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Replace _graphdef with _ for unused variables in NNX tutorials #307

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Merged
da-niao-dan merged 2 commits into from
Dec 19, 2025
Merged

Replace _graphdef with _ for unused variables in NNX tutorials #307

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Copilot Dec 19, 2025
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Replace _graphdef with _ for unused variables
Copilot Dec 19, 2025
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4 changes: 2 additions & 2 deletions tutorials/v1/device/08_initialize_nnx_on_device.py
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Original file line number Diff line number Diff line change
Expand Up @@ -84,7 +84,7 @@ def init_model_logic(input_dim: int, hidden_dim: int, output_dim: int, seed: int
)

# Split and convert state to pure dict
_graphdef, state = nnx.split(model)
_, state = nnx.split(model)
state_dict = state.to_pure_dict()

print(f"[Device P0] Initialized model with {len(state_dict)} parameter groups")
Expand Down Expand Up @@ -180,7 +180,7 @@ def init_model_with_optimizer_logic(
)

# Split and convert model state to pure dict
_graphdef, state = nnx.split(model)
_, state = nnx.split(model)
model_state_dict = state.to_pure_dict()

# Initialize optimizer and convert its state to pure dict
Expand Down
6 changes: 3 additions & 3 deletions tutorials/v1/device/09_split_learning_vertical.py
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Original file line number Diff line number Diff line change
Expand Up @@ -646,14 +646,14 @@ def initialize_and_train_split_learning(

def _init_alice_base():
model = AliceBaseModel(input_dim=m1, hidden_dim=h1, rngs=nnx.Rngs(seed_alice))
_graphdef, state = nnx.split(model)
_, state = nnx.split(model)
tx = optax.sgd(learning_rate)
opt_state = tx.init(state.to_pure_dict())
return model_state_to_dict(state, opt_state, 0)

def _init_bob_base():
model = BobBaseModel(input_dim=m2, hidden_dim=h2, rngs=nnx.Rngs(seed_bob))
_graphdef, state = nnx.split(model)
_, state = nnx.split(model)
tx = optax.sgd(learning_rate)
opt_state = tx.init(state.to_pure_dict())
return model_state_to_dict(state, opt_state, 0)
Expand All @@ -665,7 +665,7 @@ def _init_alice_agg():
output_dim=n_classes,
rngs=nnx.Rngs(seed_agg),
)
_graphdef, state = nnx.split(model)
_, state = nnx.split(model)
tx = optax.sgd(learning_rate)
opt_state = tx.init(state.to_pure_dict())
return model_state_to_dict(state, opt_state, 0)
Expand Down