class_docstr: Compute the (weighted) mean of the given values.
  
  For example, if values is `[1, 3, 5, 7]` then the mean is 4.
  If `sample_weight` was specified as `[1, 1, 0, 0]` then the mean would be 2.
  
  This metric creates two variables, `total` and `count`.
  The mean value returned is simply `total` divided by `count`.
  
  Args:
      name: (Optional) string name of the metric instance.
      dtype: (Optional) data type of the metric result.
  
  Example:
  
  >>> m = Mean()
  >>> m.update_state([1, 3, 5, 7])
  >>> m.result()
  4.0
  
  >>> m.reset_state()
  >>> m.update_state([1, 3, 5, 7], sample_weight=[1, 1, 0, 0])
  >>> m.result()
  2.0
  ```
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code: def reset_state(self):
      self.total.assign(0.0)
      self.count.assign(0)
  
imports: from keras import backend
  from keras import initializers
  from keras import losses
  from keras import ops
  from keras.api_export import keras_export
  from keras.metrics.metric import Metric
  from keras.saving import serialization_lib
label_desc: Use image node_id 3 for calling the Mean obj's underlying member method code with example usage: obj.reset_state() without return types