// output_spatial_shape[i] = ceil(input_spatial_shape[i] / strides[i])
    auto get_output_dim_for_same_padding = [](int64_t input_dim,
                                              int64_t stride_dim) -> int64_t {
      return std::ceil(input_dim / static_cast<double>(stride_dim));
    };
    return output_height ==
               get_output_dim_for_same_padding(input_height, stride_height) &&

                                 llvm::StringRef crop_b_name) -> LogicalResult {
      int64_t input_dim = input_shape[spatial_dim_index];
      int64_t output_dim = output_shape[spatial_dim_index];
      if (!static_dims(input_dim, output_dim)) return success();

      int64_t input_dim_pad = input_dim * block_size;
      // If crops are unknown, the maximum output spatial dim size is input

                 << "multiples[" << i << "] = " << m;
        }

        if (!ShapedType::isDynamic(input_dim) &&
            !ShapedType::isDynamic(output_dim) && output_dim != input_dim * m) {
          return op.emitOpError()
                 << "requires input.shape[" << i << "] (" << input_dim << ")"
                 << " * " << m << " to be equal to "

    const auto& tensor_info = iter.second;

    TF_ASSIGN_OR_RETURN(std::string name,
                        GetDenseTensorNameFromTensorInfo(tensor_info));

    VLOG(1) << "Importing Signature Input: input_name = " << iter.first
            << ", tensor_info = " << tensor_info.DebugString();

    ArrayInfo array_info;
    array_info.imported_dtype = tensor_info.dtype();

    if (tensor_info.has_tensor_shape()) {