Add changing default device recipe

Signed-off-by: Edward Z. Yang <[email protected]>

Author: ezyang

recipes_source/recipes/changing_default_device.py

@@ -0,0 +1,43 @@
+"""
+Changing default device
+=======================
+It is common to want to write PyTorch code in a device agnostic way,
+and then switch between CPU and CUDA depending on what hardware is available.
+Traditionally, to do this you might have used if-statements and cuda() calls
+to do this:
+"""
+
+import torch
+
+USE_CUDA = False
+
+mod = torch.nn.Linear(20, 30)
+if USE_CUDA:
+    mod.cuda()
+
+device = 'cpu'
+if USE_CUDA:
+    device = 'cuda'
+inp = torch.randn(128, 20, device=device)
+print(mod(inp).device)
+
+# PyTorch now also has a context manager which can take care of the
+# device transfer automatically.
+
+with torch.device('cuda'):
+    mod = torch.nn.Linear(20, 30)
+    print(mod.weight.device)
+    print(mod(torch.randn(128, 20)).device)
+
+# You can also set it globally
+
+torch.set_default_device('cuda')
+
+mod = torch.nn.Linear(20, 30)
+print(mod.weight.device)
+print(mod(torch.randn(128, 20)).device)
+
+# This function imposes a slight performance cost on every Python
+# call to the torch API (not just factory functions).  If this
+# is causing problems for you, please comment on
+# https://github.com/pytorch/pytorch/issues/92701