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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"gpuType": "T4"
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"id": "zlD1ysQ7Tckp"
},
"outputs": [],
"source": [
"import torch\n",
"from torch import nn\n",
"from pathlib import Path"
]
},
{
"cell_type": "code",
"source": [
"!pip3 install gradio"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "YJQBJHP1Tym5",
"outputId": "46afdd2e-b5fc-4eef-93e3-1f3bc9b7f1ce"
},
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Collecting gradio\n",
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"Building wheels for collected packages: ffmpy\n",
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" Attempting uninstall: markdown-it-py\n",
" Found existing installation: markdown-it-py 3.0.0\n",
" Uninstalling markdown-it-py-3.0.0:\n",
" Successfully uninstalled markdown-it-py-3.0.0\n",
"Successfully installed aiofiles-23.1.0 fastapi-0.100.0 ffmpy-0.3.1 gradio-3.38.0 gradio-client-0.2.10 h11-0.14.0 httpcore-0.17.3 httpx-0.24.1 huggingface-hub-0.16.4 linkify-it-py-2.0.2 markdown-it-py-2.2.0 mdit-py-plugins-0.3.3 orjson-3.9.2 pydub-0.25.1 python-multipart-0.0.6 semantic-version-2.10.0 starlette-0.27.0 uc-micro-py-1.0.2 uvicorn-0.23.1 websockets-11.0.3\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"LABELS=Path('class_names.txt').read_text().splitlines()"
],
"metadata": {
"id": "PGdL4zXMT8Bn"
},
"execution_count": 3,
"outputs": []
},
{
"cell_type": "code",
"source": [
"model = nn.Sequential(\n",
" nn.Conv2d(1, 32, 3, padding='same'),\n",
" nn.ReLU(),\n",
" nn.MaxPool2d(2),\n",
" nn.Conv2d(32, 64, 3, padding='same'),\n",
" nn.ReLU(),\n",
" nn.MaxPool2d(2),\n",
" nn.Conv2d(64, 128, 3, padding='same'),\n",
" nn.ReLU(),\n",
" nn.MaxPool2d(2),\n",
" nn.Flatten(),\n",
" nn.Linear(1152, 256),\n",
" nn.ReLU(),\n",
" nn.Linear(256, len(LABELS)),\n",
")"
],
"metadata": {
"id": "XZ1AM4BxUMnH"
},
"execution_count": 4,
"outputs": []
},
{
"cell_type": "code",
"source": [
"state_dict=torch.load('pytorch_model.bin',map_location='cpu')"
],
"metadata": {
"id": "lDJZ7Vo9Ui0Y"
},
"execution_count": 9,
"outputs": []
},
{
"cell_type": "code",
"source": [
"import gradio as gr"
],
"metadata": {
"id": "LzwKoPfTUq5x"
},
"execution_count": 7,
"outputs": []
},
{
"cell_type": "code",
"source": [
"model.load_state_dict(state_dict, strict=False)\n",
"model.eval()\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "e_6paL_qU4YB",
"outputId": "e018df13-6ac1-47a0-d634-cb8084d05d5a"
},
"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"Sequential(\n",
" (0): Conv2d(1, 32, kernel_size=(3, 3), stride=(1, 1), padding=same)\n",
" (1): ReLU()\n",
" (2): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
" (3): Conv2d(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=same)\n",
" (4): ReLU()\n",
" (5): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
" (6): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=same)\n",
" (7): ReLU()\n",
" (8): MaxPool2d(kernel_size=2, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
" (9): Flatten(start_dim=1, end_dim=-1)\n",
" (10): Linear(in_features=1152, out_features=256, bias=True)\n",
" (11): ReLU()\n",
" (12): Linear(in_features=256, out_features=100, bias=True)\n",
")"
]
},
"metadata": {},
"execution_count": 10
}
]
},
{
"cell_type": "code",
"source": [
"def predict(im):\n",
" x = torch.tensor(im, dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.\n",
"\n",
" with torch.no_grad():\n",
" out = model(x)\n",
"\n",
" probabilities = torch.nn.functional.softmax(out[0], dim=0)\n",
"\n",
" values, indices = torch.topk(probabilities, 5)\n",
"\n",
" return {LABELS[i]: v.item() for i, v in zip(indices, values)}"
],
"metadata": {
"id": "baptDAiGVCvF"
},
"execution_count": 11,
"outputs": []
},
{
"cell_type": "code",
"source": [
"interface=gr.Interface(\n",
" predict,\n",
" inputs=\"sketchpad\",\n",
" outputs='label',\n",
" theme=\"huggingface\",\n",
" title=\"Sketch Recognition\",\n",
" description=\"Sketch something for the model to guess in realtime\",\n",
" article = \"<p style='text-align: center'>Sketch Recognition | Demo Model</p>\",\n",
" live=True)\n",
"interface.launch(share=True)\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 1000
},
"id": "4sZiRCv-VI9O",
"outputId": "476b68b7-397e-4465-fb83-fb9b6dff499d"
},
"execution_count": 13,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py:694: UserWarning: Cannot load huggingface. Caught Exception: The space huggingface does not exist\n",
" warnings.warn(f\"Cannot load {theme}. Caught Exception: {str(e)}\")\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Colab notebook detected. This cell will run indefinitely so that you can see errors and logs. To turn off, set debug=False in launch().\n",
"Running on public URL: https://033d7a67112f637955.gradio.live\n",
"\n",
"This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.HTML object>"
],
"text/html": [
"<div><iframe src=\"https://033d7a67112f637955.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
]
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/routes.py\", line 442, in run_predict\n",
" output = await app.get_blocks().process_api(\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 1389, in process_api\n",
" result = await self.call_function(\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 1094, in call_function\n",
" prediction = await anyio.to_thread.run_sync(\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/to_thread.py\", line 33, in run_sync\n",
