strides = [5, 6, 7, 8]
       } : (tensor<1x32x32x3xf32>, tensor<1x1x3x8xf32>) -> tensor<?x?x?x?xf32>

  func.return %0 : tensor<?x?x?x?xf32>
}

// CHECK-LABEL: func @transposeConv2DBackpropFilter
func.func @transposeConv2DBackpropFilter(
  %input: tensor<1x32x32x3xf32>,
  %filter_sizes: tensor<4xi32>,
  %out_backprop: tensor<1x32x32x8xf32>
) -> tensor<1x1x3x8xf32> {

  // CHECK-SAME: dilations = [1, 3, 4, 2]
  // CHECK-SAME: explicit_paddings = [1, 2, 5, 6, 7, 8, 3, 4]
  // CHECK-SAME: padding = "EXPLICIT"
  // CHECK-SAME: strides = [5, 7, 8, 6]
  // CHECK-SAME: (tensor<1x32x32x3xf32>, tensor<1x1x3x8xf32>) -> tensor<1x7x6x8xf32>

  // CHECK: %[[RES_PERM:.*]] = "tf.Const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi64>}>
  // CHECK: %[[RES_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%[[CONV2D]], %[[RES_PERM]])