gemini-code-assist[bot] commented on code in PR #19772:
URL: https://github.com/apache/tvm/pull/19772#discussion_r3410325148
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python/tvm/relax/frontend/onnx/onnx_frontend.py:
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@@ -3834,8 +3834,7 @@ def _impl_v17(cls, bb, inputs, attr, params):
gamma_shape = get_const_tuple(scale.struct_info.shape)
if bias is None:
- seq_len = data.struct_info.shape[1].value
- bias = relax.const([0.0] * seq_len, dtype="float32")
+ bias = relax.const(_np.zeros(gamma_shape,
dtype=scale.struct_info.dtype))
Review Comment:
Using `_np.zeros(gamma_shape, dtype=scale.struct_info.dtype)` will raise a
`TypeError: data type 'bfloat16' not understood` in standard NumPy environments
when the dtype is `"bfloat16"`, as NumPy does not natively support `bfloat16`
without external libraries like `ml_dtypes`.
To prevent this, we should construct the NumPy array with a standard type
like `"float32"` and pass the target dtype to `relax.const`, which natively
supports `"bfloat16"` and handles the conversion correctly. This also aligns
with the pattern mentioned in the PR description.
```suggestion
bias = relax.const(_np.zeros(gamma_shape, dtype="float32"),
dtype=scale.struct_info.dtype)
```
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