Deploy to GitHub Pages on master [ci skip]

Author: facebook-circleci-bot

404.html

@@ -453,6 +453,12 @@ <h2>Resources</h2>
         <li><a href="https://www.linkedin.com/company/pytorch" target="_blank" title="PyTorch on LinkedIn">
           <svg xmlns="http://www.w3.org/2000/svg" viewbox="-10.23 -10.23 531.96 531.96" aria-label="LinkedIn"><rect width="512" height="512" rx="0" fill="currentColor"/><circle fill="#000" cx="142" cy="138" r="37"/><path stroke="#000" stroke-width="66" d="M244 194v198M142 194v198"/><path fill="#000" d="M276 282c0-20 13-40 36-40 24 0 33 18 33 45v105h66V279c0-61-32-89-76-89-34 0-51 19-59 32"/></svg>
         </a></li>
+        <li><a href="https://join.slack.com/t/pytorch/shared_invite/zt-2j2la612p-miUinTTaxXczKOJw48poHA" target="_blank" title="PyTorch Slack">
+          <svg xmlns="http://www.w3.org/2000/svg" viewBox="0.16 -0.03 21.19 21.19" aria-label="Slack"><path fill="currentColor" d="M4.896 13.27a2.147 2.147 0 0 1-2.141 2.142A2.147 2.147 0 0 1 .613 13.27c0-1.178.963-2.141 2.142-2.141h2.141v2.141zm1.08 0c0-1.178.962-2.141 2.141-2.141s2.142.963 2.142 2.141v5.363a2.147 2.147 0 0 1-2.142 2.141 2.147 2.147 0 0 1-2.141-2.142V13.27zm2.141-8.6a2.147 2.147 0 0 1-2.141-2.14c0-1.18.962-2.142 2.141-2.142s2.142.963 2.142 2.141v2.142H8.117zm0 1.08c1.179 0 2.141.962 2.141 2.141a2.147 2.147 0 0 1-2.141 2.142H2.755A2.147 2.147 0 0 1 .613 7.89c0-1.179.963-2.141 2.142-2.141h5.362zm8.599 2.141c0-1.179.963-2.141 2.141-2.141 1.179 0 2.143.962 2.143 2.14a2.147 2.147 0 0 1-2.142 2.142h-2.141V7.89zm-1.08 0a2.147 2.147 0 0 1-2.141 2.142 2.147 2.147 0 0 1-2.141-2.142V2.53c0-1.178.962-2.141 2.141-2.141s2.142.963 2.142 2.141v5.362zm-2.141 8.6c1.179 0 2.142.962 2.142 2.14a2.147 2.147 0 0 1-2.142 2.142 2.147 2.147 0 0 1-2.141-2.141V16.49h2.141zm0-1.08a2.147 2.147 0 0 1-2.141-2.141c0-1.179.962-2.142 2.141-2.142h5.362c1.179 0 2.142.963 2.142 2.142a2.147 2.147 0 0 1-2.142 2.142h-5.362z"></path></svg>
+        </a></li>
+        <li><a href="/wechat" title="PyTorch on WeChat">
+          <svg xmlns="http://www.w3.org/2000/svg" viewBox="0.14 -0.17 38.02 33.02" aria-label="WeChat"><path fill="currentColor" d="M26.289 10.976a12.972 12.972 0 0 0-8.742 3.53 10.386 10.386 0 0 0-3.224 8.795c-1.326-.164-2.535-.345-3.75-.448a2.332 2.332 0 0 0-1.273.216c-1.18.666-2.311 1.418-3.652 2.255.246-1.112.405-2.087.687-3.024a1.15 1.15 0 0 0-.523-1.52C1.737 17.902.02 13.601 1.307 9.165c1.189-4.1 4.11-6.587 8.077-7.884A13.54 13.54 0 0 1 24.18 5.617a10.135 10.135 0 0 1 2.109 5.359zM10.668 9.594a1.564 1.564 0 0 0-2.095-1.472 1.52 1.52 0 0 0-.895 1.964 1.502 1.502 0 0 0 1.391.966 1.545 1.545 0 0 0 1.598-1.46v.002zm8.15-1.566a1.567 1.567 0 0 0-1.528 1.543 1.528 1.528 0 0 0 1.571 1.492 1.52 1.52 0 0 0 1.375-2.117 1.518 1.518 0 0 0-1.415-.919l-.003.001z"></path><path fill="currentColor" d="M33.914 32.137c-1.075-.478-2.062-1.196-3.11-1.306-1.049-.11-2.145.494-3.24.605a10.821 10.821 0 0 1-8.781-2.864c-4.682-4.33-4.013-10.97 1.403-14.518 4.811-3.154 11.874-2.102 15.268 2.273a8.671 8.671 0 0 1-1.002 12.095c-1.046.929-1.422 1.693-.751 2.917.102.257.174.525.213.798zM21.68 20.292a1.264 1.264 0 1 0 .01-2.528 1.264 1.264 0 0 0-.01 2.528zm7.887-2.526a1.266 1.266 0 0 0-1.256 1.21 1.247 1.247 0 1 0 1.256-1.21z"></path></svg>
+        </a></li>
       </ul>
     </div>
 

