fp16

app.ipynb

@@ -2,12 +2,22 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
+   "id": "18acb717",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|default_exp app"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "id": "44eb0ad3",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#export\n",
+    "#|export\n",
     "from fastai.vision.all import *\n",
     "import gradio as gr\n",
     "\n",
@@ -16,7 +26,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "d838c0b3",
    "metadata": {},
    "outputs": [],
@@ -31,7 +41,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "c107f724",
    "metadata": {},
    "outputs": [
@@ -75,10 +85,10 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <td>0</td>\n",
-       "      <td>0.217549</td>\n",
-       "      <td>0.094998</td>\n",
-       "      <td>0.026387</td>\n",
-       "      <td>00:05</td>\n",
+       "      <td>0.209574</td>\n",
+       "      <td>0.081121</td>\n",
+       "      <td>0.022327</td>\n",
+       "      <td>00:24</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>"
@@ -130,24 +140,24 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <td>0</td>\n",
-       "      <td>0.095330</td>\n",
-       "      <td>0.042852</td>\n",
-       "      <td>0.013532</td>\n",
-       "      <td>00:06</td>\n",
+       "      <td>0.090262</td>\n",
+       "      <td>0.056602</td>\n",
+       "      <td>0.017591</td>\n",
+       "      <td>00:23</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <td>1</td>\n",
-       "      <td>0.036632</td>\n",
-       "      <td>0.046426</td>\n",
-       "      <td>0.016915</td>\n",
-       "      <td>00:05</td>\n",
+       "      <td>0.035389</td>\n",
+       "      <td>0.037754</td>\n",
+       "      <td>0.014208</td>\n",
+       "      <td>00:22</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <td>2</td>\n",
-       "      <td>0.019293</td>\n",
-       "      <td>0.038611</td>\n",
-       "      <td>0.013532</td>\n",
-       "      <td>00:05</td>\n",
+       "      <td>0.013607</td>\n",
+       "      <td>0.038817</td>\n",
+       "      <td>0.012179</td>\n",
+       "      <td>00:22</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>"
@@ -167,7 +177,158 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
+   "id": "bed928f3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "path = untar_data(URLs.PETS)/'images'\n",
+    "\n",
+    "dls = ImageDataLoaders.from_name_func('.',\n",
+    "    get_image_files(path), valid_pct=0.2, seed=42,\n",
+    "    label_func=is_cat,\n",
+    "    item_tfms=Resize(192))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7e56b200",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: left;\">\n",
+       "      <th>epoch</th>\n",
+       "      <th>train_loss</th>\n",
+       "      <th>valid_loss</th>\n",
+       "      <th>error_rate</th>\n",
+       "      <th>time</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>0.184049</td>\n",
+       "      <td>0.038403</td>\n",
+       "      <td>0.010825</td>\n",
+       "      <td>00:21</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: left;\">\n",
+       "      <th>epoch</th>\n",
+       "      <th>train_loss</th>\n",
+       "      <th>valid_loss</th>\n",
+       "      <th>error_rate</th>\n",
+       "      <th>time</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>0</td>\n",
+       "      <td>0.075693</td>\n",
+       "      <td>0.042666</td>\n",
+       "      <td>0.013532</td>\n",
+       "      <td>00:24</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>0.038955</td>\n",
+       "      <td>0.018082</td>\n",
+       "      <td>0.006089</td>\n",
+       "      <td>00:22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>0.016343</td>\n",
+       "      <td>0.018480</td>\n",
+       "      <td>0.004736</td>\n",
+       "      <td>00:24</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "learn = vision_learner(dls, resnet18, metrics=error_rate).to_fp16()\n",
+    "learn.fine_tune(3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "id": "5171c7fc",
    "metadata": {},
    "outputs": [],
@@ -177,7 +338,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "3295ef11",
    "metadata": {},
    "outputs": [
@@ -188,7 +349,7 @@
        "PILImage mode=RGB size=192x191"
       ]
      },
-     "execution_count": 6,
+     "execution_count": null,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -201,22 +362,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "ae2bc6ac",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#export\n",
+    "#|export\n",
     "learn = load_learner('model.pkl')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "6e0bf9da",
-   "metadata": {
-    "scrolled": false
-   },
+   "metadata": {},
    "outputs": [
     {
      "data": {
@@ -255,10 +414,10 @@
     {
      "data": {
       "text/plain": [
