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Add tests for Torch to Linalg backend pipeline
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test/Dialect/TorchConversion/torch-backend-to-linalg-on-tensors-no-contract-check.mlir
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| @@ -0,0 +1,24 @@ | ||
| // RUN: torch-mlir-opt -p 'builtin.module(torch-backend-to-linalg-on-tensors-backend-pipeline{verify=0})' -split-input-file %s | FileCheck %s | ||
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| // CHECK: func.func @tosa | ||
| func.func @tosa(%arg0: tensor<?x?xf32>) -> tensor<?x?xf32> { | ||
| // CHECK: tosa.abs | ||
| %1 = tosa.abs %arg0 : (tensor<?x?xf32>) -> tensor<?x?xf32> | ||
| return %1 : tensor<?x?xf32> | ||
| } | ||
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| // ----- | ||
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| // CHECK: func.func @torch_gemm | ||
| func.func @torch_gemm(%arg0: tensor<?x3xf32>, %arg1: tensor<3x?xf32>, %arg2: tensor<?x?xf32>) -> (tensor<?x?xf32> {onnx.name = "gemm"}) attributes {torch.onnx_meta.opset_version = 19 : si64} { | ||
| %0 = torch_c.from_builtin_tensor %arg0 : tensor<?x3xf32> -> !torch.vtensor<[?,3],f32> | ||
| %1 = torch_c.from_builtin_tensor %arg1 : tensor<3x?xf32> -> !torch.vtensor<[3,?],f32> | ||
| %2 = torch_c.from_builtin_tensor %arg2 : tensor<?x?xf32> -> !torch.vtensor<[?,?],f32> | ||
| %int0 = torch.constant.int 0 | ||
| %int1 = torch.constant.int 1 | ||
| %3 = torch.aten.mm %0, %1 : !torch.vtensor<[?,3],f32>, !torch.vtensor<[3,?],f32> -> !torch.vtensor<[?,?],f32> | ||
| %4 = torch.aten.add.Tensor %3, %2, %int1 : !torch.vtensor<[?,?],f32>, !torch.vtensor<[?,?],f32>, !torch.int -> !torch.vtensor<[?,?],f32> | ||
| %5 = torch_c.to_builtin_tensor %4 : !torch.vtensor<[?,?],f32> -> tensor<?x?xf32> | ||
| %6 = tosa.abs %5 : (tensor<?x?xf32>) -> tensor<?x?xf32> | ||
| return %6 : tensor<?x?xf32> | ||
| } |
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test/Dialect/TorchConversion/torch-backend-to-linalg-on-tensors-no-mlprogram.mlir
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,17 @@ | ||
| // RUN: torch-mlir-opt -p 'builtin.module(torch-backend-to-linalg-on-tensors-backend-pipeline{use-mlprogram=0})' -split-input-file %s | FileCheck %s | ||
| // RUN: torch-mlir-opt -p 'builtin.module(torch-backend-to-linalg-on-tensors-backend-pipeline{use-mlprogram=1})' -split-input-file %s | FileCheck --check-prefix=YES-CHECK %s | ||
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| // CHECK-NOT: ml_program.global{{.*}}@global_seed | ||
| // YES-CHECK: ml_program.global{{.*}}@global_seed | ||
| // CHECK: func.func @torch_gemm | ||
| func.func @torch_gemm(%arg0: tensor<?x3xf32>, %arg1: tensor<3x?xf32>, %arg2: tensor<?x?xf32>) -> (tensor<?x?xf32> {onnx.name = "gemm"}) attributes {torch.onnx_meta.opset_version = 19 : si64} { | ||
| %0 = torch_c.from_builtin_tensor %arg0 : tensor<?x3xf32> -> !torch.vtensor<[?,3],f32> | ||
| %1 = torch_c.from_builtin_tensor %arg1 : tensor<3x?xf32> -> !torch.vtensor<[3,?],f32> | ||
| %2 = torch_c.from_builtin_tensor %arg2 : tensor<?x?xf32> -> !torch.vtensor<[?,?],f32> | ||
| %int0 = torch.constant.int 0 | ||
| %int1 = torch.constant.int 1 | ||
| %3 = torch.aten.mm %0, %1 : !torch.vtensor<[?,3],f32>, !torch.vtensor<[3,?],f32> -> !torch.vtensor<[?,?],f32> | ||
| %4 = torch.aten.add.Tensor %3, %2, %int1 : !torch.vtensor<[?,?],f32>, !torch.vtensor<[?,?],f32>, !torch.int -> !torch.vtensor<[?,?],f32> | ||
| %5 = torch_c.to_builtin_tensor %4 : !torch.vtensor<[?,?],f32> -> tensor<?x?xf32> | ||
| return %5 : tensor<?x?xf32> | ||
| } |