Method CreateAndTransfer

tensorflow/compiler/xrt/xrt_state.cc:169–195

static*/

}

/*static*/ Status XRTTupleAllocation::CreateAndTransfer(
    const xla::LiteralBase& literal, XRTMemoryManager* memory_manager,
    xla::Backend* backend, int device_ordinal,
    XRTTupleAllocation** allocation) {
  auto transfer_manager = backend->transfer_manager();
  std::unique_ptr<xla::ScopedShapedBuffer> scoped_buffer;
  TF_RETURN_IF_ERROR(AllocateScopedShapedBuffer(memory_manager, backend,
                                                device_ordinal, literal.shape(),
                                                &scoped_buffer));
  TF_ASSIGN_OR_RETURN(auto stream, backend->BorrowStream(device_ordinal));
  TF_RETURN_IF_ERROR(transfer_manager->TransferLiteralToDevice(
      stream.get(), literal, *scoped_buffer));

  // By releasing the ScopedShapedBuffer we ensure that the underlying storage
  // won't be freed when the buffer goes out of scope at the end of this
  // call. To avoid a leak, there must be no error-case returns from here until
  // the end of the method.
  auto shaped_buffer = scoped_buffer->release();
  *allocation = new XRTTupleAllocation(
      device_ordinal, backend->memory_allocator(),
      shaped_buffer.on_host_shape(), shaped_buffer.on_device_shape());
  (*allocation)
      ->InitializeFromShapedBuffer(shaped_buffer, backend->memory_allocator(),
                                   device_ordinal);
  (*allocation)->SetDeviceMemorySize();
  return Status::OK();
}

/*static*/ Status XRTTupleAllocation::CreateUninitialized(
    const xla::Shape& shape, XRTMemoryManager* memory_manager,