Added support of subfunction for VLMs #699
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Signed-off-by: Abhishek Kumar Singh <[email protected]>
abhishek-singh591
requested review from
ochougul,
quic-amitraj,
quic-hemagnih and
quic-rishinr
as code owners
ochougul
requested changes
Jan 7, 2026
| - update the hidden_states, and fix for onnx model | ||
| """ | ||
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| def get_repeated_layer_class(self) -> Type[nn.Module]: |
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rename to get_submodules_for_export
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okay will do.
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| cos = torch.cat([cos[0, ..., 0:32], cos[0, ..., 32:80], cos[0, ..., 80:128]], dim=-1).unsqueeze(0) | ||
| sin = torch.cat([sin[0, ..., 0:32], sin[0, ..., 32:80], sin[0, ..., 80:128]], dim=-1).unsqueeze(0) |
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To get around (Split: Non-constant split tensor not supported) issue, although some tests are still pending. will let you know here.
| try: | ||
| _C._jit_pass_onnx_track_scope_attributes(graph, onnx_attrs) | ||
| except Exception as e: | ||
| logger.warning(f"Failed to track ONNX scope attributes: {e}. Skipping this step.") |
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why warning?
We should fail here if _C._jit_pass_onnx_track_scope_attributes(graph, onnx_attrs) fails
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This is a hacky workaround for the issue. if you remember previously, we use to pass empty onnx_attrs. for VLMs there are additional issue now. We are skipping the failing step though it does not impact model execution.
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