class_docstr: Abstract base PyTorch compressor
docstr: This method is implemented in the subclasses, i.e., `Pruner` and `Quantizer`
  
  Parameters
  ----------
  layer : LayerInfo
      the layer to instrument the compression operation
  config : dict
      the configuration for compressing this layer
docstr_tok: ["This","method","is","implemented","in","the","subclasses",",","i.e.",",","`","Pruner","`","and","`","Quantizer","`","Parameters","--","--","--","--","--","layer",":","LayerInfo","the","layer","to","instrument","the","compression","operation","config",":","dict","the","configuration","for","compressing","this","layer"]
code: def _wrap_modules(self, layer, config):
      """
      This method is implemented in the subclasses, i.e., `Pruner` and `Quantizer`
  
      Parameters
      ----------
      layer : LayerInfo
          the layer to instrument the compression operation
      config : dict
          the configuration for compressing this layer
      """
      raise NotImplementedError()
  
imports: import types
  import logging
  import torch
  from .None import default_layers
label_desc: Use image node_id 13 for calling the Compressor obj's underlying member method code with example usage: obj._wrap_modules(layer, config) without return types