int64_t output_size;
        int64_t pad_low_int64;
        int64_t pad_high_int64;
        int64_t input_size = input_ty.getDimSize(dim);
        if (input_size == ShapedType::kDynamic) return failure();
        absl::Status status = tensorflow::GetWindowedOutputSizeVerbose(
            input_size, filter_ty.getDimSize(i), dilation, stride, padding,
            &output_size, &pad_low_int64, &pad_high_int64);

    // 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",