Automated tutorials push

Author: pytorchbot

_downloads/0ccffddcfee1f815c02241b985844376/torch_compile_user_defined_triton_kernel_tutorial.py

@@ -227,12 +227,6 @@ def sin_kernel(
     output = tl.sin(x)
     tl.store(out_ptr + offsets, output, mask=mask)
 
-def sin_triton(x):
-    out = torch.empty_like(x)
-    n_elements = x.numel()
-    sin_kernel[(n_elements,)](x, out, n_elements, BLOCK_SIZE=4)
-    return out
-
 ######################################################################
 # You can invoke the ``triton_op`` in one of the following two ways.
 

_downloads/3195443a0ced3cabc0ad643537bdb5cd/introyt1_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "fd93c4dd",
+   "id": "08cb6c00",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "13993efb",
+   "id": "76b87d77",
    "metadata": {},
    "source": [
     "\n",

_downloads/4355e2cef7d17548f1e25f97a62828c4/template_tutorial.ipynb

@@ -31,7 +31,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "0b7bd3cd",
+   "id": "c26dff5f",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "4c9e9395",
+   "id": "24e76ea7",
    "metadata": {},
    "source": [
     "\n",

_downloads/63a0f0fc7b3ffb15d3a5ac8db3d521ee/tensors_deeper_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "88e7740c",
+   "id": "a44f97a5",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6aaaa644",
+   "id": "a9601b89",
    "metadata": {},
    "source": [
     "\n",

_downloads/770632dd3941d2a51b831c52ded57aa2/trainingyt.ipynb

@@ -35,7 +35,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c0f2ffb6",
+   "id": "73319286",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "58b8afc8",
+   "id": "f4c949b1",
    "metadata": {},
    "source": [
     "\n",

_downloads/c28f42852d456daf9af72da6c6909556/captumyt.ipynb

@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c49ae6d6",
+   "id": "e14c1480",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "0fec58ed",
+   "id": "0c23d28f",
    "metadata": {},
    "source": [
     "\n",

_downloads/e2e556f6b4693c2cef716dd7f40caaf6/tensorboardyt_tutorial.ipynb

@@ -35,7 +35,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "e8788757",
+   "id": "8c4b1dc8",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a71e84dd",
+   "id": "de347df5",
    "metadata": {},
    "source": [
     "\n",

_downloads/ed9d4f94afb79f7dada6742a06c486a5/autogradyt_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "29285e10",
+   "id": "71e2b25d",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "125f6aa8",
+   "id": "2b11e675",
    "metadata": {},
    "source": [
     "\n",

_downloads/f827f181506a79226f4ffbcf7c9a5a50/torch_compile_user_defined_triton_kernel_tutorial.ipynb

@@ -283,13 +283,7 @@
     "    mask = offsets < n_elements\n",
     "    x = tl.load(in_ptr0 + offsets, mask=mask)\n",
     "    output = tl.sin(x)\n",
-    "    tl.store(out_ptr + offsets, output, mask=mask)\n",
-    "\n",
-    "def sin_triton(x):\n",
-    "    out = torch.empty_like(x)\n",
-    "    n_elements = x.numel()\n",
-    "    sin_kernel[(n_elements,)](x, out, n_elements, BLOCK_SIZE=4)\n",
-    "    return out"
+    "    tl.store(out_ptr + offsets, output, mask=mask)"
    ]
   },
   {

_downloads/fe726e041160526cf828806536922cf6/modelsyt_tutorial.ipynb

@@ -34,7 +34,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "6f1ec145",
+   "id": "2ebda2a4",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -50,7 +50,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d3b40f65",
+   "id": "a3d22bbd",
    "metadata": {},
    "source": [
     "\n",