EXPECT_EQ(attr_value.i(), 2);

  // Placeholder oper now has a consumer.
  ASSERT_EQ(1, TF_OperationOutputNumConsumers(TF_Output{feed, 0}));
  TF_Input feed_port;
  EXPECT_EQ(1, TF_OperationOutputConsumers(TF_Output{feed, 0}, &feed_port, 1));
  EXPECT_EQ(add, feed_port.oper);
  EXPECT_EQ(0, feed_port.index);

  // The scalar const oper also has a consumer.
  ASSERT_EQ(1, TF_OperationOutputNumConsumers(TF_Output{three, 0}));

// Get the number of current consumers of a specific output of an
// operation.  Note that this number can change when new operations
// are added to the graph.
TF_CAPI_EXPORT extern int TF_OperationOutputNumConsumers(TF_Output oper_out);

// Get list of all current consumers of a specific output of an
// operation.  `consumers` must point to an array of length at least
// `max_consumers` (ideally set to

  }
  return count;
}

int TF_OperationOutputConsumers(TF_Output oper_out, TF_Input* consumers,
                                int max_consumers) {
  int count = 0;
  for (const auto* edge : oper_out.oper->node.out_edges()) {
    if (edge->src_output() == oper_out.index) {
      if (count < max_consumers) {
        consumers[count] = {ToOperation(edge->dst()), edge->dst_input()};
      }
      ++count;
    }

  ~TapeVSpace() override {}

  // Returns the number of elements in the gradient tensor.
  int64_t NumElements(AbstractTensorHandle* tensor) const override;

  // Consumes references to the tensors in the gradient_tensors list and returns
  // a tensor with the result.
  AbstractTensorHandle* AggregateGradients(
      gtl::ArraySlice<AbstractTensorHandle*> gradient_tensors) const override;

      memcpy(buffer,
             gcs_file->buffer.data() + (offset - gcs_file->buffer_start),
             copy_size);
    }
    bool consumed_buffer_to_eof =
        offset + copy_size >= buffer_end && gcs_file->buffer_end_is_past_eof;
    if (copy_size < n && !consumed_buffer_to_eof) {
      gcs_file->buffer_start = offset + copy_size;
      gcs_file->buffer.resize(gcs_file->buffer_size);

        SavedModel.
    *   The user object metadata field in the SavedModel proto has been
        deprecated as part of the updates to Keras SavedModel. Keras was the
        only consumer of this field prior to the update.
*   GPU
    *   TF 2.3 includes PTX kernels only for
        [compute capability](https://developer.nvidia.com/cuda-gpus) 7.0 to

class VSpace {
 public:
  virtual ~VSpace() {}

  // Returns the number of elements in the gradient tensor.
  virtual int64_t NumElements(Gradient* tensor) const = 0;

  // Consumes references to the tensors in the gradient_tensors list and returns
  // a tensor with the result.
  virtual Gradient* AggregateGradients(
      gtl::ArraySlice<Gradient*> gradient_tensors) const = 0;