-       "('False', TensorBase(0), TensorBase([9.9993e-01, 6.6811e-05]))"
+       "('False', TensorBase(0), TensorBase([9.9999e-01, 8.4523e-06]))"
       ]
      },
-     "execution_count": 8,
+     "execution_count": null,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -269,12 +428,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "0419ed3a",
    "metadata": {},
    "outputs": [],
    "source": [
-    "#export\n",
+    "#|export\n",
     "categories = ('Dog', 'Cat')\n",
     "\n",
     "def classify_image(img):\n",
@@ -284,7 +443,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "762dec00",
    "metadata": {},
    "outputs": [
@@ -325,10 +484,10 @@
     {
      "data": {
       "text/plain": [
-       "{'Dog': 0.9999332427978516, 'Cat': 6.681094237137586e-05}"
+       "{'Dog': 0.9999915361404419, 'Cat': 8.452258043689653e-06}"
       ]
      },
-     "execution_count": 10,
+     "execution_count": null,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -339,11 +498,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "0518a30a",
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -354,113 +511,69 @@
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
     },
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "        <iframe\n",
-       "            width=\"900\"\n",
-       "            height=\"500\"\n",
-       "            src=\"http://127.0.0.1:7860/\"\n",
-       "            frameborder=\"0\"\n",
-       "            allowfullscreen\n",
-       "            \n",
-       "        ></iframe>\n",
-       "        "
-      ],
-      "text/plain": [
-       "<IPython.lib.display.IFrame at 0x7f98552d6340>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "data": {
       "text/plain": [
-       "(<fastapi.applications.FastAPI at 0x7f986cf492b0>,\n",
+       "(<fastapi.applications.FastAPI at 0x7fa03ba47670>,\n",
        " 'http://127.0.0.1:7860/',\n",
        " None)"
       ]
      },
-     "execution_count": 10,
+     "execution_count": null,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "#export\n",
+    "#|export\n",
     "image = gr.inputs.Image(shape=(192, 192))\n",
     "label = gr.outputs.Label()\n",
     "examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']\n",
     "\n",
     "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
-    "intf.launch()"
+    "intf.launch(inline=False)"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "103be39f",
+   "cell_type": "markdown",
+   "id": "0d1e90ce",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "import requests,base64\n",
-    "from PIL import Image\n",
-    "from io import BytesIO"
+    "## end -"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "id": "fd962acc",
+   "execution_count": null,
+   "id": "82774c08",
    "metadata": {},
    "outputs": [],
    "source": [
-    "def data_url(filename, size=(192,192)):\n",
-    "    image = PILImage.create(filename)\n",
-    "    image.thumbnail(size)\n",
-    "    buff = BytesIO()\n",
-    "    image.save(buff, format=\"JPEG\")\n",
-    "    prefix = f'data:image/{Path(filename).suffix[1:]};base64,'\n",
-    "    return prefix + base64.b64encode(buff.getvalue()).decode('utf-8')"
+    "from nbdev.export import notebook2script"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
-   "id": "a55f921b",
-   "metadata": {
-    "scrolled": true
-   },
+   "execution_count": null,
+   "id": "7a880da1",
+   "metadata": {},
    "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"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Converted app.ipynb.\n"
+     ]
     }
    ],
    "source": [
-    "data = {\"data\": [data_url('cat.jpg')]}\n",
-    "res = requests.post(url='https://hf.space/embed/jph00/testing/+/api/predict/', json=data).json()\n",
-    "res"
+    "notebook2script('app.ipynb')"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "82774c08",
+   "id": "1a349335",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -471,31 +584,6 @@
    "display_name": "Python 3 (ipykernel)",
    "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": "3.9.5"
-  },
-  "toc": {
-   "base_numbering": 1,
-   "nav_menu": {},
-   "number_sections": false,
-   "sideBar": true,
-   "skip_h1_title": false,
-   "title_cell": "Table of Contents",
-   "title_sidebar": "Contents",
-   "toc_cell": false,
-   "toc_position": {},
-   "toc_section_display": true,
-   "toc_window_display": false
   }
  },
  "nbformat": 4,

app.py

@@ -24,4 +24,4 @@ label = gr.outputs.Label()
 examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']
 
 intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
-intf.launch()
+intf.launch(inline=False)

model.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:656a52c3cd69a13f3a23f8c1eefa1333a0b7f0509adc60e1bec6e4f9662a4e22
-size 47062571
+oid sha256:46eee60a5eac1402f8402ce1915230e6ca75d8d05c35c4e9500eadf2e39c525a
+size 47062827