mirror of https://github.com/llvm/torch-mlir
71d90788d3
This PR support `aten.view` with unique unknown dimension both in input
shape and output shape while the pass convert-torch-to-linalg that
lowing `aten.view` to `tensor.collapse_shape` or `tensor.expand_shape`.
Below is an example
```
func.func @test_reshape(%arg0: !torch.vtensor<[1,?,50,16],f32>) -> !torch.vtensor<[1,?,16],f32> attributes {torch.assume_strict_symbolic_shapes, torch.onnx_meta.ir_version = 9 : si64, torch.onnx_meta.opset_version = 19 : si64, torch.onnx_meta.producer_name = "backend-test", torch.onnx_meta.producer_version = ""} {
%int1 = torch.constant.int 1
%int-1 = torch.constant.int -1
%int16 = torch.constant.int 16
%0 = torch.prim.ListConstruct %int1, %int-1, %int16 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int>
%1 = torch.aten.view %arg0, %0 : !torch.vtensor<[1,?,50,16],f32>, !torch.list<int> -> !torch.vtensor<[1,?,16],f32>
return %1 : !torch.vtensor<[1,?,16],f32>
}
```
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|---|---|---|
| .. | ||
| CAPI | ||
| Conversion | ||
| Dialect | ||
| RefBackend | ||
| CMakeLists.txt | ||
| InitAll.cpp | ||