tensorflow model for linear regression

get_model.py

def get_model_tensors():
  """
  function obtain model tensor
  """
  # X is the placeholder for size of the house from the dataset.
  # Y is the placeholder for size of the house from the dataset.
  X = tf.placeholder("float")
  Y = tf.placeholder("float")
  
  # The parameters theta0 and theta1 
  theta1 = tf.Variable(np.random.randn(), name="weight")
  theta0 = tf.Variable(np.random.randn(), name="bias")
  
  # Hypothesis = theta0 + theta1 * X
  x_theta1 = tf.multiply(X, theta1)
  model = tf.add(x_theta1 , theta0)
  
  return X, Y, theta1, theta0, model