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2 changes: 1 addition & 1 deletion beginner_source/blitz/neural_networks_tutorial.py
Original file line number Diff line number Diff line change
Expand Up @@ -176,7 +176,7 @@ def num_flat_features(self, x):
# -> loss
#
# So, when we call ``loss.backward()``, the whole graph is differentiated
# w.r.t. the loss, and all Tensors in the graph that has ``requires_grad=True``
# w.r.t. the loss, and all Tensors in the graph that have ``requires_grad=True``
# will have their ``.grad`` Tensor accumulated with the gradient.
#
# For illustration, let us follow a few steps backward:
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