gemini-code-assist[bot] commented on code in PR #19672:
URL: https://github.com/apache/tvm/pull/19672#discussion_r3354052581
##########
python/tvm/relax/frontend/onnx/onnx_frontend.py:
##########
@@ -1814,13 +1817,42 @@ def _impl_v1(cls, bb, inputs, attr, params):
padding=attr.get("pads", 0),
output_padding=output_padding,
dilation=dilations,
- groups=attr.get("group", 1),
+ groups=groups,
data_layout=data_layout,
kernel_layout=kernel_layout,
)
if inputs[2] is not None:
- bias = relax.op.reshape(inputs[2], [1, -1] + [1] * (ndim - 2))
+ bias_shape = inputs[2].struct_info.shape
+ if hasattr(inputs[2].struct_info, "ndim"):
+ bias_ndim = inputs[2].struct_info.ndim
+ else:
+ bias_ndim = len(bias_shape)
Review Comment:
Using `hasattr(inputs[2].struct_info, "ndim")` to check for the presence of
`ndim` is safe, but if `inputs[2].struct_info` does not have `ndim` and
`bias_shape` is `None` (which can happen if the shape is completely
dynamic/unknown), calling `len(bias_shape)` will raise a `TypeError`. We should
add a fallback or check to ensure `bias_shape` is not `None` before calling
`len()` on it.
```suggestion
if hasattr(inputs[2].struct_info, "ndim") and
inputs[2].struct_info.ndim is not None:
bias_ndim = inputs[2].struct_info.ndim
elif bias_shape is not None:
bias_ndim = len(bias_shape)
else:
bias_ndim = -1
```
##########
python/tvm/relax/frontend/onnx/onnx_frontend.py:
##########
@@ -1814,13 +1817,42 @@ def _impl_v1(cls, bb, inputs, attr, params):
padding=attr.get("pads", 0),
output_padding=output_padding,
dilation=dilations,
- groups=attr.get("group", 1),
+ groups=groups,
data_layout=data_layout,
kernel_layout=kernel_layout,
)
if inputs[2] is not None:
- bias = relax.op.reshape(inputs[2], [1, -1] + [1] * (ndim - 2))
+ bias_shape = inputs[2].struct_info.shape
+ if hasattr(inputs[2].struct_info, "ndim"):
+ bias_ndim = inputs[2].struct_info.ndim
+ else:
+ bias_ndim = len(bias_shape)
+ if bias_ndim != 1:
+ raise ValueError(f"ConvTranspose bias must be a 1D tensor, but
got ndim={bias_ndim}")
+
+ def _as_static_int(dim):
+ try:
+ return int(dim)
+ except (TypeError, ValueError, TVMError):
+ return None
Review Comment:
The `_as_static_int` helper catches `TVMError`, but in some environments or
FFI boundaries, TVM might raise a standard `RuntimeError` or other custom
exceptions. To make this helper more robust and prevent unexpected compilation
failures, we should also catch `RuntimeError`.
```suggestion
def _as_static_int(dim):
try:
return int(dim)
except (TypeError, ValueError, RuntimeError, TVMError):
return None
```
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