class_docstr: Base class for streaming correlation metrics.
  
  Based on https://arxiv.org/abs/1712.01521.
  
  It stores and updates the joint and marginal histograms of (`y_true`, `y_pred`).
  
  The concrete classes estimate the different correlation metrics
  based on those histograms.
class_docstr_tok: ["Base","class","for","streaming","correlation","metrics",".","Based","on","https",":","\/\/arxiv.org\/abs\/1712.01521",".","It","stores","and","updates","the","joint","and","marginal","histograms","of","(","`","y_true","`",",","`","y_pred","`",")",".","The","concrete","classes","estimate","the","different","correlation","metrics","based","on","those","histograms","."]
docstr: Resets all of the metric state variables.
docstr_tok: ["Resets","all","of","the","metric","state","variables","."]
code: def reset_state(self):
      """Resets all of the metric state variables."""
  
      self.m.assign(
          tf.zeros(
              (self.actual_cutpoints - 1, self.preds_cutpoints - 1),
              tf.int64,
          )
      )
      self.nrow.assign(tf.zeros((self.actual_cutpoints - 1), tf.int64))
      self.ncol.assign(tf.zeros((self.preds_cutpoints - 1), tf.int64))
      self.n.assign(0)
  
imports: from abc import abstractmethod
  import numpy
  import tensorflow
  from tensorflow.keras import backend
  from tensorflow.keras.metrics import Metric
  from tensorflow_addons.utils.types import AcceptableDTypes
  from typeguard import typechecked
label_desc: Use image node_id 5 for calling the CorrelationBase obj's underlying member method code with example usage: obj.reset_state() without return types