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Fixed typos in docs_nnx/migrating/pytorch_to_jax_flax.rst #5479

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Fixed typos in docs_nnx/migrating/pytorch_to_jax_flax.rst #5479

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4 changes: 2 additions & 2 deletions docs_nnx/migrating/pytorch_to_jax_flax.rst
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Expand Up @@ -773,7 +773,7 @@ in normalization layers.
.. code-block:: python

model = nnx.view(model, deterministic=False, use_running_average=False)
eval_model = nnx.view(model, deterministic=False, use_running_average=False)
eval_model = nnx.view(model, deterministic=True, use_running_average=True)

for epoch in range(num_epochs):
# run model single epoch training
Expand Down Expand Up @@ -1030,7 +1030,7 @@ Let us first provide an NNX implementation of ResNet50:
model = nnx.eval_shape(lambda : ResNet50(rngs=nnx.Rngs(0)))
graph_def, abs_state = nnx.split(model)
jax_state = nnx.to_pure_dict(abs_state)
print(len(jax_state), list(jax_state.paths)[:3], type(next(iter(jax_state.leaves))))
print(len(jax_state), list(jax_state.keys())[:3], type(next(iter(jax_state.values()))))
# 6 ['fc', 'layer0', 'layer1'] <class 'dict'>

We have to manually create a mapping between pretrained weights keys and our NNX model state keys.
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