diff --git "a/app.ipynb" "b/app.ipynb" --- "a/app.ipynb" +++ "b/app.ipynb" @@ -2,7 +2,122 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 26, + "id": "ae753324-c23d-4011-869e-99ffc64bafd8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting git+https://github.com/huggingface/huggingface_hub (from -r requirements.txt (line 2))\n", + " Cloning https://github.com/huggingface/huggingface_hub to /tmp/pip-req-build-68x_4ir0\n", + " Running command git clone --filter=blob:none --quiet https://github.com/huggingface/huggingface_hub /tmp/pip-req-build-68x_4ir0\n", + " Resolved https://github.com/huggingface/huggingface_hub to commit 2702ec2a2bd0124cc1fddfd72ccb1297b2478148\n", + " Installing build dependencies ... \u001b[?2done\n", + "\u001b[?25h Getting requirements to build wheel ... \u001b[?25ldone\n", + "\u001b[?25h Preparing metadata (pyproject.toml) ... \u001b[?25ldone\n", + 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smart-open<8.0.0,>=5.2.1 in /home/mhnid/miniforge3/lib/python3.12/site-packages (from weasel<0.5.0,>=0.1.0->spacy<4->fastai->-r requirements.txt (line 1)) (7.1.0)\n", + "Requirement already satisfied: marisa-trie>=1.1.0 in /home/mhnid/miniforge3/lib/python3.12/site-packages (from language-data>=1.2->langcodes<4.0.0,>=3.2.0->spacy<4->fastai->-r requirements.txt (line 1)) (1.2.1)\n", + "Requirement already satisfied: mdurl~=0.1 in /home/mhnid/miniforge3/lib/python3.12/site-packages (from markdown-it-py>=2.2.0->rich>=10.11.0->typer<1.0,>=0.12->gradio->-r requirements.txt (line 3)) (0.1.2)\n", + "Requirement already satisfied: wrapt in /home/mhnid/miniforge3/lib/python3.12/site-packages (from smart-open<8.0.0,>=5.2.1->weasel<0.5.0,>=0.1.0->spacy<4->fastai->-r requirements.txt (line 1)) (1.17.0)\n" + ] + } + ], + "source": [ + "# Install dependencies from requirements.txt\n", + "!pip install -r requirements.txt" + ] + }, + { + "cell_type": "code", + "execution_count": 27, "id": "44eb0ad3", "metadata": {}, "outputs": [], @@ -17,7 +132,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 28, "id": "d838c0b3", "metadata": {}, "outputs": [], @@ -32,7 +147,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 29, "id": "c107f724", "metadata": {}, "outputs": [ @@ -48,6 +163,9 @@ " /* Needs to be in here for Safari polyfill so background images work as expected. */\n", " background-size: auto;\n", " }\n", + " progress:not([value]), progress:not([value])::-webkit-progress-bar {\n", + " background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n", + " }\n", " .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n", " background: #F44336;\n", " }\n", @@ -76,10 +194,10 @@ " \n", " \n", " 0\n", - " 0.217549\n", - " 0.094998\n", - " 0.026387\n", - " 00:05\n", + " 0.203732\n", + " 0.107336\n", + " 0.031800\n", + " 00:04\n", " \n", " \n", "" @@ -103,6 +221,9 @@ " /* Needs to be in here for Safari polyfill so background images work as expected. */\n", " background-size: auto;\n", " }\n", + " progress:not([value]), progress:not([value])::-webkit-progress-bar {\n", + " background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n", + " }\n", " .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n", " background: #F44336;\n", " }\n", @@ -131,24 +252,24 @@ " \n", " \n", " 0\n", - " 0.095330\n", - " 0.042852\n", - " 0.013532\n", - " 00:06\n", + " 0.067546\n", + " 0.075272\n", + " 0.022327\n", + " 00:04\n", " \n", " \n", " 1\n", - " 0.036632\n", - " 0.046426\n", - " 0.016915\n", - " 00:05\n", + " 0.040420\n", + " 0.042528\n", + " 0.012179\n", + " 00:04\n", " \n", " \n", " 2\n", - " 0.019293\n", - " 0.038611\n", + " 0.015238\n", + " 0.041341\n", " 0.013532\n", - " 00:05\n", + " 00:04\n", " \n", " \n", "" @@ -168,57 +289,58 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 30, "id": "5171c7fc", "metadata": {}, "outputs": [], "source": [ - "push_to_hub_fastai(learn, \"fastai/identify_dog_cat\", token=\"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\")\n", - "#The token no longer exists for security sake" + "#push_to_hub_fastai(learn, \"fastai/identify_dog_cat\", token=\"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\")\n", + "#The token no longer exists for security sake\n", + "learn.export('model.pkl')" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 37, "id": "3295ef11", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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", "text/plain": [ - "PILImage mode=RGB size=192x191" + "PILImage mode=RGB size=192x153" ] }, - "execution_count": 6, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "im = PILImage.create('dog.jpg')\n", + "im = PILImage.create('dunno.jpg')\n", "im.thumbnail((192,192))\n", "im" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 38, "id": "ae2bc6ac", "metadata": {}, "outputs": [], "source": [ "#export\n", - "learn = from_pretrained_fastai(\"fastai/cat_or_dog\")" + "#learn = from_pretrained_fastai(\"fastai/cat_or_dog\")\n", + "learn = load_learner('model.pkl')" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 39, "id": "6e0bf9da", - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -232,6 +354,9 @@ " /* Needs to be in here for Safari polyfill so background images work as expected. */\n", " background-size: auto;\n", " }\n", + " progress:not([value]), progress:not([value])::-webkit-progress-bar {\n", + " background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n", + " }\n", " .