torch-mlir/test/Dialect
Thomas Dietert 3c33dbd987
[MLIR][Torch] Canonicalize torch.from_i1 and torch.to_i1 (#3067)
When lowering `torch.aten.convolution`, it is expected that the
'transposed' argument is a torch.constant operation. In some cases, the
argument was a `from_i1` operation converting an `arith.constant`
operation into a torch.bool. This is not wrong semantically, but instead
of generalizing the legality of the `torch.aten.convolution` op, we
canonicalize `arith.constant` ops followed by `from_i1` ops to
`torch.bool` ops.

For example:
```
//===-------------------------------------------===//
Legalizing operation : 'torch.aten.convolution'(0x124705b90) {
  %33 = "torch.aten.convolution"(%arg0, %20, %21, %31, %29, %30, %19, %32, %0) : (!torch.vtensor<[1,1,28,28],f32>, !torch.vtensor<[10,1,5,5],f32>, !torch.vtensor<[10],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int) -> !torch.vtensor<[1,10,24,24],f32>

  * Fold {
  } -> FAILURE : unable to fold

  * Pattern : 'torch.aten.convolution -> ()' {
    ** Failure : unimplemented: only constant transposed supported.      <-- Resolved by this PR
  } -> FAILURE : pattern failed to match

  * Pattern : 'torch.aten.convolution -> ()' {
    ** Failure : not a supported Scalar to Tensor like op
  } -> FAILURE : pattern failed to match

  * Pattern : 'torch.aten.convolution -> ()' {
    ** Failure : not a supported elementwise op
  } -> FAILURE : pattern failed to match

  * Pattern : 'torch.aten.convolution -> ()' {
    ** Failure : not a supported reduce op
  } -> FAILURE : pattern failed to match
} -> FAILURE : no matched legalization pattern
//===-------------------------------------------===//
<stdin>:21:11: error: failed to legalize operation 'torch.aten.convolution' that was explicitly marked illegal
    %17 = torch.operator "onnx.Conv"(%arg0, %0, %1) {torch.onnx.dilations = [1 : si64, 1 : si64], torch.onnx.group = 1 : si64, torch.onnx.kernel_shape = [5 : si64, 5 : si64], torch.onnx.pads = [0 : si64, 0 : si64, 0 : si64, 0 : si64], torch.onnx.strides = [1 : si64, 1 : si64]} : (!torch.vtensor<[1,1,28,28],f32>, !torch.vtensor<[10,1,5,5],f32>, !torch.vtensor<[10],f32>) -> !torch.vtensor<[1,10,24,24],f32> 
          ^
<stdin>:21:11: note: see current operation: %33 = "torch.aten.convolution"(%arg0, %20, %21, %31, %29, %30, %19, %32, %0) : (!torch.vtensor<[1,1,28,28],f32>, !torch.vtensor<[10,1,5,5],f32>, !torch.vtensor<[10],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool, !torch.list<int>, !torch.int) -> !torch.vtensor<[1,10,24,24],f32>
```

Additionally, we require the canonicalization of `to_i1` operating on a
torch.constant bool to an `arith.constant ... : i1` for the e2e tests to
pass successfully.
2024-04-01 14:25:51 -07:00
..
TMTensor [torch] Rework lowering to tm_tensor.scatter to stop serialization (#2940) 2024-02-27 11:46:57 -08:00
Torch [Torch Dialect] enhance aten.int.tensor's canonicalize (#3058) 2024-03-27 09:51:58 +08:00
TorchConversion [MLIR][Torch] Canonicalize torch.from_i1 and torch.to_i1 (#3067) 2024-04-01 14:25:51 -07:00