="data row2 col3" >Friday 8 January 2021, 01:10:28</td>
- <td id="T_8a68a_row2_col4" class="data row2 col4" >Friday 8 January 2021, 01:10:39</td>
- <td id="T_8a68a_row2_col5" class="data row2 col5" >00:00:12 582ms</td>
+ <td id="T_15a01_row2_col0" class="data row2 col0" ><a href="../BHPD/02-DNN-Regression-Premium.ipynb">BHPD2</a></td>
+ <td id="T_15a01_row2_col1" class="data row2 col1" >BHPD</td>
+ <td id="T_15a01_row2_col2" class="data row2 col2" ><a href="../BHPD/02-DNN-Regression-Premium.ipynb"><b>02-DNN-Regression-Premium.ipynb</b></a></td>
+ <td id="T_15a01_row2_col3" class="data row2 col3" >Friday 8 January 2021, 01:10:28</td>
+ <td id="T_15a01_row2_col4" class="data row2 col4" >Friday 8 January 2021, 01:10:39</td>
+ <td id="T_15a01_row2_col5" class="data row2 col5" >00:00:12 582ms</td>
</tr>
<tr>
- <td id="T_8a68a_row3_col0" class="data row3 col0" ><a href="../GTSRB/01-Preparation-of-data.ipynb">GTSRB1</a></td>
- <td id="T_8a68a_row3_col1" class="data row3 col1" >GTSRB</td>
- <td id="T_8a68a_row3_col2" class="data row3 col2" ><a href="../GTSRB/01-Preparation-of-data.ipynb"><b>01-Preparation-of-data.ipynb</b></a></td>
- <td id="T_8a68a_row3_col3" class="data row3 col3" >Saturday 9 January 2021, 19:34:16</td>
- <td id="T_8a68a_row3_col4" class="data row3 col4" >Saturday 9 January 2021, 19:36:14</td>
- <td id="T_8a68a_row3_col5" class="data row3 col5" >00:01:58 919ms</td>
+ <td id="T_15a01_row3_col0" class="data row3 col0" ><a href="../GTSRB/01-Preparation-of-data.ipynb">GTSRB1</a></td>
+ <td id="T_15a01_row3_col1" class="data row3 col1" >GTSRB</td>
+ <td id="T_15a01_row3_col2" class="data row3 col2" ><a href="../GTSRB/01-Preparation-of-data.ipynb"><b>01-Preparation-of-data.ipynb</b></a></td>
+ <td id="T_15a01_row3_col3" class="data row3 col3" >Sunday 10 January 2021, 22:54:53</td>
+ <td id="T_15a01_row3_col4" class="data row3 col4" >Sunday 10 January 2021, 22:56:54</td>
+ <td id="T_15a01_row3_col5" class="data row3 col5" >0:02:00</td>
</tr>
<tr>
- <td id="T_8a68a_row4_col0" class="data row4 col0" ><a href="../GTSRB/02-First-convolutions.ipynb">GTSRB2</a></td>
- <td id="T_8a68a_row4_col1" class="data row4 col1" >GTSRB</td>
- <td id="T_8a68a_row4_col2" class="data row4 col2" ><a href="../GTSRB/02-First-convolutions.ipynb"><b>02-First-convolutions.ipynb</b></a></td>
- <td id="T_8a68a_row4_col3" class="data row4 col3" >Saturday 9 January 2021, 19:36:17</td>
- <td id="T_8a68a_row4_col4" class="data row4 col4" >Saturday 9 January 2021, 19:39:16</td>
- <td id="T_8a68a_row4_col5" class="data row4 col5" >00:02:59 895ms</td>
+ <td id="T_15a01_row4_col0" class="data row4 col0" ><a href="../GTSRB/02-First-convolutions.ipynb">GTSRB2</a></td>
+ <td id="T_15a01_row4_col1" class="data row4 col1" >GTSRB</td>
+ <td id="T_15a01_row4_col2" class="data row4 col2" ><a href="../GTSRB/02-First-convolutions.ipynb"><b>02-First-convolutions.ipynb</b></a></td>
+ <td id="T_15a01_row4_col3" class="data row4 col3" >Sunday 10 January 2021, 22:56:54</td>
+ <td id="T_15a01_row4_col4" class="data row4 col4" ></td>
