code: def __init__(
      self, slope: gpflow.base.TensorData, bias: gpflow.base.TensorData
  ) -> None:
      super().__init__()
      self.slope = gpflow.Parameter(slope)
      self.bias = gpflow.Parameter(bias)
  
file_path: GPflow/doc/sphinx/notebooks/getting_started/parameters_and_their_optimisation.pct.py
imports: import os
  import warnings
  from typing import Optional
  import matplotlib.pyplot
  import numpy
  import pandas
  import tensorflow
  import tensorflow_probability
  from check_shapes import check_shapes
  from matplotlib.axes import Axes
  import gpflow
  from gpflow.ci_utils import is_continuous_integration
label_desc: Use image node_id 1 to create a new LinearModel object from inherited base classes: gpflow with example: obj = LinearModel(slope, bias)