// This method uses a temporary buffer to hold contents.
int CopyFileContents(int dst_fd, int src_fd, off_t size) {
  // Use a copy buffer of 128KB but don't store it on the stack.
  constexpr static size_t kPosixCopyFileBufferSize = 128 * 1024;
  std::unique_ptr<char[]> buffer(new char[kPosixCopyFileBufferSize]);

  off_t offset = 0;
  int bytes_transferred = 0;
  int rc = 1;
  // When `sendfile` returns 0 we stop copying and let callers handle this.

      }
      break;
    case DLDataTypeCode::kDLComplex:
      switch (dtype.bits) {
        case 64:
          *tf_dtype = TF_DataType::TF_COMPLEX64;
          return absl::OkStatus();
        case 128:
          *tf_dtype = TF_DataType::TF_COMPLEX128;
          return absl::OkStatus();
        default:
          return tensorflow::errors::InvalidArgument(
              "Unsupported Complex bits: ", dtype.bits);

// memory consumption is over kMinAggregateBytes, do an early aggregation
// so as to release the gradient tensor to save memory.
constexpr int kMinAggregateCount = 4;
constexpr int kMinAggregateBytes = 128 * 1024 * 1024;

template <typename Gradient, typename BackwardFunction, typename TapeTensor>
Status GradientTape<Gradient, BackwardFunction, TapeTensor>::ComputeGradient(