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[FRONTEND][ONNX] Make bias input optional in LayerNormalization #17980

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Merged
Hzfengsy merged 1 commit into from
May 15, 2025
Merged

[FRONTEND][ONNX] Make bias input optional in LayerNormalization #17980

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4 changes: 4 additions & 0 deletions python/tvm/relax/frontend/onnx/onnx_frontend.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2489,6 +2489,10 @@ def _impl_v17(cls, bb, inputs, attr, params):
axis = attr.get("axis", -1)
epsilon = attr.get("epsilon", 1e-05)

if bias is None:
seq_len = data.struct_info.shape[1].value
bias = relax.const([0.0] * seq_len, dtype="float32")

output = relax.op.nn.layer_norm(data, scale, bias, axis, epsilon)
# Onnx layernorm has 3 outputs but only the first is used.
# We construct two empty constants for this.
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18 changes: 18 additions & 0 deletions tests/python/relax/test_frontend_onnx.py
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Expand Up @@ -1303,6 +1303,24 @@ def test_layer_norm():
model = helper.make_model(graph, producer_name="layer_norm_test")
check_correctness(model)

# Test case with no bias that is an optional input
layer_norm_node = helper.make_node("LayerNormalization", ["a", "b"], ["d"], epsilon=1e-12)

graph = helper.make_graph(
[layer_norm_node],
"layer_norm_test",
inputs=[
helper.make_tensor_value_info("a", TensorProto.FLOAT, [32, 32]),
helper.make_tensor_value_info("b", TensorProto.FLOAT, [32]),
],
outputs=[
helper.make_tensor_value_info("d", TensorProto.FLOAT, [32, 32]),
],
)

model = helper.make_model(graph, producer_name="layer_norm_test")
check_correctness(model)


# TODO Enable dynamism
@pytest.mark.parametrize("dynamic", [False])
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