if (api_def == nullptr) {
    return nullptr;
  }

  TF_Buffer* ret = TF_NewBuffer();
  status->status = MessageToBuffer(*api_def, ret);
  if (!status->status.ok()) {
    TF_DeleteBuffer(ret);
    return nullptr;
  }
  return ret;
#endif  // defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
}

    using a job called "copybara".

**5. Copy to Google Internal codebase and run internal CI**

-   Once the PR is in the Google codebase, we make sure it integrates well with
    its dependencies and the rest of the system.
-   Rarely, If the tests fail at this stage, we cannot merge the code.
-   If needed, we may come to you to make some changes. At times, it may not be

                                  TF_Status* status) {
  TF_AttrType ret;
  TFE_Op* op = TFE_NewOp(ctx, op_or_function_name, status);
  if (status->status.ok()) {
    ret = TFE_OpGetAttrType(op, attr_name, is_list, status);
  } else {
    ret = TF_ATTR_INT;  // Same dummy return as TFE_OpGetAttrType.
  }
  TFE_DeleteOp(op);
  return ret;
}

    *   Allow sparse float splits to support multivalent feature columns.
    *   Add `quantile` to `tf.distributions.TransformedDistribution`.
    *   Add `NCHW_VECT_C` support for `tf.depth_to_space` on GPU.
    *   Add `NCHW_VECT_C` support for `tf.space_to_depth` on GPU.

## API Changes

*   Rename `SqueezeDims` attribute to `Axis` in C++ API for Squeeze op.

  }
  TF_Buffer* ret = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(options, ret));
  return ret;
}

const char* TF_GraphDebugString(TF_Graph* graph, size_t* len) {
  tensorflow::mutex_lock c(graph->mu);
  const auto& debug_str = graph->graph.ToGraphDefDebug().DebugString();
  *len = debug_str.size();
  char* ret = static_cast<char*>(malloc(*len + 1));

// gradient function can accept None values. e.g. FusedBatchNorm outputs 5
// values and hence receives 5 gradient values during backprop. However the
// gradient function uses only the first of those values and ignores the rest.
// The entry, "FusedBatchNorm": [1, 2, 3, 4], indicates that only the gradient
// corresponding to index 0 is used, and the gradient values at indices 1-4 are