// does various checks while doing so. `input_nodes` will contain the same
// information as input_tensors just in a different structure to make
// following processing easier. TODO(iga): Simplify this nested structure.
Status ProcessInputs(
    const TF_Graph* fn_body, const char* fn_name, int ninputs,
    const TF_Output* inputs, std::vector<OutputTensor>* input_tensors,

  TF_Operation* neg = TF_GraphOperationByName(graph, "imported/neg");
  ASSERT_TRUE(scalar != nullptr);
  ASSERT_TRUE(feed != nullptr);
  ASSERT_TRUE(neg != nullptr);

  // Test basic structure of the imported graph.
  EXPECT_EQ(0, TF_OperationNumInputs(scalar));
  EXPECT_EQ(0, TF_OperationNumInputs(feed));
  ASSERT_EQ(1, TF_OperationNumInputs(neg));
  TF_Output neg_input = TF_OperationInput({neg, 0});

    import.
*   Breaking change to `tf.contrib.data.Dataset` APIs that expect a nested
    structure. Lists are now converted to `tf.Tensor` implicitly. You may need
    to change uses of lists to tuples in existing code. In addition, dicts are
    now supported as a nested structure.

## Changes to contrib APIs

*   Adds tf.contrib.nn.rank_sampled_softmax_loss, a sampled-softmax variant that