class_docstr: Quantizes the weights and activations of the keras layer it wraps.
class_docstr_tok: ["Quantizes","the","weights","and","activations","of","the","keras","layer","it","wraps","."]
docstr: Extracts the weight name from the full TensorFlow variable name.
  
  For example, returns 'kernel' for 'dense_2/kernel:0'.
  
  Args:
    name: TensorFlow variable name.
  
  Returns:
    Extracted weight name.
docstr_tok: ["Extracts","the","weight","name","from","the","full","TensorFlow","variable","name",".","For","example",",","returns","'kernel","'","for","'dense_2\/kernel:0","'",".","Args",":","name",":","TensorFlow","variable","name",".","Returns",":","Extracted","weight","name","."]
code: def _weight_name(self, name):
      """Extracts the weight name from the full TensorFlow variable name.
  
      For example, returns 'kernel' for 'dense_2/kernel:0'.
  
      Args:
        name: TensorFlow variable name.
  
      Returns:
        Extracted weight name.
      """
      return name.split(":")[0].split("/")[-1]
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tensorflow.python.util import tf_inspect
  from tensorflow_model_optimization.python.core.keras import metrics
  from tensorflow_model_optimization.python.core.keras import utils
  from tensorflow_model_optimization.python.core.quantization.keras import quantize_aware_activation
  from tensorflow_model_optimization.python.core.quantization.keras import utils
label_desc: Use image node_id 3 for calling the QuantizeWrapper obj's underlying member method code with example usage: obj._weight_name(name) and returns: name