V-aerus commented on code in PR #19937:
URL: https://github.com/apache/tvm/pull/19937#discussion_r3523202149
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python/tvm/relax/frontend/torch/base_fx_graph_translator.py:
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@@ -2619,6 +2619,16 @@ def _masked_select(self, node: fx.Node) -> relax.Var:
data_flat = self.block_builder.emit(relax.op.reshape(data, [-1]))
mask_flat = self.block_builder.emit(relax.op.reshape(mask, [-1]))
indices = self.block_builder.emit(relax.op.nonzero(mask_flat))
+ tensor_meta = node.meta.get("tensor_meta")
+ if tensor_meta is not None and len(tensor_meta.shape) == 1:
+ num_selected = tensor_meta.shape[0]
+ if not isinstance(num_selected, int):
+ num_selected = tirx.Var(str(num_selected), "int64")
+ else:
+ num_selected = tirx.Var(f"{node.name}_num_selected", "int64")
+ indices = self.block_builder.match_cast(
+ indices, relax.TensorType([1, num_selected], "int64")
+ )
Review Comment:
Thanks for the review. I checked the current TVM Relax API and existing code
patterns. `BlockBuilder.match_cast` is used with `relax.TensorType(shape,
dtype)` in the current codebase, for example in
`tests/python/relax/test_blockbuilder_core.py`, and the ONNX frontend has a
similar `nonzero ->
match_cast` pattern using `relax.TensorType([1, num_nonzero], "int64")`.
Also, in this TVM version, `relax.TensorType` accepts a shape and dtype. I
don't see `relax.TensorStructInfo` being used in the current tree. The current
code passes the targeted masked_select tests, so I will keep this as
`TensorType` unless maintainers prefer a different API.
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