Automated tutorials push

Author: pytorchbot

_downloads/3195443a0ced3cabc0ad643537bdb5cd/introyt1_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f93222ca",
+   "id": "6a684e1b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5d9dfe2a",
+   "id": "87e9ac7b",
    "metadata": {},
    "source": [
     "\n",

_downloads/4355e2cef7d17548f1e25f97a62828c4/template_tutorial.ipynb

@@ -31,7 +31,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2b41f878",
+   "id": "86475651",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0ca8d09a",
+   "id": "635d0831",
    "metadata": {},
    "source": [
     "\n",

_downloads/57114670a041b4c96ed6eb9fc17a6b3f/transformer_building_blocks.py

@@ -1,4 +1,7 @@
 """
+.. meta::
+  :description: Learn how to optimize transformer models by replacing nn.Transformer with Nested Tensors and torch.compile() for significant performance gains in PyTorch.
+
 Accelerating PyTorch Transformers by replacing ``nn.Transformer`` with Nested Tensors and ``torch.compile()``
 =============================================================================================================
 **Author:** `Mikayla Gawarecki <https://github.com/mikaylagawarecki>`_

_downloads/63a0f0fc7b3ffb15d3a5ac8db3d521ee/tensors_deeper_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "66d15d76",
+   "id": "02fd62c5",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3402a303",
+   "id": "44437ff8",
    "metadata": {},
    "source": [
     "\n",

_downloads/770632dd3941d2a51b831c52ded57aa2/trainingyt.ipynb

@@ -35,7 +35,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6660a7b4",
+   "id": "e11681ba",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b1058cad",
+   "id": "a10d4513",
    "metadata": {},
    "source": [
     "\n",

_downloads/c28f42852d456daf9af72da6c6909556/captumyt.ipynb

@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "f0f86bc0",
+   "id": "eb22ee32",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c0c48c20",
+   "id": "072a548b",
    "metadata": {},
    "source": [
     "\n",

_downloads/c64acc5fdbf3a35d59b5e6c99e984337/nestedtensor.py

@@ -369,3 +369,8 @@ def benchmark(func, *args, **kwargs):
 # how implement multi-head attention for transformers in a way that avoids computation on padding.
 # For more information, check out the docs for the
 # `torch.nested <https://pytorch.org/docs/stable/nested.html>`__ namespace.
+#
+# See Also
+# --------
+#
+# * `Accelerating PyTorch Transformers by replacing nn.Transformer with Nested Tensors and torch.compile() <https://docs.pytorch.org/tutorials/intermediate/transformer_building_blocks.html`__

_downloads/db9e0933e73063322e250e5d0cec413d/nestedtensor.ipynb

@@ -669,7 +669,14 @@
     "nested tensors and how implement multi-head attention for transformers\n",
     "in a way that avoids computation on padding. For more information, check\n",
     "out the docs for the\n",
-    "[torch.nested](https://pytorch.org/docs/stable/nested.html) namespace.\n"
+    "[torch.nested](https://pytorch.org/docs/stable/nested.html) namespace.\n",
+    "\n",
+    "See Also\n",
+    "========\n",
+    "\n",
+    "-   [Accelerating PyTorch Transformers by replacing nn.Transformer with\n",
+    "    Nested Tensors and torch.compile()\n",
+    "    \\<https://docs.pytorch.org/tutorials/intermediate/transformer\\_building\\_blocks.html]{.title-ref}\\_\\_\n"
    ]
   }
  ],

_downloads/e201125c39959609ca168c306995205c/transformer_building_blocks.ipynb

@@ -17,6 +17,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "::: {.meta description=\"Learn how to optimize transformer models by replacing nn.Transformer with Nested Tensors and torch.compile() for significant performance gains in PyTorch.\"}\n",
+    ":::\n",
+    "\n",
     "Accelerating PyTorch Transformers by replacing `nn.Transformer` with Nested Tensors and `torch.compile()`\n",
     "=========================================================================================================\n",
     "\n",

_downloads/e2e556f6b4693c2cef716dd7f40caaf6/tensorboardyt_tutorial.ipynb

@@ -35,7 +35,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "fa642d58",
+   "id": "bbb98c4c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4ccddece",
+   "id": "d51e9f58",
    "metadata": {},
    "source": [
     "\n",