+ <td id="T_15a01_row4_col5" class="data row4 col5" >Unfinished...</td>
</tr>
<tr>
- <td id="T_8a68a_row5_col0" class="data row5 col0" ><a href="../GTSRB/03-Tracking-and-visualizing.ipynb">GTSRB3</a></td>
- <td id="T_8a68a_row5_col1" class="data row5 col1" >GTSRB</td>
- <td id="T_8a68a_row5_col2" class="data row5 col2" ><a href="../GTSRB/03-Tracking-and-visualizing.ipynb"><b>03-Tracking-and-visualizing.ipynb</b></a></td>
- <td id="T_8a68a_row5_col3" class="data row5 col3" >Thursday 7 January 2021, 12:15:52</td>
- <td id="T_8a68a_row5_col4" class="data row5 col4" >Thursday 7 January 2021, 12:20:01</td>
- <td id="T_8a68a_row5_col5" class="data row5 col5" >00:04:09 711ms</td>
+ <td id="T_15a01_row5_col0" class="data row5 col0" ><a href="../GTSRB/03-Tracking-and-visualizing.ipynb">GTSRB3</a></td>
+ <td id="T_15a01_row5_col1" class="data row5 col1" >GTSRB</td>
+ <td id="T_15a01_row5_col2" class="data row5 col2" ><a href="../GTSRB/03-Tracking-and-visualizing.ipynb"><b>03-Tracking-and-visualizing.ipynb</b></a></td>
+ <td id="T_15a01_row5_col3" class="data row5 col3" >Thursday 7 January 2021, 12:15:52</td>
+ <td id="T_15a01_row5_col4" class="data row5 col4" >Thursday 7 January 2021, 12:20:01</td>
+ <td id="T_15a01_row5_col5" class="data row5 col5" >00:04:09 711ms</td>
</tr>
<tr>
- <td id="T_8a68a_row6_col0" class="data row6 col0" ><a href="../GTSRB/04-Data-augmentation.ipynb">GTSRB4</a></td>
- <td id="T_8a68a_row6_col1" class="data row6 col1" >GTSRB</td>
- <td id="T_8a68a_row6_col2" class="data row6 col2" ><a href="../GTSRB/04-Data-augmentation.ipynb"><b>04-Data-augmentation.ipynb</b></a></td>
- <td id="T_8a68a_row6_col3" class="data row6 col3" >Thursday 7 January 2021, 13:40:52</td>
- <td id="T_8a68a_row6_col4" class="data row6 col4" >Thursday 7 January 2021, 13:41:31</td>
- <td id="T_8a68a_row6_col5" class="data row6 col5" >00:00:39 161ms</td>
+ <td id="T_15a01_row6_col0" class="data row6 col0" ><a href="../GTSRB/04-Data-augmentation.ipynb">GTSRB4</a></td>
+ <td id="T_15a01_row6_col1" class="data row6 col1" >GTSRB</td>
+ <td id="T_15a01_row6_col2" class="data row6 col2" ><a href="../GTSRB/04-Data-augmentation.ipynb"><b>04-Data-augmentation.ipynb</b></a></td>
+ <td id="T_15a01_row6_col3" class="data row6 col3" >Thursday 7 January 2021, 13:40:52</td>
+ <td id="T_15a01_row6_col4" class="data row6 col4" >Thursday 7 January 2021, 13:41:31</td>
+ <td id="T_15a01_row6_col5" class="data row6 col5" >00:00:39 161ms</td>
</tr>
<tr>
- <td id="T_8a68a_row7_col0" class="data row7 col0" ><a href="../GTSRB/05-Full-convolutions.ipynb">GTSRB5</a></td>
- <td id="T_8a68a_row7_col1" class="data row7 col1" >GTSRB</td>
- <td id="T_8a68a_row7_col2" class="data row7 col2" ><a href="../GTSRB/05-Full-convolutions.ipynb"><b>05-Full-convolutions.ipynb</b></a></td>
- <td id="T_8a68a_row7_col3" class="data row7 col3" >Thursday 7 January 2021, 14:47:12</td>
- <td id="T_8a68a_row7_col4" class="data row7 col4" >Thursday 7 January 2021, 14:48:44</td>
- <td id="T_8a68a_row7_col5" class="data row7 col5" >00:01:32 269ms</td>