" return await get_asynclib().run_sync_in_worker_thread(\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py\", line 877, in run_sync_in_worker_thread\n",
" return await future\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py\", line 807, in run\n",
" result = context.run(func, *args)\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/utils.py\", line 703, in wrapper\n",
" response = f(*args, **kwargs)\n",
" File \"<ipython-input-11-83491c3d48b5>\", line 2, in predict\n",
" x = torch.tensor(im, dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.\n",
"TypeError: must be real number, not NoneType\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/routes.py\", line 442, in run_predict\n",
" output = await app.get_blocks().process_api(\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 1389, in process_api\n",
" result = await self.call_function(\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 1094, in call_function\n",
" prediction = await anyio.to_thread.run_sync(\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/to_thread.py\", line 33, in run_sync\n",
" return await get_asynclib().run_sync_in_worker_thread(\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py\", line 877, in run_sync_in_worker_thread\n",
" return await future\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py\", line 807, in run\n",
" result = context.run(func, *args)\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/utils.py\", line 703, in wrapper\n",
" response = f(*args, **kwargs)\n",
" File \"<ipython-input-11-83491c3d48b5>\", line 2, in predict\n",
" x = torch.tensor(im, dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.\n",
"TypeError: must be real number, not NoneType\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/routes.py\", line 442, in run_predict\n",
" output = await app.get_blocks().process_api(\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 1389, in process_api\n",
" result = await self.call_function(\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 1094, in call_function\n",
" prediction = await anyio.to_thread.run_sync(\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/to_thread.py\", line 33, in run_sync\n",
" return await get_asynclib().run_sync_in_worker_thread(\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py\", line 877, in run_sync_in_worker_thread\n",
" return await future\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py\", line 807, in run\n",
" result = context.run(func, *args)\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/utils.py\", line 703, in wrapper\n",
" response = f(*args, **kwargs)\n",
" File \"<ipython-input-11-83491c3d48b5>\", line 2, in predict\n",
" x = torch.tensor(im, dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.\n",
"TypeError: must be real number, not NoneType\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/routes.py\", line 442, in run_predict\n",
" output = await app.get_blocks().process_api(\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 1389, in process_api\n",
" result = await self.call_function(\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 1094, in call_function\n",
" prediction = await anyio.to_thread.run_sync(\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/to_thread.py\", line 33, in run_sync\n",
" return await get_asynclib().run_sync_in_worker_thread(\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py\", line 877, in run_sync_in_worker_thread\n",
" return await future\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py\", line 807, in run\n",
" result = context.run(func, *args)\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/utils.py\", line 703, in wrapper\n",
" response = f(*args, **kwargs)\n",
" File \"<ipython-input-11-83491c3d48b5>\", line 2, in predict\n",
" x = torch.tensor(im, dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.\n",
"TypeError: must be real number, not NoneType\n",
"Traceback (most recent call last):\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/routes.py\", line 442, in run_predict\n",
" output = await app.get_blocks().process_api(\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 1389, in process_api\n",
" result = await self.call_function(\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/blocks.py\", line 1094, in call_function\n",
" prediction = await anyio.to_thread.run_sync(\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/to_thread.py\", line 33, in run_sync\n",
" return await get_asynclib().run_sync_in_worker_thread(\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py\", line 877, in run_sync_in_worker_thread\n",
" return await future\n",
" File \"/usr/local/lib/python3.10/dist-packages/anyio/_backends/_asyncio.py\", line 807, in run\n",
" result = context.run(func, *args)\n",
" File \"/usr/local/lib/python3.10/dist-packages/gradio/utils.py\", line 703, in wrapper\n",
" response = f(*args, **kwargs)\n",
" File \"<ipython-input-11-83491c3d48b5>\", line 2, in predict\n",
" x = torch.tensor(im, dtype=torch.float32).unsqueeze(0).unsqueeze(0) / 255.\n",
"TypeError: must be real number, not NoneType\n"
]
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"Keyboard interruption in main thread... closing server.\n",
"Killing tunnel 127.0.0.1:7860 <> https://033d7a67112f637955.gradio.live\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": []
},
"metadata": {},
"execution_count": 13
}
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "30uwS_0zVhT3"
},
"execution_count": null,
"outputs": []
}
]
} |