class_docstr: Base class for Preprocessing Layers.
  
  **Don't use this class directly: it's an abstract base class!** You may
  be looking for one of the many built-in
  [preprocessing layers](https://keras.io/guides/preprocessing_layers/)
  instead.
  
  Preprocessing layers are layers whose state gets computed before model
  training starts. They do not get updated during training.
  Most preprocessing layers implement an `adapt()` method for state computation.
  
  The `PreprocessingLayer` class is the base class you would subclass to
  implement your own preprocessing layers.
  
  Attributes:
    streaming: Whether a layer can be adapted multiple times without resetting
      the state of the layer.
docstr: Merge the statistics of multiple preprocessing layers.
  
  This layer will contain the merged state.
  
  Arguments:
    layers: Layers whose statistics should be merge with the statistics of
      this layer.
docstr_tok: ["Merge","the","statistics","of","multiple","preprocessing","layers",".","This","layer","will","contain","the","merged","state",".","Arguments",":","layers",":","Layers","whose","statistics","should","be","merge","with","the","statistics","of","this","layer","."]
code: def merge_state(self, layers):
      """Merge the statistics of multiple preprocessing layers.
  
      This layer will contain the merged state.
  
      Arguments:
        layers: Layers whose statistics should be merge with the statistics of
          this layer.
      """
      raise NotImplementedError
  
imports: import abc
  import collections
  import numpy
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor
  from tensorflow.python.keras import backend
  from tensorflow.python.keras.engine import data_adapter
  from tensorflow.python.keras.engine.base_layer import Layer
  from tensorflow.python.keras.utils import tf_utils
  from tensorflow.python.keras.utils import version_utils
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import sparse_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.trackable import base
label_desc: Use image node_id 6 for calling the PreprocessingLayer obj's underlying member method code with example usage: obj.merge_state(layers) without return types