tensorflow_probability/python/glm/fisher_scoring.py
def calculate_linear_predictor(model_matrix, model_coefficients, offset=None,
                               name=None):
  """Computes `model_matrix @ model_coefficients + offset`."""
  with tf.compat.v1.name_scope(name, 'calculate_linear_predictor',
                               [model_matrix, model_coefficients, offset]):
    predicted_linear_response = tf.linalg.matvec(model_matrix,
                                                 model_coefficients)
    if offset is not None:
      predicted_linear_response += offset
    return predicted_linear_response
def calculate_linear_predictor(model_matrix, model_coefficients, offset=None,
                               name=None):
  """Computes `model_matrix @ model_coefficients + offset`."""
  with tf.compat.v1.name_scope(name, 'calculate_linear_predictor',
                               [model_matrix, model_coefficients, offset]):
    predicted_linear_response = tf.linalg.matvec(model_matrix,
                                                 model_coefficients)
    if offset is not None:
      predicted_linear_response += offset
    return predicted_linear_response
def calculate_linear_predictor ( model_matrix , model_coefficients , offset = None , name = None ) : with tf . compat . v1 . name_scope ( name , 'calculate_linear_predictor' , [ model_matrix , model_coefficients , offset ] ) : predicted_linear_response = tf . linalg . matvec ( model_matrix , model_coefficients ) if offset is not None : predicted_linear_response += offset return predicted_linear_response
Computes `model_matrix @ model_coefficients + offset`.
Computes model_matrix