class_docstr: Initialisation from the paper `All you need is a good init <https://arxiv.org/abs/1511.06422>`__. Call
  LSUV.init_model(...) on a torch model to perform the initialisation. Implementation based off of the PyTorch
  implementation `here <https://github.com/ducha-aiki/LSUV-pytorch>`__.
  
  Example: ::
  
      >>> import torch.nn
      >>> from torchbearer.callbacks import LSUV
  
      # Example of initialising a torch model with LSUV
      >>> model = torch.nn.Linear(1,1)
      >>> data = torch.rand(100, 1)
      >>> lsuv = LSUV(model, data)
      >>> model = lsuv.init_model(model, data)
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code: def reset_parameters(self):
      self.gg = {
          "hook_position": 0,
          "total_fc_conv_layers": 0,
          "done_counter": -1,
          "hook": None,
          "act_dict": {},
          "counter_to_apply_correction": 0,
          "correction_needed": False,
          "current_coef": 1.0,
          "weight_lambda": lambda m: m.weight,
      }
      return self.gg
  
file_path: torchbearer/torchbearer/callbacks/lsuv.py
imports: import numpy
  import torch
  import torch.nn.init
  import torch.nn
label_desc: Use image node_id 2 for calling the LSUV obj's underlying member method code with example usage: obj.reset_parameters() and returns: self