Automated tutorials push

Author: pytorchbot

_downloads/76d764ad694d0795e494a1edbfb068a6/buildmodel_tutorial.ipynb

@@ -64,11 +64,10 @@
     "Get Device for Training\n",
     "=======================\n",
     "\n",
-    "We want to be able to train our model on a hardware accelerator like the\n",
-    "GPU or MPS, if available. Let\\'s check to see if\n",
-    "[torch.cuda](https://pytorch.org/docs/stable/notes/cuda.html) or\n",
-    "[torch.backends.mps](https://pytorch.org/docs/stable/notes/mps.html) are\n",
-    "available, otherwise we use the CPU.\n"
+    "We want to be able to train our model on an\n",
+    "[accelerator](https://pytorch.org/docs/stable/torch.html#accelerators)\n",
+    "such as CUDA, MPS, MTIA, or XPU. If the current accelerator is\n",
+    "available, we will use it. Otherwise, we use the CPU.\n"
    ]
   },
   {
@@ -79,13 +78,7 @@
    },
    "outputs": [],
    "source": [
-    "device = (\n",
-    "    \"cuda\"\n",
-    "    if torch.cuda.is_available()\n",
-    "    else \"mps\"\n",
-    "    if torch.backends.mps.is_available()\n",
-    "    else \"cpu\"\n",
-    ")\n",
+    "device = torch.accelerator.current_accelerator().type if torch.accelerator.is_available() else \"cpu\"\n",
     "print(f\"Using {device} device\")"
    ]
   },

_downloads/ac800c8c4c9c372154788058b1e89246/buildmodel_tutorial.py

@@ -32,17 +32,10 @@
 #############################################
 # Get Device for Training
 # -----------------------
-# We want to be able to train our model on a hardware accelerator like the GPU or MPS,
-# if available. Let's check to see if `torch.cuda <https://pytorch.org/docs/stable/notes/cuda.html>`_
-# or `torch.backends.mps <https://pytorch.org/docs/stable/notes/mps.html>`_ are available, otherwise we use the CPU.
-
-device = (
-    "cuda"
-    if torch.cuda.is_available()
-    else "mps"
-    if torch.backends.mps.is_available()
-    else "cpu"
-)
+# We want to be able to train our model on an `accelerator <https://pytorch.org/docs/stable/torch.html#accelerators>`__
+# such as CUDA, MPS, MTIA, or XPU. If the current accelerator is available, we will use it. Otherwise, we use the CPU.
+
+device = torch.accelerator.current_accelerator().type if torch.accelerator.is_available() else "cpu"
 print(f"Using {device} device")
 
 ##############################################