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[Relax][Onnx][BatchNorm] Pass momentum and training_mode into BatchNorm Operator #18704

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Merged
tlopex merged 1 commit into from
Feb 2, 2026
Merged

[Relax][Onnx][BatchNorm] Pass momentum and training_mode into BatchNorm Operator #18704

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12 changes: 11 additions & 1 deletion python/tvm/relax/frontend/onnx/onnx_frontend.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2435,8 +2435,18 @@ def _impl_v15(cls, bb, inputs, attr, params):
mean = inputs[3]
var = inputs[4]
epsilon = attr.get("epsilon", 1e-05)
momentum = attr.get("momentum", 0.9)
training_mode = attr.get("training_mode", 0)
return relax.op.nn.batch_norm(
data, gamma=scale, beta=bias, moving_mean=mean, moving_var=var, epsilon=epsilon, axis=1
data,
gamma=scale,
beta=bias,
moving_mean=mean,
moving_var=var,
axis=1,
epsilon=epsilon,
momentum=momentum,
training=training_mode,

@gemini-code-assist gemini-code-assist Bot Feb 2, 2026

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medium

For clarity and type safety, it's better to explicitly cast training_mode to a boolean. The training parameter of relax.op.nn.batch_norm expects a boolean, and while Python's truthiness handles the integer 0 or 1 correctly, an explicit cast makes the intent clearer and guards against potential issues if the operator's signature becomes stricter in the future.

Suggested change
training=training_mode,
training=bool(training_mode),

)


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