Method add_variable

tensorflow/contrib/eager/python/metrics_impl.py:260–290

***Only for use by descendants of Metric***.

(self, name, shape=None, dtype=None, initializer=None)

  # ---- For use by descendants ---
  def add_variable(self, name, shape=None, dtype=None, initializer=None):
    """***Only for use by descendants of Metric***."""
    if self._built:
      raise RuntimeError("Can't call add_variable() except in build().")
    if context.executing_eagerly():
      collections = None
    else:
      if self._use_global_variables:
        collections = [ops.GraphKeys.GLOBAL_VARIABLES]
      else:
        collections = [ops.GraphKeys.LOCAL_VARIABLES]
      collections += [ops.GraphKeys.METRIC_VARIABLES]
    # Variables are Trackable dependencies of Metrics regardless of the
    # global/local distinction. Users can avoid saving variables by not adding a
    # dependency on the Metric.
    v = self._add_variable_with_custom_getter(
        name=name,
        shape=shape,
        dtype=dtype,
        initializer=initializer,
        trainable=False,
        collections=collections,
        use_resource=True,
        getter=variable_scope.get_variable,
        # Raise duplicate variable exceptions from get_variable rather than
        # Trackable.
        overwrite=True)
    self._vars.append(v)
    if context.executing_eagerly():
      self._initial_values[v] = v.value()
    return v


class Mean(Metric):