+ <td id="T_15a01_row7_col0" class="data row7 col0" ><a href="../GTSRB/05-Full-convolutions.ipynb">GTSRB5</a></td>
+ <td id="T_15a01_row7_col1" class="data row7 col1" >GTSRB</td>
+ <td id="T_15a01_row7_col2" class="data row7 col2" ><a href="../GTSRB/05-Full-convolutions.ipynb"><b>05-Full-convolutions.ipynb</b></a></td>
+ <td id="T_15a01_row7_col3" class="data row7 col3" >Thursday 7 January 2021, 14:47:12</td>
+ <td id="T_15a01_row7_col4" class="data row7 col4" >Thursday 7 January 2021, 14:48:44</td>
+ <td id="T_15a01_row7_col5" class="data row7 col5" >00:01:32 269ms</td>
</tr>
<tr>
- <td id="T_8a68a_row8_col0" class="data row8 col0" ><a href="../GTSRB/06-Notebook-as-a-batch.ipynb">GTSRB6</a></td>
- <td id="T_8a68a_row8_col1" class="data row8 col1" >GTSRB</td>
- <td id="T_8a68a_row8_col2" class="data row8 col2" ><a href="../GTSRB/06-Notebook-as-a-batch.ipynb"><b>06-Notebook-as-a-batch.ipynb</b></a></td>
- <td id="T_8a68a_row8_col3" class="data row8 col3" >Thursday 7 January 2021, 15:41:17</td>
- <td id="T_8a68a_row8_col4" class="data row8 col4" >Thursday 7 January 2021, 15:41:18</td>
- <td id="T_8a68a_row8_col5" class="data row8 col5" >00:00:01 101ms</td>
+ <td id="T_15a01_row8_col0" class="data row8 col0" ><a href="../GTSRB/06-Notebook-as-a-batch.ipynb">GTSRB6</a></td>
+ <td id="T_15a01_row8_col1" class="data row8 col1" >GTSRB</td>
+ <td id="T_15a01_row8_col2" class="data row8 col2" ><a href="../GTSRB/06-Notebook-as-a-batch.ipynb"><b>06-Notebook-as-a-batch.ipynb</b></a></td>
+ <td id="T_15a01_row8_col3" class="data row8 col3" >Thursday 7 January 2021, 15:41:17</td>
+ <td id="T_15a01_row8_col4" class="data row8 col4" >Thursday 7 January 2021, 15:41:18</td>
+ <td id="T_15a01_row8_col5" class="data row8 col5" >00:00:01 101ms</td>
</tr>
<tr>
- <td id="T_8a68a_row9_col0" class="data row9 col0" ><a href="../GTSRB/07-Show-report.ipynb">GTSRB7</a></td>
- <td id="T_8a68a_row9_col1" class="data row9 col1" >GTSRB</td>
- <td id="T_8a68a_row9_col2" class="data row9 col2" ><a href="../GTSRB/07-Show-report.ipynb"><b>07-Show-report.ipynb</b></a></td>
- <td id="T_8a68a_row9_col3" class="data row9 col3" >Thursday 7 January 2021, 15:16:05</td>
- <td id="T_8a68a_row9_col4" class="data row9 col4" >Thursday 7 January 2021, 15:16:06</td>
- <td id="T_8a68a_row9_col5" class="data row9 col5" >00:00:00 116ms</td>
+ <td id="T_15a01_row9_col0" class="data row9 col0" ><a href="../GTSRB/07-Show-report.ipynb">GTSRB7</a></td>
+ <td id="T_15a01_row9_col1" class="data row9 col1" >GTSRB</td>
+ <td id="T_15a01_row9_col2" class="data row9 col2" ><a href="../GTSRB/07-Show-report.ipynb"><b>07-Show-report.ipynb</b></a></td>
+ <td id="T_15a01_row9_col3" class="data row9 col3" >Thursday 7 January 2021, 15:16:05</td>
+ <td id="T_15a01_row9_col4" class="data row9 col4" >Thursday 7 January 2021, 15:16:06</td>
+ <td id="T_15a01_row9_col5" class="data row9 col5" >00:00:00 116ms</td>
</tr>
<tr>
- <td id="T_8a68a_row10_col0" class="data row10 col0" ><a href="../SYNOP/01-Preparation-of-data.ipynb">SYNOP1</a></td>