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n", " background: #F44336;\n", " }\n", @@ -257,10 +382,10 @@ { "data": { "text/plain": [ - "('False', TensorBase(0), TensorBase([9.9993e-01, 6.6811e-05]))" + "('False', tensor(0), tensor([9.9980e-01, 1.9651e-04]))" ] }, - "execution_count": 8, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } @@ -271,7 +396,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 63, "id": "0419ed3a", "metadata": {}, "outputs": [], @@ -279,14 +404,27 @@ "#export\n", "categories = ('Dog', 'Cat')\n", "\n", - "def classify_image(img):\n", + "from PIL import Image\n", + "import numpy as np\n", + "\n", + "def classify_image(image):\n", + " # Check if the input is a NumPy array (Gradio web interface)\n", + " if isinstance(image, np.ndarray):\n", + " # Convert NumPy array to a Pillow image\n", + " img = Image.fromarray(image.astype('uint8'))\n", + " else:\n", + " # Otherwise, assume it's already a Pillow image\n", + " img = image\n", + " \n", + " # Resize the image\n", + " img = img.resize((192, 192))\n", " pred,idx,probs = learn.predict(img)\n", " return dict(zip(categories, map(float,probs)))" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 64, "id": "762dec00", "metadata": {}, "outputs": [ @@ -302,6 +440,9 @@ " /* Needs to be in here for Safari polyfill so background images work as expected. */\n", " background-size: auto;\n", " }\n", + " progress:not([value]), progress:not([value])::-webkit-progress-bar {\n", + " background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n", + " }\n", " .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n", " background: #F44336;\n", " }\n", @@ -327,10 +468,10 @@ { "data": { "text/plain": [ - "{'Dog': 0.9999332427978516, 'Cat': 6.681094237137586e-05}" + "{'Dog': 0.9997860789299011, 'Cat': 0.00021398466196842492}" ] }, - "execution_count": 10, + "execution_count": 64, "metadata": {}, "output_type": "execute_result" } @@ -341,37 +482,63 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 65, "id": "0518a30a", "metadata": { - "collapsed": true + "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Running on local URL: http://127.0.0.1:7860/\n", + "* Running on local URL: http://127.0.0.1:7865\n", "\n", "To create a public link, set `share=True` in `launch()`.\n" ] }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + }, { "data": { "text/html": [ "\n", - " \n", - " " + "\n" ], "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -379,21 +546,204 @@ }, { "data": { + "text/html": [], "text/plain": [ - "(,\n", - " 'http://127.0.0.1:7860/',\n", - " None)" + "" ] }, - "execution_count": 10, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "\n", + "\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ "#export\n", - "image = gr.inputs.Image(shape=(192, 192))\n", - "label = gr.outputs.Label()\n", + "image = gr.Image()\n", + "label = gr.Label()\n", "examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']\n", "\n", "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n", @@ -402,7 +752,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 66, "id": "103be39f", "metadata": {}, "outputs": [], @@ -414,7 +764,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 67, "id": "fd962acc", "metadata": {}, "outputs": [], @@ -430,27 +780,30 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 68, "id": "a55f921b", "metadata": { "scrolled": true }, "outputs": [ { - "data": { - "text/plain": [ - "{'data': [{'label': 'Cat',\n", - " 'confidences': [{'label': 'Cat', 'confidence': 1.0},\n", - " {'label': 'Dog', 'confidence': 2.655391640078719e-13}]}],\n", - " 'flag_index': None,\n", - " 'updated_state': None,\n", - " 'durations': [0.0977640151977539],\n", - " 'avg_durations': [0.0977640151977539]}" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" + "ename": "JSONDecodeError", + "evalue": "Expecting value: line 1 column 1 (char 0)", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mJSONDecodeError\u001b[0m Traceback (most recent call last)", + "File \u001b[0;32m~/miniforge3/lib/python3.12/site-packages/requests/models.py:974\u001b[0m, in \u001b[0;36mResponse.json\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 973\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 974\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mcomplexjson\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloads\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtext\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 975\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m