Automated tutorials push

Author: pytorchbot

_downloads/11f1adacb7d237f2041ce267ac38abb6/saveloadrun_tutorial.ipynb

@@ -137,8 +137,8 @@
     "We can then load the model as demonstrated below.\n",
     "\n",
     "As described in [Saving and loading\n",
-    "torch.nn.Modules](pytorch.org/docs/main/notes/serialization.html#saving-and-loading-torch-nn-modules),\n",
-    "saving `state_dict`s is considered the best practice. However, below we\n",
+    "torch.nn.Modules](https://pytorch.org/docs/main/notes/serialization.html#saving-and-loading-torch-nn-modules),\n",
+    "saving `state_dict` is considered the best practice. However, below we\n",
     "use `weights_only=False` because this involves loading the model, which\n",
     "is a legacy use case for `torch.save`.\n"
    ]

_downloads/3195443a0ced3cabc0ad643537bdb5cd/introyt1_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "350e2e0d",
+   "id": "53a4ac06",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3f37fe0b",
+   "id": "6625516c",
    "metadata": {},
    "source": [
     "\n",

_downloads/3648b0dccaebca71b234070fe2124770/saveloadrun_tutorial.py

@@ -57,8 +57,8 @@
 ########################
 # We can then load the model as demonstrated below.
 #
-# As described in `Saving and loading torch.nn.Modules <pytorch.org/docs/main/notes/serialization.html#saving-and-loading-torch-nn-modules>`__,
-# saving ``state_dict``s is considered the best practice. However,
+# As described in `Saving and loading torch.nn.Modules <https://pytorch.org/docs/main/notes/serialization.html#saving-and-loading-torch-nn-modules>`_,
+# saving ``state_dict`` is considered the best practice. However,
 # below we use ``weights_only=False`` because this involves loading the
 # model, which is a legacy use case for ``torch.save``.
 

_downloads/4355e2cef7d17548f1e25f97a62828c4/template_tutorial.ipynb

@@ -31,7 +31,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b582101f",
+   "id": "4b83c984",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fe79e3e1",
+   "id": "b4bbc786",
    "metadata": {},
    "source": [
     "\n",

_downloads/63a0f0fc7b3ffb15d3a5ac8db3d521ee/tensors_deeper_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "975f3d7c",
+   "id": "3f26ccf4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "518c7e13",
+   "id": "93335a06",
    "metadata": {},
    "source": [
     "\n",

_downloads/770632dd3941d2a51b831c52ded57aa2/trainingyt.ipynb

@@ -35,7 +35,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5e339d4e",
+   "id": "ae50fd58",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "eb3ace20",
+   "id": "51f7a4bb",
    "metadata": {},
    "source": [
     "\n",

_downloads/c28f42852d456daf9af72da6c6909556/captumyt.ipynb

@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "7d3af6d0",
+   "id": "a7cf888f",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "7888cc26",
+   "id": "1932e608",
    "metadata": {},
    "source": [
     "\n",

_downloads/e2e556f6b4693c2cef716dd7f40caaf6/tensorboardyt_tutorial.ipynb

@@ -35,7 +35,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e5134784",
+   "id": "71d69762",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9250741b",
+   "id": "2e6583f2",
    "metadata": {},
    "source": [
     "\n",

_downloads/ed9d4f94afb79f7dada6742a06c486a5/autogradyt_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "dcb0daa4",
+   "id": "10c3037d",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "75ce82e8",
+   "id": "6b726311",
    "metadata": {},
    "source": [
     "\n",

_downloads/fe726e041160526cf828806536922cf6/modelsyt_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "40e30221",
+   "id": "aa6444b2",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "48db8215",
+   "id": "57c33926",
    "metadata": {},
    "source": [
     "\n",