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Fix Typo in Autograd Documentation for Gradient Description (Fixes #41) #42

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Fix Typo in Autograd Documentation for Gradient Description (Fixes #41) #42

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1 change: 1 addition & 0 deletions .gitignore
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@@ -1 +1,2 @@
*.swp
.aider*
2 changes: 1 addition & 1 deletion autograd/two_layer_net_autograd.py
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Expand Up @@ -13,7 +13,7 @@
through the graph to compute gradients of some downstream (scalar) loss with
respect to a Tensor. Concretely if x is a Tensor with x.requires_grad == True
then after backpropagation x.grad will be another Tensor holding the gradient
of x with respect to some scalar value.
of scalar (usually loss) with respect to x.
"""

device = torch.device('cpu')
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