def LegalizeConv2DBackpropInput : Pat<
  (TF_Conv2DBackpropInputOp $input_sizes, $filter, $out_backprop,
     IsIntList1XY1:$strides,
     BoolAttr:$use_cudnn_on_gpu,
     IsSameOrValid:$padding,
     I64ArrayAttr:$explicit_paddings,
     IsDataFormatNHWC:$data_format,
     IsAllOnes:$dilations),
  (TFL_TransposeConvOp $input_sizes,
     (TFL_TransposeOp $filter,

    // CHECK-SAME: batch_group_count = 1 : i64
    // CHECK-SAME: feature_group_count = 1 : i64
    // CHECK: return %[[RESULT]]
  %input_sizes = "tf.Const" () { value = dense<[100,28,28,1]> : tensor<4xi32> } : () -> tensor<4xi32>
  %result = "tf.Conv2DBackpropInput"(%input_sizes, %filter, %out_backprop) {
    data_format = "NHWC",
    dilations = [1, 1, 1, 1],
    explicit_paddings = [],
    padding = "VALID",

  }];

  let arguments = (ins
    Arg<TF_Int32Tensor, [{An integer vector representing the shape of `input`,
where `input` is a 4-D `[batch, height, width, channels]` tensor.}]>:$input_sizes,
    Arg<TensorOf<[TF_Bfloat16, TF_Float16, TF_Float32, TF_Float64, TF_Int32]>, [{4-D with shape
`[filter_height, filter_width, in_channels, out_channels]`.}]>:$filter,