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","."]
code: def trainable(self, value):
      self.layer.trainable = value
  
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 11 for calling the QuantizeWrapper obj's underlying member method code with example usage: obj.trainable(value) without return types