assets/hub/datvuthanh_hybridnets.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "b86bb38e",
+   "id": "a3312e6d",
    "metadata": {},
    "source": [
     "### This notebook is optionally accelerated with a GPU runtime.\n",
@@ -24,7 +24,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d8e6570f",
+   "id": "dfc2b7f3",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -34,7 +34,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5cfb241e",
+   "id": "6e8a3b9f",
    "metadata": {},
    "source": [
     "## Model Description\n",
@@ -93,7 +93,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1bc56f6d",
+   "id": "284776c3",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -109,7 +109,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "33826cd1",
+   "id": "9f77a526",
    "metadata": {},
    "source": [
     "### Citation\n",
@@ -120,7 +120,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "66a8111f",
+   "id": "6d761678",
    "metadata": {
     "attributes": {
      "classes": [

assets/hub/facebookresearch_WSL-Images_resnext.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "63fd6913",
+   "id": "daf641c2",
    "metadata": {},
    "source": [
     "### This notebook is optionally accelerated with a GPU runtime.\n",
@@ -22,7 +22,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "192e3f86",
+   "id": "485e1742",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3f19d467",
+   "id": "5e8281ee",
    "metadata": {},
    "source": [
     "All pre-trained models expect input images normalized in the same way,\n",
@@ -53,7 +53,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "282fd4ff",
+   "id": "b21e7305",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -67,7 +67,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "8b3d7eeb",
+   "id": "e4ad7361",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -99,7 +99,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "216b393a",
+   "id": "b2b63fd4",
    "metadata": {},
    "source": [
     "### Model Description\n",

assets/hub/facebookresearch_pytorch-gan-zoo_dcgan.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "71f9a8d9",
+   "id": "dd56f149",
    "metadata": {},
    "source": [
     "### This notebook is optionally accelerated with a GPU runtime.\n",
@@ -22,7 +22,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d7adbdaa",
+   "id": "cfb500f3",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -34,7 +34,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b6a92c44",
+   "id": "fdf05e62",
    "metadata": {},
    "source": [
     "The input to the model is a noise vector of shape `(N, 120)` where `N` is the number of images to be generated.\n",
@@ -45,7 +45,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d62cbed6",
+   "id": "2744397d",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -63,7 +63,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3b14698a",
+   "id": "2a07aca5",
    "metadata": {},
    "source": [
     "You should see an image similar to the one on the left.\n",

assets/hub/facebookresearch_pytorch-gan-zoo_pgan.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "51cc1900",
+   "id": "c16d095a",
    "metadata": {},
    "source": [
     "### This notebook is optionally accelerated with a GPU runtime.\n",
@@ -24,7 +24,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ee74ad23",
+   "id": "b3a0fc8a",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -44,7 +44,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e0b1d672",
+   "id": "1a472056",
    "metadata": {},
    "source": [
     "The input to the model is a noise vector of shape `(N, 512)` where `N` is the number of images to be generated.\n",
@@ -55,7 +55,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "742c8b7b",
+   "id": "12fec382",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -74,7 +74,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "02b70d7e",
+   "id": "2590cade",
    "metadata": {},
    "source": [
     "You should see an image similar to the one on the left.\n",

assets/hub/facebookresearch_pytorchvideo_resnet.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "e5df62f5",
+   "id": "425b633e",
    "metadata": {},
    "source": [
     "# 3D ResNet\n",
@@ -22,7 +22,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6ddaa8b6",
+   "id": "f35bbda6",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -33,7 +33,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d0cc6811",
+   "id": "4cec1beb",
    "metadata": {},
    "source": [
     "Import remaining functions:"
@@ -42,7 +42,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "d2783125",
+   "id": "24287b10",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -64,7 +64,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7b2546a5",
+   "id": "86d9021b",
    "metadata": {},
    "source": [
     "#### Setup\n",
@@ -75,7 +75,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5ac8b66b",
+   "id": "fc521d93",
    "metadata": {
     "attributes": {
      "classes": [
@@ -94,7 +94,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2ed761a4",
+   "id": "c41abab6",
    "metadata": {},
    "source": [
     "Download the id to label mapping for the Kinetics 400 dataset on which the torch hub models were trained. This will be used to get the category label names from the predicted class ids."
@@ -103,7 +103,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b0228614",
+   "id": "9cf77219",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -116,7 +116,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "52ce68d3",
+   "id": "4fb9d83e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -131,7 +131,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c4a1167b",
+   "id": "6e1f7064",
    "metadata": {},
    "source": [
     "#### Define input transform"
@@ -140,7 +140,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b3a32f0b",
+   "id": "e025e0e4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -174,7 +174,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "298f6d85",
+   "id": "9caf5604",
    "metadata": {},
    "source": [
     "#### Run Inference\n",
@@ -185,7 +185,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7432a09a",
+   "id": "58f46c1c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -197,7 +197,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c5bcead3",
+   "id": "db257913",
    "metadata": {},
    "source": [
     "Load the video and transform it to the input format required by the model."
@@ -206,7 +206,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "912c52fd",
+   "id": "46408422",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -231,7 +231,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6a203be2",
+   "id": "3d15b27c",
    "metadata": {},
    "source": [
     "#### Get Predictions"
@@ -240,7 +240,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ee9a1f5c",
+   "id": "30937e12",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -259,7 +259,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9828a0c9",
+   "id": "37131e5f",
    "metadata": {},
    "source": [
     "### Model Description\n",