code: def build_toy_dataset(N=40, noise_std=0.1):
      D = 1
      X = np.concatenate(
          [np.linspace(0, 2, num=N / 2), np.linspace(6, 8, num=N / 2)]
      )
      y = np.cos(X) + np.random.normal(0, noise_std, size=N)
      X = (X - 4.0) / 4.0
      X = X.reshape((N, D))
      return X, y
  
file_path: edward/examples/bayesian_nn.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 Normal
label_desc: Use image node_id 1 for calling a global function with example usage: build_toy_dataset(N, noise_std) and returns: X,  y