Method SendStringSlice

tensorflow/core/kernels/slice_sendrecv_ops.cc:184–218

}

Status SliceSendOp::SendStringSlice(OpKernelContext* ctx,
                                    const FrameAndIter& frame_iter,
                                    const std::string& elem, int64 index) {
  Rendezvous::Args args;
  args.device_context = ctx->op_device_context();
  args.alloc_attrs = ctx->input_alloc_attr(0);
  Rendezvous::ParsedKey parsed_key;

  int64 slice_num = elem.size() / slice_size_;
  if (elem.size() % slice_size_ != 0) {
    slice_num += 1;
  }
  Tensor data_t;
  for (int64 i = 0; i < slice_num; i++) {
    TF_RETURN_IF_ERROR(ctx->allocate_temp(DT_STRING, TensorShape({}), &data_t));
    size_t start = i * slice_size_;
    size_t copy_size = slice_size_;
    if (start > elem.size() - slice_size_) {
      copy_size = elem.size() - start;
    }
    data_t.scalar<tstring>()() = elem.substr(start, copy_size);
    std::string tensor_name_suffix = \
      strings::StrCat("_slice_transfer_data_", std::to_string(index), "_",
                      std::to_string(i));
    slice_sendrecv::GetSliceRendezvousKey(key_prefix_, tensor_name_suffix,
                                          frame_iter, &parsed_key.buf_);
    VLOG(2) << "SliceSend " << parsed_key.buf_;
    TF_RETURN_IF_ERROR(Rendezvous::ParseKey(parsed_key.buf_, &parsed_key));
    TF_RETURN_IF_ERROR(
      ctx->rendezvous()->FlowControlSend(tensor_name_, parsed_key, args, data_t,
                                         ctx->is_input_dead()));
  }

  return Status::OK();
}

Status SliceSendOp::SendBasicType(OpKernelContext* ctx,
                                  const FrameAndIter& frame_iter,