forked from OSchip/llvm-project
41 lines
2.1 KiB
MLIR
41 lines
2.1 KiB
MLIR
// RUN: mlir-opt --split-input-file --tosa-optional-decompositions %s | FileCheck %s
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// -----
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// CHECK-LABEL: @conv2d_as_fully_connected
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func @conv2d_as_fully_connected(%arg0: tensor<4x10x10x2xf32>, %arg1: tensor<3x1x1x2xf32>, %arg2: tensor<3xf32>) -> tensor<4x10x10x3xf32> {
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// CHECK-NOT: "tosa.conv2d"
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// CHECK: %[[VAR0:.*]] = "tosa.reshape"(%arg0) {new_shape = [400, 2]}
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// CHECK-SAME: -> tensor<400x2xf32>
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// CHECK: %[[VAR1:.*]] = "tosa.reshape"(%arg1) {new_shape = [3, 2]}
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// CHECK-SAME: -> tensor<3x2xf32>
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// CHECK: %[[VAR2:.*]] = "tosa.fully_connected"(%[[VAR0]], %[[VAR1]], %arg2)
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// CHECK-SAME: -> tensor<400x3xf32>
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// CHECK: %[[VAR3:.*]] = "tosa.reshape"(%[[VAR2]]) {new_shape = [4, 10, 10, 3]}
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// CHECK-SAME: -> tensor<4x10x10x3xf32>
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// CHECK: return %[[VAR3]]
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%0 = "tosa.conv2d"(%arg0, %arg1, %arg2) {pad = [0, 0, 0, 0], stride = [1, 1], dilation = [1, 1]} : (tensor<4x10x10x2xf32>, tensor<3x1x1x2xf32>, tensor<3xf32>) -> tensor<4x10x10x3xf32>
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return %0 : tensor<4x10x10x3xf32>
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}
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// -----
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// CHECK-LABEL: @conv2d_as_fully_connected_quant
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func @conv2d_as_fully_connected_quant(%arg0: tensor<4x10x10x2xi8>, %arg1: tensor<3x1x1x2xi8>, %arg2: tensor<3xi32>) -> tensor<4x10x10x3xi32> {
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// CHECK-NOT: "tosa.conv2d"
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// CHECK: %[[VAR0:.*]] = "tosa.reshape"(%arg0) {new_shape = [400, 2]}
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// CHECK-SAME: -> tensor<400x2xi8>
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// CHECK: %[[VAR1:.*]] = "tosa.reshape"(%arg1) {new_shape = [3, 2]}
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// CHECK-SAME: -> tensor<3x2xi8>
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// CHECK: %[[VAR2:.*]] = "tosa.fully_connected"(%[[VAR0]], %[[VAR1]], %arg2)
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// CHECK-SAME: quantization_info = {input_zp = 42 : i32, weight_zp = 24 : i32}
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// CHECK-SAME: -> tensor<400x3xi32>
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// CHECK: %[[VAR3:.*]] = "tosa.reshape"(%[[VAR2]]) {new_shape = [4, 10, 10, 3]}
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// CHECK-SAME: -> tensor<4x10x10x3xi32>
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// CHECK: return %[[VAR3]]
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%0 = "tosa.conv2d"(%arg0, %arg1, %arg2) {pad = [0, 0, 0, 0], stride = [1, 1], dilation = [1, 1], quantization_info = {input_zp = 42 : i32, weight_zp = 24 : i32}} : (tensor<4x10x10x2xi8>, tensor<3x1x1x2xi8>, tensor<3xi32>) -> tensor<4x10x10x3xi32>
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return %0 : tensor<4x10x10x3xi32>
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}
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// -----
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