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// RUN: mlir-opt --split-input-file --tosa-optional-decompositions %s | FileCheck %s
// CHECK-LABEL: @transpose_conv2d
func.func @transpose_conv2d(%arg0: tensor<2x16x14x3xf32>, %arg1: tensor<5x3x6x3xf32>, %arg2: tensor<5xf32>) -> tensor<2x18x19x5xf32> {
// CHECK: %[[REV1:.+]] = "tosa.reverse"(%arg1) <{axis = 1 : i64}
// CHECK: %[[REV2:.+]] = "tosa.reverse"(%[[REV1]]) <{axis = 2 : i64}
// CHECK: "tosa.conv2d"(%arg0, %[[REV2]], %arg2)
// CHECK-SAME: dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 5, 5>, stride = array<i64: 1, 1>
%0 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {out_pad = array<i64: 0, 0, 0, 0>, out_shape = array<i64: -1, -1, -1, -1>, stride = array<i64: 1, 1>} : (tensor<2x16x14x3xf32>, tensor<5x3x6x3xf32>, tensor<5xf32>) -> tensor<2x18x19x5xf32>
return %0 : tensor<2x18x19x5xf32>
}
// -----
// CHECK-LABEL: @transpose_conv2d_quantized
func.func @transpose_conv2d_quantized(%arg0: tensor<2x16x14x3xi8>, %arg1: tensor<5x3x6x3xi8>, %arg2: tensor<5xi32>) -> (tensor<2x18x19x5xi32>) {
// CHECK: %[[REV1:.+]] = "tosa.reverse"(%arg1) <{axis = 1 : i64}
// CHECK: %[[REV2:.+]] = "tosa.reverse"(%[[REV1]]) <{axis = 2 : i64}
// CHECK: "tosa.conv2d"(%arg0, %[[REV2]], %arg2) <{dilation = array<i64: 1, 1>, pad = array<i64: 2, 2, 5, 5>, quantization_info = #tosa.conv_quant<input_zp = -22, weight_zp = 42>, stride = array<i64: 1, 1>}
%0 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {out_pad = array<i64: 0, 0, 0, 0>, quantization_info = #tosa.conv_quant<input_zp = -22, weight_zp = 42>, out_shape = array<i64: -1, -1, -1, -1>, stride = array<i64: 1, 1>} : (tensor<2x16x14x3xi8>, tensor<5x3x6x3xi8>, tensor<5xi32>) -> tensor<2x18x19x5xi32>
return %0 : tensor<2x18x19x5xi32>
}
// -----
// CHECK-LABEL: @transpose_conv2d_quantized_padded
func.func @transpose_conv2d_quantized_padded(%arg0: tensor<2x16x14x3xi8>, %arg1: tensor<5x3x6x3xi8>, %arg2: tensor<5xi32>) -> (tensor<2x21x26x5xi32>) {
// CHECK-DAG: %[[REV0:.+]] = "tosa.reverse"(%0) <{axis = 2 : i64}
// CHECK-DAG: %[[REV1:.+]] = "tosa.reverse"(%arg1) <{axis = 1 : i64}
// CHECK: "tosa.conv2d"(%arg0, %1, %arg2)
// CHECK-SAME: dilation = array<i64: 1, 1>, pad = array<i64: 3, 4, 8, 9>,
// CHECK-SAME: quantization_info = #tosa.conv_quant<input_zp = -22, weight_zp = 42>, stride = array<i64: 1, 1>}
%0 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {
out_pad = array<i64: 1, 2, 3, 4>,
quantization_info = #tosa.conv_quant<input_zp = -22, weight_zp = 42>,
out_shape = array<i64: -1, -1, -1, -1>,
stride = array<i64: 1, 1>} : (tensor<2x16x14x3xi8>, tensor<5x3x6x3xi8>, tensor<5xi32>) -> tensor<2x21x26x5xi32>
return %0 : tensor<2x21x26x5xi32>
}
// -----
// CHECK-LABEL: @transpose_conv2d_strided
func.func @transpose_conv2d_strided(%arg0: tensor<2x17x15x3xf32>, %arg1: tensor<5x3x5x3xf32>, %arg2: tensor<5xf32>) -> tensor<2x?x?x5xf32> {
// Manipulate the weight matrix to handle striding.
