Method StartRecv

tensorflow/core/distributed_runtime/eager/remote_copy_node.cc:232–269

}

Status RemoteCopyNode::StartRecv() {
  // TODO(gjn): We should consider just using the low-level RecvOp::Compute()
  // functionality here instead of constructing an Op.
  const AttrTypeMap* types;
  bool is_function = false;
  Status status = AttrTypeMapForOp("_Recv", &types, &is_function);
  if (!status.ok()) {
    captured_state_->dst()->Poison(status);
    return status;
  }
  DCHECK(!is_function);
  EagerOperation op(ctx_, "_Recv", /*is_function=*/false, types);

  op.SetDevice(recv_device_);

  op.MutableAttrs()->Set("tensor_name", wire_id_);
  op.MutableAttrs()->Set("send_device", send_device_->name());
  op.MutableAttrs()->Set(
      "send_device_incarnation",
      static_cast<int64>(send_device_->attributes().incarnation()));
  op.MutableAttrs()->Set("recv_device", recv_device_->name());
  op.MutableAttrs()->Set("client_terminated", false);

  op.MutableAttrs()->Set("tensor_type", src_->dtype);

  if (recv_device_->IsLocal()) {
    std::vector<Tensor> outputs(1);
    status = RunLocalRecv(&op, &outputs);
    if (!status.ok()) {
      captured_state_->dst()->Poison(status);
      return status;
    }
    return captured_state_->dst()->SetTensor(outputs[0]);
  } else {
    // Handles captured_state_->dst_ internally.
    return RunRemoteRecv(&op);
  }
}

Status RemoteCopyNode::StartRemoteSendTensor() {
  EnqueueRequest request;