code: def read_eog_regression(fname):
      """Read an EOG regression model from an HDF5 file.
  
      Parameters
      ----------
      fname : path-like
          The file to read the regression model from. Should end in ``.h5``.
  
      Returns
      -------
      model : EOGRegression
          The regression model read from the file.
  
      Notes
      -----
      .. versionadded:: 1.2
      """
      read_hdf5, _ = _import_h5io_funcs()
      _validate_type(fname, "path-like", "fname")
      fname = _check_fname(
          fname, overwrite="read", must_exist=True, name="fname"
      )
      model = EOGRegression()
      model.__dict__.update(read_hdf5(fname))
      return model
  
file_path: mne-python/mne/preprocessing/_regress.py
imports: import numpy
  from .._fiff.pick import _picks_to_idx
  from ..defaults import _BORDER_DEFAULT, _EXTRAPOLATE_DEFAULT, _INTERPOLATION_DEFAULT
  from ..epochs import BaseEpochs
  from ..evoked import Evoked
  from ..io import BaseRaw
  from ..minimum_norm.inverse import _needs_eeg_average_ref_proj
  from ..utils import _check_fname, _check_option, _check_preload, _import_h5io_funcs, _validate_type, copy_function_doc_to_method_doc, fill_doc, verbose
  from ..viz import plot_regression_weights
label_desc: Use image node_id 2 for calling a global function with example usage: read_eog_regression(fname) and returns: model