// CHECK-DAG: %[[PADV:.+]] = "tosa.const"() <{value = dense<{{\[\[}}0, 0], [0, 1], [0, 1], [0, 0]]> : tensor<4x2xi32>}
// CHECK-DAG: %[[TRANSV:.+]] = "tosa.const"() <{value = dense<[2, 4, 0, 1, 3, 5]> : tensor<6xi32>}
// CHECK-DAG: %[[PADW:.+]] = "tosa.pad"(%arg1, %[[PADV]])
// CHECK-DAG: %[[RESW1:.+]] = "tosa.reshape"(%[[PADW]]) <{new_shape = array<i64: 5, 2, 2, 2, 3, 3>}
// CHECK-DAG: %[[TRANS:.+]] = "tosa.transpose"(%[[RESW1]], %[[TRANSV]])
// CHECK-DAG: %[[RESW2:.+]] = "tosa.reshape"(%[[TRANS]]) <{new_shape = array<i64: 30, 2, 2, 3>}
// CHECK-DAG: %[[REV1:.+]] = "tosa.reverse"(%[[RESW2]]) <{axis = 1 : i64}
// CHECK-DAG: %[[NEWWEIGHT:.+]] = "tosa.reverse"(%[[REV1]]) <{axis = 2 : i64}
// Pad out the input matrix to handle the transpose conv.
// CHECK-DAG: %[[PAD:.+]] = "tosa.const"() <{value = dense<{{\[\[}}0, 0], [1, 1], [1, 1], [0, 0]]> : tensor<4x2xi32>}
// CHECK-DAG: %[[TRANS2:.+]] = "tosa.const"() <{value = dense<[0, 1, 3, 2, 4, 5]> : tensor<6xi32>}
// CHECK-DAG: %[[NEWINPUT:.+]] = "tosa.pad"(%arg0, %[[PAD]])
// Manipulate the final shape.
// CHECK-DAG: %[[BIAS:.+]] = "tosa.const"() <{value = dense<0.000000e+00> : tensor<30xf32>}
// CHECK-DAG: %[[CONV:.+]] = "tosa.conv2d"(%[[NEWINPUT]], %[[NEWWEIGHT]], %[[BIAS]]) <{dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, stride = array<i64: 1, 1>}
// CHECK-DAG: %[[RESHAPE_OUT_1:.+]] = "tosa.reshape"(%[[CONV]]) <{new_shape = array<i64: 2, 18, 16, 2, 3, 5>}
// CHECK-DAG: %[[TRANS_OUT:.+]] = "tosa.transpose"(%[[RESHAPE_OUT_1]], %[[TRANS2]])
// CHECK-DAG: %[[RESHAPE_OUT_2:.+]] = "tosa.reshape"(%[[TRANS_OUT]]) <{new_shape = array<i64: 2, 36, 48, 5>}
// CHECK-DAG: %[[SLICE:.+]] = "tosa.slice"(%[[RESHAPE_OUT_2]]) <{size = array<i64: 2, 35, 47, 5>, start = array<i64: 0, 0, 0, 0>}
// CHECK-DAG: %[[RESHAPE_ARG2:.+]] = "tosa.reshape"(%arg2) <{new_shape = array<i64: 1, 1, 1, 5>}
// CHECK: %[[ADD:.+]] = "tosa.add"(%[[SLICE]], %[[RESHAPE_ARG2]])
%0 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {out_pad = array<i64: 0, 0, 0, 0>, out_shape = array<i64: -1, -1, -1, -1>, stride = array<i64: 2, 3>} : (tensor<2x17x15x3xf32>, tensor<5x3x5x3xf32>, tensor<5xf32>) -> tensor<2x35x47x5xf32>
%1 = tensor.cast %0 : tensor<2x35x47x5xf32> to tensor<2x?x?x5xf32>
return %1 : tensor<2x?x?x5xf32>
}
// -----
// CHECK-LABEL: @transpose_conv2d_strided_quantized
func.func @transpose_conv2d_strided_quantized(%arg0: tensor<2x17x15x3xi8>, %arg1: tensor<5x3x5x3xi8>, %arg2: tensor<5xi32>) -> (tensor<2x35x47x5xi32>) {
// Manipulate the weight matrix to handle striding.