- <td id="T_8a68a_row10_col1" class="data row10 col1" >SYNOP</td>
- <td id="T_8a68a_row10_col2" class="data row10 col2" ><a href="../SYNOP/01-Preparation-of-data.ipynb"><b>01-Preparation-of-data.ipynb</b></a></td>
- <td id="T_8a68a_row10_col3" class="data row10 col3" >Saturday 9 January 2021, 10:04:28</td>
- <td id="T_8a68a_row10_col4" class="data row10 col4" >Saturday 9 January 2021, 10:04:34</td>
- <td id="T_8a68a_row10_col5" class="data row10 col5" >00:00:05 236ms</td>
+ <td id="T_15a01_row10_col0" class="data row10 col0" ><a href="../SYNOP/01-Preparation-of-data.ipynb">SYNOP1</a></td>
+ <td id="T_15a01_row10_col1" class="data row10 col1" >SYNOP</td>
+ <td id="T_15a01_row10_col2" class="data row10 col2" ><a href="../SYNOP/01-Preparation-of-data.ipynb"><b>01-Preparation-of-data.ipynb</b></a></td>
+ <td id="T_15a01_row10_col3" class="data row10 col3" >Saturday 9 January 2021, 10:04:28</td>
+ <td id="T_15a01_row10_col4" class="data row10 col4" >Saturday 9 January 2021, 10:04:34</td>
+ <td id="T_15a01_row10_col5" class="data row10 col5" >00:00:05 236ms</td>
</tr>
<tr>
- <td id="T_8a68a_row11_col0" class="data row11 col0" ><a href="../SYNOP/02-First-predictions.ipynb">SYNOP2</a></td>
- <td id="T_8a68a_row11_col1" class="data row11 col1" >SYNOP</td>
- <td id="T_8a68a_row11_col2" class="data row11 col2" ><a href="../SYNOP/02-First-predictions.ipynb"><b>02-First-predictions.ipynb</b></a></td>
- <td id="T_8a68a_row11_col3" class="data row11 col3" >Saturday 9 January 2021, 10:30:55</td>
- <td id="T_8a68a_row11_col4" class="data row11 col4" >Saturday 9 January 2021, 10:31:11</td>
- <td id="T_8a68a_row11_col5" class="data row11 col5" >00:00:16 248ms</td>
+ <td id="T_15a01_row11_col0" class="data row11 col0" ><a href="../SYNOP/02-First-predictions.ipynb">SYNOP2</a></td>
+ <td id="T_15a01_row11_col1" class="data row11 col1" >SYNOP</td>
+ <td id="T_15a01_row11_col2" class="data row11 col2" ><a href="../SYNOP/02-First-predictions.ipynb"><b>02-First-predictions.ipynb</b></a></td>
+ <td id="T_15a01_row11_col3" class="data row11 col3" >Saturday 9 January 2021, 10:30:55</td>
+ <td id="T_15a01_row11_col4" class="data row11 col4" >Saturday 9 January 2021, 10:31:11</td>
+ <td id="T_15a01_row11_col5" class="data row11 col5" >00:00:16 248ms</td>
</tr>
<tr>
- <td id="T_8a68a_row12_col0" class="data row12 col0" ><a href="../SYNOP/03-12h-predictions.ipynb">SYNOP3</a></td>
- <td id="T_8a68a_row12_col1" class="data row12 col1" >SYNOP</td>
- <td id="T_8a68a_row12_col2" class="data row12 col2" ><a href="../SYNOP/03-12h-predictions.ipynb"><b>03-12h-predictions.ipynb</b></a></td>
- <td id="T_8a68a_row12_col3" class="data row12 col3" >Saturday 9 January 2021, 10:27:54</td>
- <td id="T_8a68a_row12_col4" class="data row12 col4" >Saturday 9 January 2021, 10:27:59</td>
- <td id="T_8a68a_row12_col5" class="data row12 col5" >00:00:05 249ms</td>
+ <td id="T_15a01_row12_col0" class="data row12 col0" ><a href="../SYNOP/03-12h-predictions.ipynb">SYNOP3</a></td>
