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Clarify model output dimensions in buildmodel tutorial #3968

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Clarify model output dimensions in buildmodel tutorial #3968

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2 changes: 1 addition & 1 deletion beginner_source/basics/buildmodel_tutorial.py
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Expand Up @@ -75,7 +75,7 @@ def forward(self, x):
# along with some `background operations <https://github.com/pytorch/pytorch/blob/270111b7b611d174967ed204776985cefca9c144/torch/nn/modules/module.py#L866>`_.
# Do not call ``model.forward()`` directly!
#
# Calling the model on the input returns a 2-dimensional tensor with dim=0 corresponding to each output of 10 raw predicted values for each class, and dim=1 corresponding to the individual values of each output.
# Calling the model on the input returns a 2-dimensional tensor of shape ``(batch_size, 10)``, with dim=0 corresponding to each sample in the batch and dim=1 corresponding to the raw predicted values (logits) for each of the 10 classes.
# We get the prediction probabilities by passing it through an instance of the ``nn.Softmax`` module.

X = torch.rand(1, 28, 28, device=device)
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