Function RunCallableHelper

tensorflow/python/client/tf_session_helper.cc:208–288

namespace {
void RunCallableHelper(tensorflow::Session* session, int64_t handle,
                       PyObject* feed_values, TF_Status* out_status,
                       PyObjectVector* out_values, TF_Buffer* run_metadata) {
  // Convert feed values to a vector of tensorflow::Tensor objects.
  std::vector<Tensor> input_tensors;
  Status s;
  {
    feed_values =
        PySequence_Fast(feed_values, "feed_values must be a sequence");
    if (feed_values == nullptr) return;
    Safe_PyObjectPtr feed_values_holder(make_safe(feed_values));
    Py_ssize_t len = PySequence_Fast_GET_SIZE(feed_values);
    input_tensors.reserve(len);
    for (Py_ssize_t i = 0; i < len; ++i) {
      PyObject* elem = PySequence_Fast_GET_ITEM(feed_values, i);
      if (!elem) {
        Set_TF_Status_from_Status(
            out_status, errors::Internal("Could not get feed value ", i));
        return;
      }
      Tensor t;
      s = NdarrayToTensor(elem, &t);
      if (!s.ok()) {
        Set_TF_Status_from_Status(out_status, s);
        return;
      }
      input_tensors.push_back(std::move(t));
    }
  }

  // Allocate a RunMetadata protobuf object to receive the metadata,
  // if the caller is expecting any.
  std::unique_ptr<RunMetadata> run_metadata_proto;
  if (run_metadata != nullptr) {
    run_metadata_proto.reset(new RunMetadata);
  }

  // Run the callable.
  std::vector<Tensor> output_tensors;
  Py_BEGIN_ALLOW_THREADS;
  s = session->RunCallable(handle, input_tensors, &output_tensors,
                           run_metadata_proto.get());
  Py_END_ALLOW_THREADS;

  if (!s.ok()) {
    Set_TF_Status_from_Status(out_status, s);
    return;
  }

  // If requested, serialize the RunMetadata to pass it back to the caller.
  if (run_metadata != nullptr) {
    s = MessageToBuffer(*run_metadata_proto, run_metadata);
    if (!s.ok()) {
      Set_TF_Status_from_Status(out_status, s);
      return;
    }
  }