+ <td id="T_15a01_row12_col1" class="data row12 col1" >SYNOP</td>
+ <td id="T_15a01_row12_col2" class="data row12 col2" ><a href="../SYNOP/03-12h-predictions.ipynb"><b>03-12h-predictions.ipynb</b></a></td>
+ <td id="T_15a01_row12_col3" class="data row12 col3" >Saturday 9 January 2021, 10:27:54</td>
+ <td id="T_15a01_row12_col4" class="data row12 col4" >Saturday 9 January 2021, 10:27:59</td>
+ <td id="T_15a01_row12_col5" class="data row12 col5" >00:00:05 249ms</td>
</tr>
<tr>
- <td id="T_8a68a_row13_col0" class="data row13 col0" ><a href="../VAE/01-VAE-with-MNIST.ipynb">VAE1</a></td>
- <td id="T_8a68a_row13_col1" class="data row13 col1" >VAE</td>
- <td id="T_8a68a_row13_col2" class="data row13 col2" ><a href="../VAE/01-VAE-with-MNIST.ipynb"><b>01-VAE-with-MNIST.ipynb</b></a></td>
- <td id="T_8a68a_row13_col3" class="data row13 col3" >Thursday 7 January 2021, 09:37:44</td>
- <td id="T_8a68a_row13_col4" class="data row13 col4" ></td>
- <td id="T_8a68a_row13_col5" class="data row13 col5" >Unfinished...</td>
+ <td id="T_15a01_row13_col0" class="data row13 col0" ><a href="../VAE/01-VAE-with-MNIST.ipynb">VAE1</a></td>
+ <td id="T_15a01_row13_col1" class="data row13 col1" >VAE</td>
+ <td id="T_15a01_row13_col2" class="data row13 col2" ><a href="../VAE/01-VAE-with-MNIST.ipynb"><b>01-VAE-with-MNIST.ipynb</b></a></td>
+ <td id="T_15a01_row13_col3" class="data row13 col3" >Thursday 7 January 2021, 09:37:44</td>
+ <td id="T_15a01_row13_col4" class="data row13 col4" ></td>
+ <td id="T_15a01_row13_col5" class="data row13 col5" >Unfinished...</td>
</tr>
<tr>
- <td id="T_8a68a_row14_col0" class="data row14 col0" ><a href="../VAE/08-VAE-with-CelebA.ipynb">VAE8</a></td>
- <td id="T_8a68a_row14_col1" class="data row14 col1" >VAE</td>
- <td id="T_8a68a_row14_col2" class="data row14 col2" ><a href="../VAE/08-VAE-with-CelebA.ipynb"><b>08-VAE-with-CelebA.ipynb</b></a></td>
- <td id="T_8a68a_row14_col3" class="data row14 col3" >Wednesday 6 January 2021, 22:17:12</td>
- <td id="T_8a68a_row14_col4" class="data row14 col4" ></td>
- <td id="T_8a68a_row14_col5" class="data row14 col5" >Unfinished...</td>
+ <td id="T_15a01_row14_col0" class="data row14 col0" ><a href="../VAE/08-VAE-with-CelebA.ipynb">VAE8</a></td>
+ <td id="T_15a01_row14_col1" class="data row14 col1" >VAE</td>
+ <td id="T_15a01_row14_col2" class="data row14 col2" ><a href="../VAE/08-VAE-with-CelebA.ipynb"><b>08-VAE-with-CelebA.ipynb</b></a></td>
+ <td id="T_15a01_row14_col3" class="data row14 col3" >Wednesday 6 January 2021, 22:17:12</td>
+ <td id="T_15a01_row14_col4" class="data row14 col4" ></td>
+ <td id="T_15a01_row14_col5" class="data row14 col5" >Unfinished...</td>
</tr>
</tbody></table>
</div>
diff --git a/fidle/logs/ci_report.json b/fidle/logs/ci_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..933e2a7684a6c5cc17d9c834e897553d225830eb
--- /dev/null
+++ b/fidle/logs/ci_report.json
@@ -0,0 +1,98 @@
+{
+ "VAE8": {
+ "path": "/home/pjluc/dev/fidle/VAE",
+ "start": "Wednesday 6 January 2021, 22:17:12",
+ "end": "",
+ "duration": "Unfinished..."