JSONDecodeError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 976\u001b[0m \u001b[38;5;66;03m# Catch JSON-related errors and raise as requests.JSONDecodeError\u001b[39;00m\n\u001b[1;32m 977\u001b[0m \u001b[38;5;66;03m# This aliases json.JSONDecodeError and simplejson.JSONDecodeError\u001b[39;00m\n", + "File \u001b[0;32m~/miniforge3/lib/python3.12/json/__init__.py:346\u001b[0m, in \u001b[0;36mloads\u001b[0;34m(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)\u001b[0m\n\u001b[1;32m 343\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m object_hook \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[1;32m 344\u001b[0m parse_int \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m parse_float \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[1;32m 345\u001b[0m parse_constant \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m object_pairs_hook \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m kw):\n\u001b[0;32m--> 346\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_default_decoder\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 347\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "File \u001b[0;32m~/miniforge3/lib/python3.12/json/decoder.py:338\u001b[0m, in \u001b[0;36mJSONDecoder.decode\u001b[0;34m(self, s, _w)\u001b[0m\n\u001b[1;32m 334\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Return the Python representation of ``s`` (a ``str`` instance\u001b[39;00m\n\u001b[1;32m 335\u001b[0m \u001b[38;5;124;03mcontaining a JSON document).\u001b[39;00m\n\u001b[1;32m 336\u001b[0m \n\u001b[1;32m 337\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m--> 338\u001b[0m obj, end \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraw_decode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43midx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_w\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mend\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 339\u001b[0m end \u001b[38;5;241m=\u001b[39m _w(s, end)\u001b[38;5;241m.\u001b[39mend()\n", + "File \u001b[0;32m~/miniforge3/lib/python3.12/json/decoder.py:356\u001b[0m, in \u001b[0;36mJSONDecoder.raw_decode\u001b[0;34m(self, s, idx)\u001b[0m\n\u001b[1;32m 355\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[0;32m--> 356\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m JSONDecodeError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExpecting value\u001b[39m\u001b[38;5;124m\"\u001b[39m, s, err\u001b[38;5;241m.\u001b[39mvalue) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 357\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m obj, end\n", + "\u001b[0;31mJSONDecodeError\u001b[0m: Expecting value: line 1 column 1 (char 0)", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001b[0;31mJSONDecodeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[68], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m data \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdata\u001b[39m\u001b[38;5;124m\"\u001b[39m: [data_url(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcat.jpg\u001b[39m\u001b[38;5;124m'\u001b[39m)]}\n\u001b[0;32m----> 2\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[43mrequests\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpost\u001b[49m\u001b[43m(\u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mhttps://hf.space/embed/jph00/testing/+/api/predict/\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mjson\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjson\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 3\u001b[0m res\n", + "File \u001b[0;32m~/miniforge3/lib/python3.12/site-packages/requests/models.py:978\u001b[0m, in \u001b[0;36mResponse.json\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m 974\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m complexjson\u001b[38;5;241m.\u001b[39mloads(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtext, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 975\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m JSONDecodeError \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m 976\u001b[0m \u001b[38;5;66;03m# Catch JSON-related errors and raise as requests.JSONDecodeError\u001b[39;00m\n\u001b[1;32m 977\u001b[0m \u001b[38;5;66;03m# This aliases json.JSONDecodeError and simplejson.JSONDecodeError\u001b[39;00m\n\u001b[0;32m--> 978\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m RequestsJSONDecodeError(e\u001b[38;5;241m.\u001b[39mmsg, e\u001b[38;5;241m.\u001b[39mdoc, e\u001b[38;5;241m.\u001b[39mpos)\n", + "\u001b[0;31mJSONDecodeError\u001b[0m: Expecting value: line 1 column 1 (char 0)" + ] } ], "source": [ @@ -466,6 +819,14 @@ "metadata": {}, "outputs": [], "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8c3fc18e-301c-467a-aef5-5095d1884209", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { @@ -484,7 +845,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.5" + "version": "3.12.8" }, "toc": { "base_numbering": 1,