class_docstr: Matches patterns to apply transforms in a tf.keras model graph.
docstr: Returns a map of weight name, weight matrix. Keeps keras ordering.
code: def _get_keras_layer_weights(self, keras_layer):
      """Returns a map of weight name, weight matrix. Keeps keras ordering."""
      weights_map = collections.OrderedDict()
      for weight_tensor, weight_numpy in zip(
          keras_layer.weights, keras_layer.get_weights()
      ):
          weights_map[
              self._weight_name(weight_tensor.name)
          ] = weight_numpy
  
      if len(weights_map) != len(keras_layer.weights):
          # The case that variable identifier is not unique. It's a fallback that
          # uses weight list instead of the weights map.
          return None
  
      return weights_map
  
imports: import collections
  import copy
  import re
  import tensorflow
  from tensorflow_model_optimization.python.core.quantization.keras.graph_transformations import transforms
label_desc: Use image node_id 25 for calling the ModelTransformer obj's underlying member method code with example usage: obj._get_keras_layer_weights(keras_layer) and returns: weights_map, None