{ "cells": [ { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "from tqdm.notebook import trange, tqdm\n", "from time import sleep" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "metrics = {\"loss\": 0.0, \"accuracy\": 0.0}" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "e02253811497426483b5492663f276ee", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, description='Epoch', max=10.0, style=ProgressStyle(description_width='…" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, max=10.0), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, max=10.0), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, max=10.0), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, max=10.0), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, max=10.0), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, max=10.0), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] } ], "source": [ "for j in trange(10, unit=\"epoch\", initial=5,\n", " bar_format=\"{desc}: {n_fmt}/{total_fmt} {bar} {remaining}{postfix}\",\n", " desc=\"Epoch\"):\n", " with tqdm(\n", " total=10,\n", " leave=False,\n", " initial=0,\n", " unit=\"step\",\n", " bar_format=\"{n_fmt}/{total_fmt} {bar} {remaining} {rate_inv_fmt}{postfix}\",\n", " ) as t:\n", " for i in range(10):\n", " sleep(0.1)\n", " metrics[\"loss\"] = 0.9 * i\n", " metrics[\"accuracy\"] = 100 / (i + 1)\n", " t.set_postfix(**metrics)\n", " t.update()\n", " if j + 5 == 10:\n", " break\n", "# for j in tqdm(range(100), desc='2nd loop', leave=False, bar_format=\"{n_fmt}/{total_fmt} {bar} {remaining} {rate_inv_fmt}{postfix}\"):\n", "# sleep(0.1)\n", "# t.set_postfix(**metrics)\n", "# t.update()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "from datetime import datetime" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'0616_231817'" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "datetime.now().strftime(\"%m%d_%H%M%S\")" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "from loguru import logger" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": [ "a = 2" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2020-06-16 23:44:24.228 | DEBUG | __main__::1 - hej 2\n" ] } ], "source": [ "logger.debug(f\"hej {a}\", format=\"{time:YYYY-MM-DD at HH:mm:ss} : {level} : {message}\")" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from pathlib import Path" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "PosixPath('agaga/afaf')" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Path(\"agaga\") / \"afaf\"" ] }, { "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": "3.8.2" } }, "nbformat": 4, "nbformat_minor": 4 }