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{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: progress"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio tqdm datasets"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import random\n", "import time\n", "import tqdm\n", "from datasets import load_dataset\n", "import shutil\n", "from uuid import uuid4\n", "\n", "with gr.Blocks() as demo:\n", " with gr.Row():\n", " text = gr.Textbox()\n", " textb = gr.Textbox()\n", " with gr.Row():\n", " load_set_btn = gr.Button(\"Load Set\")\n", " load_nested_set_btn = gr.Button(\"Load Nested Set\")\n", " load_random_btn = gr.Button(\"Load Random\")\n", " clean_imgs_btn = gr.Button(\"Clean Images\")\n", " wait_btn = gr.Button(\"Wait\")\n", " do_all_btn = gr.Button(\"Do All\")\n", " track_tqdm_btn = gr.Button(\"Bind TQDM\")\n", " bind_internal_tqdm_btn = gr.Button(\"Bind Internal TQDM\")\n", "\n", " text2 = gr.Textbox()\n", "\n", " # track list\n", " def load_set(text, text2, progress=gr.Progress()):\n", " imgs = [None] * 24\n", " for img in progress.tqdm(imgs, desc=\"Loading from list\"):\n", " time.sleep(0.1)\n", " return \"done\"\n", " load_set_btn.click(load_set, [text, textb], text2)\n", "\n", " # track nested list\n", " def load_nested_set(text, text2, progress=gr.Progress()):\n", " imgs = [[None] * 8] * 3\n", " for img_set in progress.tqdm(imgs, desc=\"Nested list\"):\n", " time.sleep(2)\n", " for img in progress.tqdm(img_set, desc=\"inner list\"):\n", " time.sleep(0.1)\n", " return \"done\"\n", " load_nested_set_btn.click(load_nested_set, [text, textb], text2)\n", "\n", " # track iterable of unknown length\n", " def load_random(data, progress=gr.Progress()):\n", " def yielder():\n", " for i in range(0, random.randint(15, 20)):\n", " time.sleep(0.1)\n", " yield None\n", " for img in progress.tqdm(yielder()):\n", " pass\n", " return \"done\"\n", " load_random_btn.click(load_random, {text, textb}, text2)\n", "\n", " # manual progress\n", " def clean_imgs(text, progress=gr.Progress()):\n", " progress(0.2, desc=\"Collecting Images\")\n", " time.sleep(1)\n", " progress(0.5, desc=\"Cleaning Images\")\n", " time.sleep(1.5)\n", " progress(0.8, desc=\"Sending Images\")\n", " time.sleep(1.5)\n", " return \"done\"\n", " clean_imgs_btn.click(clean_imgs, text, text2)\n", "\n", " # no progress\n", " def wait(text):\n", " time.sleep(4)\n", " return \"done\"\n", " wait_btn.click(wait, text, text2)\n", "\n", " # multiple progressions\n", " def do_all(data, progress=gr.Progress()):\n", " load_set(data[text], data[textb], progress)\n", " load_random(data, progress)\n", " clean_imgs(data[text], progress)\n", " progress(None)\n", " wait(text)\n", " return \"done\"\n", " do_all_btn.click(do_all, {text, textb}, text2)\n", "\n", " def track_tqdm(data, progress=gr.Progress(track_tqdm=True)):\n", " for i in tqdm.tqdm(range(5), desc=\"outer\"):\n", " for j in tqdm.tqdm(range(4), desc=\"inner\"):\n", " time.sleep(1)\n", " return \"done\"\n", " track_tqdm_btn.click(track_tqdm, {text, textb}, text2)\n", "\n", " def bind_internal_tqdm(data, progress=gr.Progress(track_tqdm=True)):\n", " outdir = \"__tmp/\" + str(uuid4())\n", " load_dataset(\"beans\", split=\"train\", cache_dir=outdir)\n", " shutil.rmtree(outdir)\n", " return \"done\"\n", " bind_internal_tqdm_btn.click(bind_internal_tqdm, {text, textb}, text2)\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} |