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Add graph surgery for scalar tensor constants - #2791
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Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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🟡 Changes recommended
The surgery can replace unresolved intermediate metadata with an incompatible INT64 tensor and emit an invalid Constant for opset-11 models.
2 open issues
What changed in this PR
Adds ReplaceTensorWithConstant to Olive’s ONNX graph surgeries, allowing a named scalar INT64 tensor’s producer to be replaced with a constant while pruning unused upstream nodes.
Changes:
- Adds tensor lookup, producer validation, and signed 64-bit value validation.
- Preserves shared outputs while removing unused computation.
- Adds runtime checks and tests for invalid targets and replacement values.
| File | Description |
|---|---|
test/passes/onnx/test_graph_surgeries.py |
Tests pruning, shared-output preservation, runtime results, and invalid inputs. |
olive/passes/onnx/graph_surgeries.py |
Implements constant replacement and unused-node cleanup. |
Review effort: Balanced
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| if output.dtype not in (None, ir.DataType.INT64) or (output.shape is not None and len(output.shape) != 0): | ||
| raise ValueError(f"Tensor '{self.tensor_name}' must be scalar INT64.") |
| node.domain = "" | ||
| node.op_type = "Constant" | ||
| node.attributes.clear() | ||
| node.attributes["value_int"] = ir.AttrInt64("value_int", self.value) |
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I feel like this is something that can be generalized. For example, would it make sense if you allow a map as input, so users don't need to run the pass multiple times to replace tensors? Additionally, it seems like we can just allow users to replace some value with some arbitrary dtype matching constant?
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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Describe your changes
Add ReplaceTensorWithConstant , a graph surgery that replaces a named scalar INT64 tensor’s producer with an integer Constant and removes unused upstream nodes. Add focused tests for shared outputs and invalid inputs.
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