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Change order of optimizer.step() in documentation #3006

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Change order of optimizer.step() in documentation #3006

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2 changes: 1 addition & 1 deletion beginner_source/basics/optimization_tutorial.py
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Expand Up @@ -134,9 +134,9 @@ def forward(self, x):

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# Inside the training loop, optimization happens in three steps:
# * Call ``optimizer.zero_grad()`` to reset the gradients of model parameters. Gradients by default add up; to prevent double-counting, we explicitly zero them at each iteration.
# * Backpropagate the prediction loss with a call to ``loss.backward()``. PyTorch deposits the gradients of the loss w.r.t. each parameter.
# * Once we have our gradients, we call ``optimizer.step()`` to adjust the parameters by the gradients collected in the backward pass.
# * Call ``optimizer.zero_grad()`` to reset the gradients of model parameters. Gradients by default add up; to prevent double-counting, we explicitly zero them at each iteration.


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