// CHECK-DAG:           %[[VAL_5:.*]] = arith.constant dense<[0, 3, 1, 2]> : tensor<4xi32>
// CHECK-DAG:           %[[VAL_6:.*]] = "tfl.transpose"(%[[VAL_4]], %[[VAL_5]]) : (tensor<1x32x32x64xf32>, tensor<4xi32>) -> tensor<1x64x32x32xf32>
// CHECK:           return %[[VAL_6]] : tensor<1x64x32x32xf32>
// CHECK:         }

  func.return %2 : tensor<1x32x32x16xf32>
}

// -----

// CHECK-LABEL: @test_conv2d_qi8

    "tfl.yield"(%4, %5, %6, %7) : (tensor<1x32x32x32xf32>, tensor<1x32x32x32xf32>, tensor<1x32x32x32xf32>, tensor<1x32x32x32xf32>) -> ()
  }) : (tensor<1x64x64x32xf32>, tensor<1x64x64x32xf32>, tensor<1x64x64x32xf32>) -> (tensor<1x32x32x32xf32>, tensor<1x32x32x32xf32>, tensor<1x32x32x32xf32>, tensor<1x32x32x32xf32>)

// CHECK-DAG:       %[[VAL_2:.*]] = "tf.Const"() <{value = dense<[0, 1]> : tensor<2xi64>}> : () -> tensor<2xi64>
// CHECK-DAG:       %[[VAL_3:.*]] = "tf.Const"() <{value = dense<[0, 1, 3, 2]> : tensor<4xi64>}> : () -> tensor<4xi64>
// CHECK-DAG:       %[[VAL_4:.*]] = "tf.Transpose"(%[[VAL_1]], %[[VAL_3]]) : (tensor<3x3x32x64xf32>, tensor<4xi64>) -> tensor<3x3x64x32xf32>

  %0 = "tf.Conv2D"(%arg0, %arg1) {data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<?x32x32x6xf32>, tensor<3x3x3x16xf32>) -> tensor<?x8x7x16xf32>
  func.return %0 : tensor<?x8x7x16xf32>
}