class_docstr: This class is intended for the EVAC+ model.
class_docstr_tok: ["This","class","is","intended","for","the","EVAC+","model","."]
docstr: Load the custom pre-training weights to use for the fitting.
  
  Parameters
  ----------
  weights_path : str
      Path to the file containing the weights (hdf5, saved by tensorflow)
docstr_tok: ["Load","the","custom","pre-training","weights","to","use","for","the","fitting",".","Parameters","--","--","--","--","--","weights_path",":","str","Path","to","the","file","containing","the","weights","(","hdf5",",","saved","by","tensorflow",")"]
code: def load_model_weights(self, weights_path):
      r"""
      Load the custom pre-training weights to use for the fitting.
  
      Parameters
      ----------
      weights_path : str
          Path to the file containing the weights (hdf5, saved by tensorflow)
      """
      try:
          self.model.load_weights(weights_path)
      except ValueError:
          raise ValueError(
              "Expected input for the provided model weights \
                               do not match the declared model"
          )
  
imports: import logging
  import numpy
  from dipy.data import get_fnames
  from dipy.testing.decorators import doctest_skip_parser
  from dipy.utils.optpkg import optional_package
  from dipy.align.reslice import reslice
  from dipy.nn.utils import normalize, set_logger_level, transform_img
  from dipy.nn.utils import recover_img, correct_minor_errors
label_desc: Use image node_id 3 for calling the EVACPlus obj's underlying member method code with example usage: obj.load_model_weights(weights_path) without return types