code: def _setup(self):
      N = 250  # number of data points
      D = 5  # number of features
  
      # DATA
      w_true = np.ones(D) * 5.0
      X_train, y_train = build_toy_dataset(N, w_true)
  
      # MODEL
      X = tf.placeholder(tf.float32, [N, D])
      w = Normal(loc=tf.zeros(D), scale=tf.ones(D))
      b = Normal(loc=tf.zeros(1), scale=tf.ones(1))
      y = Normal(loc=ed.dot(X, w) + b, scale=tf.ones(N))
  
      return N, D, w_true, X_train, y_train, X, w, b, y
  
file_path: edward/tests/inferences/laplace_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import edward
  import numpy
  import tensorflow
  from edward.models import MultivariateNormalDiag, MultivariateNormalTriL, Normal
label_desc: Use image node_id 1 for calling the test_laplace_class obj's underlying member method code with example usage: obj._setup() and returns: N,  D,  w_true,  X_train,  y_train,  X,  w,  b,  y