class_docstr: Abstract base PyTorch compressor
docstr: reset model state dict and model wrapper
docstr_tok: ["reset","model","state","dict","and","model","wrapper"]
code: def reset(self, checkpoint=None):
      """
      reset model state dict and model wrapper
      """
      self._unwrap_model()
      if checkpoint is not None:
          self.bound_model.load_state_dict(checkpoint)
  
      self.modules_to_compress = None
      self.modules_wrapper = []
  
      for layer, config in self._detect_modules_to_compress():
          wrapper = self._wrap_modules(layer, config)
          self.modules_wrapper.append(wrapper)
  
      self._wrap_model()
  
imports: import types
  import logging
  import torch
  from .None import default_layers
label_desc: Use image node_id 3 for calling the Compressor obj's underlying member method code with example usage: obj.reset(checkpoint) without return types