// CHECK-DAG: %[[PADV:.+]] = "tosa.const"() <{value = dense<{{\[\[}}0, 0], [0, 1], [0, 1], [0, 0]]> : tensor<4x2xi32>}
// CHECK-DAG: %[[TRANSV:.+]] = "tosa.const"() <{value = dense<[2, 4, 0, 1, 3, 5]> : tensor<6xi32>}
// CHECK-DAG: %[[PADW:.+]] = "tosa.pad"(%arg1, %[[PADV]]) <{quantization_info = #tosa.pad_quant<input_zp = 42>}
// CHECK-DAG: %[[RESW1:.+]] = "tosa.reshape"(%[[PADW]]) <{new_shape = array<i64: 5, 2, 2, 2, 3, 3>}
// CHECK-DAG: %[[TRANS:.+]] = "tosa.transpose"(%[[RESW1]], %[[TRANSV]])
// CHECK-DAG: %[[RESW2:.+]] = "tosa.reshape"(%[[TRANS]]) <{new_shape = array<i64: 30, 2, 2, 3>}
// CHECK-DAG: %[[REV1:.+]] = "tosa.reverse"(%[[RESW2]]) <{axis = 1 : i64}
// CHECK-DAG: %[[NEWWEIGHT:.+]] = "tosa.reverse"(%[[REV1]]) <{axis = 2 : i64}
// Pad out the input matrix to handle the transpose conv.
// CHECK-DAG: %[[PAD:.+]] = "tosa.const"() <{value = dense<{{\[\[}}0, 0], [1, 1], [1, 1], [0, 0]]> : tensor<4x2xi32>}
// CHECK-DAG: %[[TRANS2:.+]] = "tosa.const"() <{value = dense<[0, 1, 3, 2, 4, 5]> : tensor<6xi32>}
// CHECK-DAG: %[[NEWINPUT:.+]] = "tosa.pad"(%arg0, %[[PAD]]) <{quantization_info = #tosa.pad_quant<input_zp = -22>}
// Manipulate the final shape.
// CHECK-DAG: %[[BIAS:.+]] = "tosa.const"() <{value = dense<0> : tensor<30xi32>}
// CHECK-DAG: %[[CONV:.+]] = "tosa.conv2d"(%[[NEWINPUT]], %[[NEWWEIGHT]], %[[BIAS]]) <{dilation = array<i64: 1, 1>, pad = array<i64: 0, 0, 0, 0>, quantization_info = #tosa.conv_quant<input_zp = -22, weight_zp = 42>, stride = array<i64: 1, 1>}
// CHECK-DAG: %[[RESHAPE_OUT_1:.+]] = "tosa.reshape"(%[[CONV]]) <{new_shape = array<i64: 2, 18, 16, 2, 3, 5>}
// CHECK-DAG: %[[TRANS_OUT:.+]] = "tosa.transpose"(%[[RESHAPE_OUT_1]], %[[TRANS2]])
// CHECK-DAG: %[[RESHAPE_OUT_2:.+]] = "tosa.reshape"(%[[TRANS_OUT]]) <{new_shape = array<i64: 2, 36, 48, 5>}
// CHECK-DAG: %[[SLICE:.+]] = "tosa.slice"(%[[RESHAPE_OUT_2]]) <{size = array<i64: 2, 35, 47, 5>, start = array<i64: 0, 0, 0, 0>}
// CHECK-DAG: %[[RESHAPE_ARG2:.+]] = "tosa.reshape"(%arg2) <{new_shape = array<i64: 1, 1, 1, 5>}
// CHECK: %[[ADD:.+]] = "tosa.add"(%[[SLICE]], %[[RESHAPE_ARG2]])
%0 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {out_pad = array<i64: 0, 0, 0, 0>, quantization_info = #tosa.conv_quant<input_zp = -22, weight_zp = 42>, out_shape = array<i64: -1, -1, -1, -1>, stride = array<i64: 2, 3>} : (tensor<2x17x15x3xi8>, tensor<5x3x5x3xi8>, tensor<5xi32>) -> tensor<2x35x47x5xi32>
return %0 : tensor<2x35x47x5xi32>
}
// -----
// CHECK-LABEL: @transpose_conv2d_strided_overpad
func.func @transpose_conv2d_strided_overpad(%arg0 : tensor<1x16x1x1xi8>, %arg1 : tensor<1x2x1x1xi8>, %arg2 : tensor<1xi32>) -> (tensor<1x19x2x1xi32>) {
