class_docstr: Base class for PreprocessingLayers that do computation using a Combiner.
  
  This class provides several helper methods to make creating a
  PreprocessingLayer easier. It assumes that the core of your computation will
  be done via a Combiner object. Subclassing this class to create a
  PreprocessingLayer allows your layer to be compatible with distributed
  computation.
  
  This class is compatible with Tensorflow 2.0+.
docstr: Directly update the internal state of this Layer.
  
  This method expects a string-keyed dict of {state_variable_name: state}. The
  precise nature of the state, and the names associated, are describe by
  the subclasses of CombinerPreprocessingLayer.
  
  Args:
    updates: A string keyed dict of weights to update.
  
  Raises:
    RuntimeError: if 'build()' was not called before 'set_processing_state'.
docstr_tok: ["Directly","update","the","internal","state","of","this","Layer",".","This","method","expects","a","string-keyed","dict","of","{","state_variable_name",":","state","}",".","The","precise","nature","of","the","state",",","and","the","names","associated",",","are","describe","by","the","subclasses","of","CombinerPreprocessingLayer",".","Args",":","updates",":","A","string","keyed","dict","of","weights","to","update",".","Raises",":","RuntimeError",":","if","'build","(",")","'","was","not","called","before","'set_processing_state","'","."]
code: def _set_state_variables(self, updates):
      """Directly update the internal state of this Layer.
  
      This method expects a string-keyed dict of {state_variable_name: state}. The
      precise nature of the state, and the names associated, are describe by
      the subclasses of CombinerPreprocessingLayer.
  
      Args:
        updates: A string keyed dict of weights to update.
  
      Raises:
        RuntimeError: if 'build()' was not called before 'set_processing_state'.
      """
      # TODO(momernick): Do we need to do any more input sanitization?
      if not self.built:
          raise RuntimeError(
              "_set_state_variables() must be called after build()."
          )
  
      with ops.init_scope():
          for var_name, value in updates.items():
              self.state_variables[var_name].assign(value)
  
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 12 for calling the CombinerPreprocessingLayer obj's underlying member method code with example usage: obj._set_state_variables(updates) without return types