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);

    Location loc = op.getLoc();
    Value scalar_zero = CreateI32SplatConst(loc, &rewriter, {}, 0);

    // Compute the input tensorlist's length and store it in `input_size`.
    IntegerType shape_dtype = rewriter.getIntegerType(32);
    auto input_size = rewriter.create<TF::TensorListLengthOp>(
        loc, tensorflow::GetTypeFromTFTensorShape({}, shape_dtype),
        op.getOperand(0));

  }];

  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,