code: def __init__(
      self,
      loss_type="L2Loss",
      loss_func_params=None,
      name="loss_function",
  ):
      super(LossFunction, self).__init__(name=name)
  
      # set loss function and function-specific additional params.
      self._data_loss_func = LossRegressionFactory.create(loss_type)
      self._loss_func_params = (
          loss_func_params if loss_func_params is not None else {}
      )
      self._reshape = True
      if loss_type == "Cosine":
          self._reshape = False
  
file_path: NiftyNet/niftynet/layer/loss_regression.py
imports: from __future__ import absolute_import, print_function, division
  import tensorflow
  from niftynet.engine.application_factory import LossRegressionFactory
  from niftynet.layer.base_layer import Layer
label_desc: Use image node_id 1 to create a new LossFunction object from inherited base classes: Layer with example: obj = LossFunction(loss_type, loss_func_params, name)