samples/microbenchmarks/conv1x1_test.mlir

module {
  func.func @main(%arg0: tensor<1x112x112x8xi8>) -> tensor<1x112x112x16xi8> {
    %0 = "tosa.const"() {value = dense<[-918, -4433, 87, -234, -21393, 7738, 529, -8835, -16817, -375, -199, 572, 5082, 15569, -186, 4955]> : tensor<16xi32>} : () -> tensor<16xi32>
    %1 = "tosa.const"() {value = dense<"0xE2E2E2E2E2EBF6E206E2E2E8EBE6DEE2E0E2E2FDDCE7E1E2E2E2E2FDDFE6E0E3EBE2E2DCEFAC213DE2E2E2E3E2D3C9E4E2E2E2E2E3E1E1FA3EE2E2E9E9E5E3E47FE2E2E4EDE2E2E3E0E2E2E4DFE9DCFEE3E2E2E2E2E2E2E2F9E2E2E6EBEADCE4E2E2E2CEE5E1E0E181E2E2D9D3DEE1DDE2E2E2E2E2E2E2E2C5E2E2E2DBE1E3E1"> : tensor<16x1x1x8xi8>} : () -> tensor<16x1x1x8xi8>
    %2 = "tosa.conv2d"(%arg0, %1, %0) {dilation = [1, 1], pad = [0, 0, 0, 0], quantization_info = #tosa.conv_quant<input_zp = -128, weight_zp = -30>, stride = [1, 1]} : (tensor<1x112x112x8xi8>, tensor<16x1x1x8xi8>, tensor<16xi32>) -> tensor<1x112x112x16xi32>
    %3 = "tosa.rescale"(%2) {double_round = true, input_zp = 0 : i32, multiplier = [1364139008 : i32], output_zp = -128 : i32, per_channel = false, scale32 = true, shift = [35 : i32]} : (tensor<1x112x112x16xi32>) -> tensor<1x112x112x16xi8>
    return %3 : tensor<1x112x112x16xi8>
  }
}