mirror of https://github.com/llvm/torch-mlir
738d45d3bb
1. Adds case handling for `aten.slice.tensor` shape inference with negative strides. This is not technically allowed by native pytorch, but it is useful for ONNX ingest. We were getting some incorrect shapes for these negative strided slice ops. 2. Adds scalarization support for ops seen in pytorch pad exports to ONNX. These are typically `aten.view` `aten.transpose.int` and `aten.slice.Tensor` with negative strides (and rank 2). 3. Allows view op `self` to be added to the worklist conditionally, based on whether the view op actually occurs as a middle point in a shape computation. |
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| .. | ||
| e2e_testing | ||
| examples | ||
| python | ||
| test | ||
| tools | ||
| CMakeLists.txt | ||