mirror of https://github.com/llvm/torch-mlir
21f070e95f
This PR contains three commits to update the validation checks in the ONNX -> Torch conversion pass for the AveragePool, Pad, and Slice operators: > onnx: fix preconditions for lowering AveragePool ops > > The `pads` attribute of the AveragePool operator specifies the value to > pad at both the beginning as well as the end of the axis (see > https://onnx.ai/onnx/operators/onnx__AveragePool.html#attributes), so > the size of this attribute should be twice the rank of the input tensor. > However, our TorchOnnxToTorch bails out early since it incorrectly > compares the pads attribute with the rank (not twice the rank) of the > input tensor. > > This patch fixes the code to match the spec and adds a lit test. > onnx: allow optional constant value for Pad operator > > The `constant_value` input of the onnx.Pad operator is optional (see > https://onnx.ai/onnx/operators/onnx__Pad.html#inputs), but the existing > logic for lowering the operator into the Torch dialect assumes that it > is mandatory. > > This patch makes the attribute optional and constructs a default value > (a list of zeros the size of the input tensor) if the attribute was not > specified. > onnx: fix checks for axes and steps inputs of Slice operator > > The ONNX Spec for the Slice operator allows the `starts` and `ends` > inputs to have fewer indices that the dimensions of the `data` tensor > (see https://onnx.ai/onnx/operators/onnx__Slice.html), but our code > expects these inputs to be as many as the `data` tensor's dimensions. > > More precisely, the spec requires that the `starts` and `ends` inputs > are only as long as the `axes` input, but since the `axes` input is > optional, the default type for the `axes` input has to match the type > for the `starts` and `ends` inputs. Moreover, the number of indices in > the `steps` input also has to match those in the `axes` inputs (instad > of matching the dimensions of the `data` input). > > This patch fixes the checks in the TorchOnnxToTorch conversion so that > they match the ONNX spec. |
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| .. | ||
| simple_ops_a_to_f.mlir | ||
| simple_ops_g_to_p.mlir | ||
| simple_ops_q_to_z.mlir | ||
| unsupported_fb_opt_ops.mlir | ||
| unsupported_simple_ops.mlir | ||