class_docstr: This class is intended for the ResDNN Histology Network model.
class_docstr_tok: ["This","class","is","intended","for","the","ResDNN","Histology","Network","model","."]
docstr: Load the model pre-training weights to use for the fitting.
  Will not work if the declared SH_ORDER does not match the weights
  expected input.
docstr_tok: ["Load","the","model","pre-training","weights","to","use","for","the","fitting",".","Will","not","work","if","the","declared","SH_ORDER","does","not","match","the","weights","expected","input","."]
code: def fetch_default_weights(self):
      r"""
      Load the model pre-training weights to use for the fitting.
      Will not work if the declared SH_ORDER does not match the weights
      expected input.
      """
      fetch_model_weights_path = get_fnames("histo_resdnn_weights")
      self.load_model_weights(fetch_model_weights_path)
  
file_path: dipy/dipy/nn/histo_resdnn.py
imports: import logging
  import numpy
  from dipy.core.gradients import unique_bvals_magnitude, get_bval_indices
  from dipy.core.sphere import HemiSphere
  from dipy.data import get_sphere, get_fnames
  from dipy.reconst.shm import sf_to_sh, sh_to_sf, sph_harm_ind_list
  from dipy.testing.decorators import doctest_skip_parser
  from dipy.utils.optpkg import optional_package
  from dipy.nn.utils import set_logger_level
label_desc: Use image node_id 2 for calling the HistoResDNN obj's underlying member method code with example usage: obj.fetch_default_weights() without return types