mirror of https://github.com/llvm/torch-mlir
25 lines
1.3 KiB
MLIR
25 lines
1.3 KiB
MLIR
// RUN: npcomp-opt %s -aten-layer-name -aten-op-report |& FileCheck %s
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// CHECK-LABEL: "L0-batch_norm-0": {
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// CHECK-NEXT: "activation_in": 103320,
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// CHECK-NEXT: "activation_out": 103320,
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// CHECK-NEXT: "ops:*": 310206,
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// CHECK-NEXT: "ops:+": 413280,
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// CHECK-NEXT: "ops:-": 123,
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// CHECK-NEXT: "ops:/": 123,
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// CHECK-NEXT: "ops:sqrt": 123,
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// CHECK-NEXT: "parameters_in": 246,
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// CHECK-NEXT: "reads": 103566,
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// CHECK-NEXT: "writes": 103320
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module {
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func @graph(%arg0: tensor<42x123x4x5xf32>, %arg1: tensor<123xf32>, %arg2: tensor<123xf32>, %arg3: tensor<123xf32>, %arg4: tensor<123xf32>, %arg5: tensor<?xi64>) -> tensor<42x123x4x5xf32> {
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%0 = "aten.constant"() {type = "bool", value = 0 : i1} : () -> i1
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%1 = "aten.constant"() {type = "f32", value = 1.000000e-01 : f32} : () -> f32
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%2 = "aten.constant"() {type = "f32", value = 9.99999974E-6 : f32} : () -> f32
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%3 = "aten.constant"() {type = "bool", value = 1 : i1} : () -> i1
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%4:3 = "aten.batch_norm"(%arg0, %arg1, %arg2, %arg3, %arg4, %0, %1, %2, %3) : (tensor<42x123x4x5xf32>, tensor<123xf32>, tensor
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<123xf32>, tensor<123xf32>, tensor<123xf32>, i1, f32, f32, i1) -> (tensor<42x123x4x5xf32>, tensor<123xf32>, tensor<123xf32>)
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return %4#0 : tensor<42x123x4x5xf32>
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}
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}
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