class_docstr: Track moving mean, std and count.
class_docstr_tok: ["Track","moving","mean",",","std","and","count","."]
docstr: Update moving mean, std and count.
  
  Args:
      batch_mean: Input batch mean.
      batch_var: Input batch variance.
      batch_count: Number of cases in the batch.
docstr_tok: ["Update","moving","mean",",","std","and","count",".","Args",":","batch_mean",":","Input","batch","mean",".","batch_var",":","Input","batch","variance",".","batch_count",":","Number","of","cases","in","the","batch","."]
code: def update_params(
      self, batch_mean: float, batch_var: float, batch_count: float
  ) -> None:
      """Update moving mean, std and count.
  
      Args:
          batch_mean: Input batch mean.
          batch_var: Input batch variance.
          batch_count: Number of cases in the batch.
      """
      delta = batch_mean - self.mean
      tot_count = self.count + batch_count
  
      # This moving mean calculation is from reference implementation.
      self.mean = self.mean + delta + batch_count / tot_count
      m_a = self.var * self.count
      m_b = batch_var * batch_count
      M2 = (
          m_a
          + m_b
          + np.power(delta, 2) * self.count * batch_count / tot_count
      )
      self.var = M2 / tot_count
      self.count = tot_count
  
imports: from gymnasium.spaces import Box, Discrete, Space
  import numpy
  from typing import List, Optional, Union
  from ray.rllib.models.action_dist import ActionDistribution
  from ray.rllib.models.catalog import ModelCatalog
  from ray.rllib.models.modelv2 import ModelV2
  from ray.rllib.policy.sample_batch import SampleBatch
  from ray.rllib.utils.annotations import override, PublicAPI
  from ray.rllib.utils.exploration.exploration import Exploration
  from ray.rllib.utils.framework import try_import_tf
  from ray.rllib.utils.from_config import from_config
  from ray.rllib.utils.tf_utils import get_placeholder
  from ray.rllib.utils.typing import FromConfigSpec, ModelConfigDict, TensorType
label_desc: Use image node_id 3 for calling the _MovingMeanStd obj's underlying member method code with example usage: obj.update_params(batch_mean, batch_var, batch_count) without return types