Automated tutorials push

Author: pytorchbot

_downloads/162cf335b789dd055d4192f77cb0251c/foreach_map.ipynb

@@ -17,8 +17,8 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "(beta) Explicit horizontal fusion with foreach\\_map and torch.compile\n",
-    "============================================================\n",
+    "Explicit horizontal fusion with foreach\\_map and torch.compile\n",
+    "==============================================================\n",
     "\n",
     "**Author:** [Michael Lazos](https://github.com/mlazos)\n"
    ]
@@ -41,10 +41,14 @@
     "\n",
     "<div style=\"background-color: #f3f4f7; padding-left: 10px; padding-top: 10px; padding-bottom: 10px; padding-right: 10px\">\n",
     "\n",
-    "<p>This tutorial requires PyTorch 2.7.0 or later.</p>\n",
+    "<p>This recipe describes a prototype feature. Prototype features are typicallyat an early stage for feedback and testing and are subject to change.</p>\n",
     "\n",
     "</div>\n",
-    "\n"
+    "\n",
+    "Prerequisites\n",
+    "=============\n",
+    "\n",
+    "-   PyTorch v2.7.0 or later\n"
    ]
   },
   {

_downloads/3195443a0ced3cabc0ad643537bdb5cd/introyt1_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "3fbaa42d",
+   "id": "38a1560c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "631e54b6",
+   "id": "94e89df5",
    "metadata": {},
    "source": [
     "\n",

_downloads/4355e2cef7d17548f1e25f97a62828c4/template_tutorial.ipynb

@@ -31,7 +31,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "243e20eb",
+   "id": "160d42d0",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d87c0429",
+   "id": "fdaab039",
    "metadata": {},
    "source": [
     "\n",

_downloads/63a0f0fc7b3ffb15d3a5ac8db3d521ee/tensors_deeper_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "fdaed460",
+   "id": "311f734b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e50880ea",
+   "id": "8c4830b3",
    "metadata": {},
    "source": [
     "\n",

_downloads/770632dd3941d2a51b831c52ded57aa2/trainingyt.ipynb

@@ -35,7 +35,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b05c97eb",
+   "id": "b0b01bc5",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3d043e79",
+   "id": "5959d669",
    "metadata": {},
    "source": [
     "\n",

_downloads/bcb9aa4fd3968b85310b970dbd86bbc3/foreach_map.py

@@ -1,6 +1,6 @@
 """
-(beta) Explicit horizontal fusion with foreach_map and torch.compile
-============================================================
+Explicit horizontal fusion with foreach_map and torch.compile
+===============================================================
 
 **Author:** `Michael Lazos <https://github.com/mlazos>`_
 """
@@ -13,11 +13,17 @@
 #  allows conversion of any pointwise op in ``torch`` to a horiztonally fused foreach
 #  variant. In this tutorial, we will demonstrate how to implement the Adam optimizer
 #  with ``foreach_map`` to generate a fully fused kernel.  
-# 
 #
 # .. note::
 #
-#    This tutorial requires PyTorch 2.7.0 or later.
+#    This recipe describes a prototype feature. Prototype features are typically
+#    at an early stage for feedback and testing and are subject to change.
+#
+# Prerequisites
+# -------------
+#
+# * PyTorch v2.7.0 or later
+#
 
 #####################################################################
 # Model Setup

_downloads/c28f42852d456daf9af72da6c6909556/captumyt.ipynb

@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "bcbad24c",
+   "id": "af36484e",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4e80cc63",
+   "id": "810442ef",
    "metadata": {},
    "source": [
     "\n",

_downloads/e2e556f6b4693c2cef716dd7f40caaf6/tensorboardyt_tutorial.ipynb

@@ -35,7 +35,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2ffcd889",
+   "id": "dce6995f",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ad903238",
+   "id": "26e77e7c",
    "metadata": {},
    "source": [
     "\n",

_downloads/ed9d4f94afb79f7dada6742a06c486a5/autogradyt_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "44844848",
+   "id": "7f1dbea4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "2321d663",
+   "id": "c0294452",
    "metadata": {},
    "source": [
     "\n",

_downloads/fe726e041160526cf828806536922cf6/modelsyt_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e9ca788f",
+   "id": "de2324fa",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3f5a7f48",
+   "id": "71a624e5",
    "metadata": {},
    "source": [
     "\n",