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beginner_source/blitz/cifar10_tutorial.py

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@@ -252,7 +252,7 @@ def forward(self, x):
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# calculate outputs by running images through the network
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outputs = net(images)
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# the class with the highest energy is what we choose as prediction
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_, predicted = torch.max(outputs.data, 1)
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_, predicted = torch.max(outputs, 1)
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total += labels.size(0)
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correct += (predicted == labels).sum().item()
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prototype_source/flight_recorder_tutorial.rst

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@@ -214,7 +214,6 @@ For demonstration purposes, we named this program ``crash.py``.
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complexities.
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.. code:: python
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:caption: A crashing example
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import torch
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import torch.distributed as dist

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