With inconsistent num_segments, the op still runs. only difference is,
the output takes the size of num_segments irrespective of size of segment_ids and data.
for num_segments less than expected output size, the last elements are ignored
for num_segments more than the expected output size, last elements are assigned 
smallest possible value for the specific numeric type.

For example:

                      rule: self.all(key, key.size() != 0)
                type: object
            type: object
            x-kubernetes-validations:
            - message: portLevelMtls requires selector
              rule: (has(self.selector) && has(self.selector.matchLabels) && self.selector.matchLabels.size()
                > 0) || !has(self.portLevelMtls)
          status:

                      rule: self.all(key, key.size() != 0)
                type: object
            type: object
            x-kubernetes-validations:
            - message: portLevelMtls requires selector
              rule: (has(self.selector) && has(self.selector.matchLabels) && self.selector.matchLabels.size()
                > 0) || !has(self.portLevelMtls)
          status:

        methods.
*   TensorFlow Debugger (tfdbg) CLI: fix an issue in which the TensorBoard
    Debugger Plugin could not handle total source file size exceeding gRPC
    message size limit (4 MB).
*   `tf.contrib`:
    *   `tf.contrib.framework.zero_initializer` supports ResourceVariable.
    *   Adding "constrained_optimization" to tensorflow/contrib.
*   Other: