reinterpret_cast<tensorflow::grappler::GraphProperties*>(graph_properties)
          ->GetInputProperties(name);
  const int len =
      std::min(num_values, static_cast<int>(tensor_properties.size()));
  for (int i = 0; i < len; ++i) {
    absl::Status s =
        tensorflow::MessageToBuffer(tensor_properties[i], properties[i]);
    if (!s.ok()) {

// Return the serialized list `properties`.
TF_CAPI_EXPORT extern void TF_GetInputPropertiesList(
    TF_GraphProperties* graph_properties, const char* name,
    TF_Buffer** properties, int num_values, TF_Status* status);

// Get a list of output OpInfo::TensorProperties given node name.
// Return the serialized list `properties`.
TF_CAPI_EXPORT extern void TF_GetOutputPropertiesList(
    TF_GraphProperties* graph_properties, const char* name,

  GrapplerItem item;
  CHECK(fake_input.NextItem(&item));

  TF_Status* status = TF_NewStatus();
  TF_GraphProperties* graph_properties =
      TF_NewGraphProperties(reinterpret_cast<TF_GrapplerItem*>(&item));
  TF_InferStatically(graph_properties, true, false, false, false, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  for (const NodeDef& node : item.graph.node()) {

      failure.text = failure_msg
    else:
      properties = ElemTree.SubElement(testcase, 'properties')
      success_msg = 'Build completed successfully.\n' f'See {url} for details.'
      ElemTree.SubElement(properties, 'property',
                          name='description',
                          value=success_msg)
      if command:
        ElemTree.SubElement(properties, 'property',

    TF_CheckpointReader* reader, const char* name, TF_Status* status);

// TF_NewAttrBuilder() returns an object that you can set attributes on as
// though it were an op. This allows querying properties of that op for
// type-checking purposes like if the op will run on a particular device type.
typedef struct TF_AttrBuilder TF_AttrBuilder;
TF_CAPI_EXPORT extern TF_AttrBuilder* TF_NewAttrBuilder(const char* op_name);