mirror of https://github.com/llvm/torch-mlir
27 lines
1.3 KiB
MLIR
27 lines
1.3 KiB
MLIR
// RUN: npcomp-opt <%s | npcomp-opt | FileCheck %s --dump-input=fail
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// CHECK-LABEL: func @binary_elementwise
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func @binary_elementwise(%arg0: tensor<?xf32>, %arg1: tensor<?xf32>) {
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// CHECK: tcf.add %arg0, %arg1 : (tensor<?xf32>, tensor<?xf32>) -> tensor<?xf32>
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// CHECK: tcf.max %arg0, %arg1 : (tensor<?xf32>, tensor<?xf32>) -> tensor<?xf32>
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// CHECK: tcf.exp %arg0 : tensor<?xf32>
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%0 = tcf.add %arg0, %arg1 : (tensor<?xf32>, tensor<?xf32>) -> tensor<?xf32>
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%1 = tcf.max %arg0, %arg1 : (tensor<?xf32>, tensor<?xf32>) -> tensor<?xf32>
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%2 = tcf.exp %arg0 : tensor<?xf32>
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return
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}
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// CHECK-LABEL: func @matmul
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func @matmul(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>) -> tensor<?x?xf32> {
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// CHECK: tcf.matmul %arg0, %arg1 : (tensor<?x?xf32>, tensor<?x?xf32>) -> tensor<?x?xf32>
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%0 = tcf.matmul %arg0, %arg1 : (tensor<?x?xf32>, tensor<?x?xf32>) -> tensor<?x?xf32>
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return %0 : tensor<?x?xf32>
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}
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// CHECK-LABEL: func @conv_2d_nchw
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func @conv_2d_nchw(%arg0: tensor<?x?x?x?xf32>, %arg1: tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32> {
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// CHECK: tcf.conv_2d_nchw %arg0, %arg1 : (tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
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%0 = tcf.conv_2d_nchw %arg0, %arg1 : (tensor<?x?x?x?xf32>, tensor<?x?x?x?xf32>) -> tensor<?x?x?x?xf32>
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return %0 : tensor<?x?x?x?xf32>
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}
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