+ },
+ "VAE1": {
+ "path": "/home/pjluc/dev/fidle/VAE",
+ "start": "Thursday 7 January 2021, 09:37:44",
+ "end": "",
+ "duration": "Unfinished..."
+ },
+ "GTSRB1": {
+ "path": "/home/pjluc/dev/fidle/GTSRB",
+ "start": "Sunday 10 January 2021, 22:54:53",
+ "end": "Sunday 10 January 2021, 22:56:54",
+ "duration": "0:02:00"
+ },
+ "GTSRB2": {
+ "path": "/home/pjluc/dev/fidle/GTSRB",
+ "start": "Sunday 10 January 2021, 22:56:54",
+ "end": "",
+ "duration": "Unfinished..."
+ },
+ "GTSRB3": {
+ "path": "/home/pjluc/dev/fidle/GTSRB",
+ "start": "Thursday 7 January 2021, 12:15:52",
+ "end": "Thursday 7 January 2021, 12:20:01",
+ "duration": "00:04:09 711ms"
+ },
+ "GTSRB4": {
+ "path": "/home/pjluc/dev/fidle/GTSRB",
+ "start": "Thursday 7 January 2021, 13:40:52",
+ "end": "Thursday 7 January 2021, 13:41:31",
+ "duration": "00:00:39 161ms"
+ },
+ "GTSRB5": {
+ "path": "/home/pjluc/dev/fidle/GTSRB",
+ "start": "Thursday 7 January 2021, 14:47:12",
+ "end": "Thursday 7 January 2021, 14:48:44",
+ "duration": "00:01:32 269ms"
+ },
+ "GTSRB6": {
+ "path": "/home/pjluc/dev/fidle/GTSRB",
+ "start": "Thursday 7 January 2021, 15:41:17",
+ "end": "Thursday 7 January 2021, 15:41:18",
+ "duration": "00:00:01 101ms"
+ },
+ "GTSRB7": {
+ "path": "/home/pjluc/dev/fidle/GTSRB",
+ "start": "Thursday 7 January 2021, 15:16:05",
+ "end": "Thursday 7 January 2021, 15:16:06",
+ "duration": "00:00:00 116ms"
+ },
+ "BHPD1": {
+ "path": "/home/pjluc/dev/fidle/BHPD ",
+ "start": "Friday 8 January 2021, 01:09:13",
+ "end": "Friday 8 January 2021, 01:09:24",
+ "duration": "00:00:11 984ms"
+ },
+ "BHPD2": {
+ "path": "/home/pjluc/dev/fidle/BHPD ",
+ "start": "Friday 8 January 2021, 01:10:28",
+ "end": "Friday 8 January 2021, 01:10:39",
+ "duration": "00:00:12 582ms"
+ },
+ "SYNOP1": {
+ "path": "/home/pjluc/dev/fidle/SYNOP",
+ "start": "Saturday 9 January 2021, 10:04:28",
+ "end": "Saturday 9 January 2021, 10:04:34",
+ "duration": "00:00:05 236ms"
+ },
+ "SYNOP2": {
+ "path": "/home/pjluc/dev/fidle/SYNOP",
+ "start": "Saturday 9 January 2021, 10:30:55",
+ "end": "Saturday 9 January 2021, 10:31:11",
+ "duration": "00:00:16 248ms"
+ },
+ "SYNOP3": {
+ "path": "/home/pjluc/dev/fidle/SYNOP",
+ "start": "Saturday 9 January 2021, 10:27:54",
+ "end": "Saturday 9 January 2021, 10:27:59",
+ "duration": "00:00:05 249ms"
+ },
+ "LINR1": {
+ "path": "/home/pjluc/dev/fidle/LinearReg",
+ "start": "Sunday 10 January 2021, 22:54:49",
+ "end": "Sunday 10 January 2021, 22:54:53",
+ "duration": "0:00:04"
+ },
+ "GTSRB0": {
+ "path": "/home/pjluc/dev/fidle/GTSRB",
+ "start": "Saturday 9 January 2021, 19:34:14",
+ "end": "",
+ "duration": "Unfinished..."