// CHECK: %[[WEIGHT_PAD:.+]] = "tosa.const"()
// CHECK-SAME{literal}: value = dense<[[0, 0], [0, 0], [0, 1], [0, 0]]> : tensor<4x2xi32>
// CHECK: %[[WEIGHT_PERMS:.+]] = "tosa.const"() <{value = dense<[2, 4, 0, 1, 3, 5]> : tensor<6xi32>}
// CHECK: %[[INPUT_PAD:.+]] = "tosa.const"()
// CHECK-SAME{literal}: value = dense<[[0, 0], [1, 1], [0, 0], [0, 0]]> : tensor<4x2xi32>}
// CHECK: %[[ZERO:.+]] = "tosa.const"() <{value = dense<0> : tensor<2xi32>}
// CHECK: %[[RESULT_PERMS:.+]] = "tosa.const"() <{value = dense<[0, 1, 3, 2, 4, 5]> : tensor<6xi32>}
// CHECK: %[[RESULT_PAD:.+]] = "tosa.const"()
// CHECK-SAME{literal}: value = dense<[[0, 0], [2, 0], [0, 0], [0, 0]]> : tensor<4x2xi32>}
// CHECK: %[[PAD_WEIGHT:.+]] = "tosa.pad"(%arg1, %[[WEIGHT_PAD]]) <{quantization_info = #tosa.pad_quant<input_zp = 93>}
// CHECK: %[[RESHAPE_WEIGHT_0:.+]] = "tosa.reshape"(%[[PAD_WEIGHT]]) <{new_shape = array<i64: 1, 2, 1, 1, 2, 1>}
// CHECK: %[[TRANSPOSE_WEIGHT:.+]] = "tosa.transpose"(%[[RESHAPE_WEIGHT_0]], %[[WEIGHT_PERMS]])
// CHECK: %[[RESHAPE_WEIGHT_1:.+]] = "tosa.reshape"(%[[TRANSPOSE_WEIGHT]]) <{new_shape = array<i64: 2, 2, 1, 1>}
// CHECK: %[[REVERSE:.+]] = "tosa.reverse"(%[[RESHAPE_WEIGHT_1]]) <{axis = 1 : i64}
// CHECK: %[[PAD_INPUT:.+]] = "tosa.pad"(%arg0, %[[INPUT_PAD]]) <{quantization_info = #tosa.pad_quant<input_zp = -103>}
// CHECK: %[[CONV:.+]] = "tosa.conv2d"(%[[PAD_INPUT]], %[[REVERSE]], %[[ZERO]])
// CHECK-SAME{literal}: dilation = [1, 1], pad = [0, 0, 0, 0], quantization_info = #tosa.conv_quant<input_zp = -103, weight_zp = 93>, stride = [1, 1]}
// CHECK: %[[RESHAPE_RESULT_0:.+]] = "tosa.reshape"(%[[CONV]]) <{new_shape = array<i64: 1, 17, 1, 1, 2, 1>}
// CHECK: %[[TRANSPOSE_RESULT:.+]] = "tosa.transpose"(%[[RESHAPE_RESULT_0]], %[[RESULT_PERMS]])
// CHECK: %[[RESHAPE_RESULT_1:.+]] = "tosa.reshape"(%[[TRANSPOSE_RESULT]]) <{new_shape = array<i64: 1, 17, 2, 1>}
// CHECK: %[[PAD_RESULT:.+]] = "tosa.pad"(%[[RESHAPE_RESULT_1]], %[[RESULT_PAD]])
// CHECK: %[[RESHAPE_ARG2:.+]] = "tosa.reshape"(%arg2) <{new_shape = array<i64: 1, 1, 1, 1>}
// CHECK: %[[ADD:.+]] = "tosa.add"(%[[PAD_RESULT]], %[[RESHAPE_ARG2]])
%2 = "tosa.transpose_conv2d"(%arg0, %arg1, %arg2) {
out_pad = array<i64: 2, 0, 0, 1>,
out_shape = array<i64: 1, -1, -1, 1>,
stride = array<i64: 1, 2>,
quantization_info = #tosa.conv_quant<input_zp = -103, weight_zp = 93>} :
(tensor<1x16x1x1xi8>, tensor<1x2x1x1xi8>, tensor<1xi32>) -> (tensor<1x19x2x1xi32>)
"func.return" (%2) : (tensor<1x19x2x1xi32>) -> ()
}
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