class_docstr: An abstract base class for a generalized linear model (one-class
  supervised learning)
  
  Parameters
  ----------
  fit_intercept : `bool`
      If `True`, the model uses an intercept
  
  Attributes
  ----------
  features : `numpy.ndarray`, shape=(n_samples, n_features) (read-only)
      The features matrix
  
  labels : `numpy.ndarray`, shape=(n_samples,)  (read-only)
      The labels vector
  
  n_samples : `int`  (read-only)
      Number of samples
  
  n_features : `int` (read-only)
      Number of features
  
  n_coeffs : `int` (read-only)
      Total number of coefficients of the model
  
  dtype : `{'float64', 'float32'}`
      Type of the data arrays used.
  
  Notes
  -----
  This class should be not used by end-users, it is intended for
  development only.
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code: def _get_n_coeffs(self):
      return self._model.get_n_coeffs()
  
imports: from .None import ModelLabelsFeatures
label_desc: Use image node_id 2 for calling the ModelGeneralizedLinear obj's underlying member method code with example usage: obj._get_n_coeffs() and returns: self