+ }
+}
\ No newline at end of file
diff --git a/fidle/pwk.py b/fidle/pwk.py
index a4778682fbae7883ed6a1c1b8a694cf234b131bc..48c19f2df51b666bbbdfbad3f89b73159ce42eec 100644
--- a/fidle/pwk.py
+++ b/fidle/pwk.py
@@ -5,7 +5,7 @@
# | |_) | '__/ _` |/ __| __| |/ __/ _` | | \ \ /\ / / _ \| '__| |/ /
# | __/| | | (_| | (__| |_| | (_| (_| | | \ V V / (_) | | | <
# |_| |_| \__,_|\___|\__|_|\___\__,_|_| \_/\_/ \___/|_| |_|\_\
-# module pwk
+# Fidle module pwk
# ==================================================================
# A simple module to host some common functions for practical work
# Jean-Luc Parouty 2020
@@ -116,9 +116,6 @@ def init(name=None, run_directory='./run'):
save_figs = os.getenv('FIDLE_SAVE_FIGS', str(config.SAVE_FIGS) )
if save_figs.lower() == 'true':
set_save_fig(save=True, figs_dir=f'{run_dir}/figs', figs_name='fig_', figs_id=0)
-
-
- update_finished_file(start=True)
return datasets_dir
@@ -744,63 +741,12 @@ def np_print(*args, precision=3, linewidth=120):
with np.printoptions(precision=precision, linewidth=linewidth):
for a in args:
print(a)
-
-
-def check_finished_file():
- if not os.access(config.FINISHED_FILE, os.W_OK):
- print("\n** Error : Cannot access finished file in write mode for reset...")
- print(f'** Finished file should be at : {config.FINISHED_FILE}\n')
- return False
- return True
-
-
-def reset_finished_file(verbose=False):
- try:
- data={}
- with open(config.FINISHED_FILE,'wt') as fp:
- json.dump(data,fp,indent=4)
- if verbose : print(f'Finished file has been reset.\n')
- except:
- print(f'\n**Warning : cannot reset finished file ({config.FINISHED_FILE})\n')
- return False
- return True
-
-
-def update_finished_file(start=False, end=False):
-
- # ---- No writable finished file ?
- if not os.access(config.FINISHED_FILE, os.W_OK):
- done = reset_finished_file()
- if not done : return
-
- # ---- Load it
- with open(config.FINISHED_FILE) as fp:
- data = json.load(fp)
-
- # ---- Update as a start
- if start is True:
- data[notebook_id] = {}
- data[notebook_id]['path'] = os.getcwd()
- data[notebook_id]['start'] = _start_time.strftime("%A %-d %B %Y, %H:%M:%S")
- data[notebook_id]['end'] = ''
- data[notebook_id]['duration'] = 'Unfinished...'
-
- # ---- Update as an end
- if end is True:
- data[notebook_id]['end'] = _end_time.strftime("%A %-d %B %Y, %H:%M:%S")
- data[notebook_id]['duration'] = hdelay_ms(_end_time - _start_time)
-
- # ---- Save it
- with open(config.FINISHED_FILE,'wt') as fp:
- json.dump(data,fp,indent=4)
def end():
global _end_time
_end_time = datetime.datetime.now()
-
- update_finished_file(end=True)
-
+
print('End time is :', time.strftime("%A %-d %B %Y, %H:%M:%S"))
print('Duration is :', hdelay_ms(_end_time - _start_time))
print('This notebook ends here')