torch-mlir/test/Dialect/TorchConversion/verify-invariants-before-ba...

29 lines
1.2 KiB
MLIR

// RUN: torch-mlir-opt -split-input-file -verify-diagnostics %s -torch-verify-invariants-before-backend-lowering
// -----
func @unknown_rank(%arg0: !torch.vtensor<[],f32>) {
// expected-error@+2 {{unsupported by backend lowering: tensor with unknown rank or dtype}}
// expected-note@+1 {{this is likely due to a missing case in RefineTypes}}
%0 = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[],f32>, !torch.vtensor<[],f32> -> !torch.vtensor<*,f32>
return
}
// -----
func @unknown_dtype(%arg0: !torch.vtensor<[],f32>) {
// expected-error@+2 {{unsupported by backend lowering: tensor with unknown rank or dtype}}
// expected-note@+1 {{this is likely due to a missing case in RefineTypes}}
%0 = torch.aten.mul.Tensor %arg0, %arg0 : !torch.vtensor<[],f32>, !torch.vtensor<[],f32> -> !torch.vtensor<[],unk>
return
}
// -----
func @unresolved_operator(%arg0: !torch.vtensor<[],f32>, %arg1: !torch.int) {
// expected-error@+2 {{unsupported by backend lowering: `torch.operator` op}}
// expected-note@+1 {{this is likely due to a missing op that needs to be generated by torch_ods_gen.py}}
torch.operator "aten.mul.Scalar"(%arg0, %arg1) : (!torch.vtensor<[],f32>, !torch.int) -> !torch.vtensor<[],f32>
return
}