code: def get_data():
      # Data is for hidden weights of [3, 1] and bias of 2.
      # Loss is (w.x + b - y)^2, model is initialized at (w, b) = (0, 0).
      # y = 15
      # Loss: y^2 = 15^2 = 225
      # Gradient w.r.t. w = -2yx = [90, 120]
      # Gradient w.r.t. b = -2y = 30
      data = np.array([[3, 4]])
      labels = np.matmul(data, [[3], [1]]) + 2
      return data, labels
  
file_path: privacy/tensorflow_privacy/privacy/keras_models/dp_keras_model_test.py
imports: from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow_privacy.privacy.fast_gradient_clipping import layer_registry
  from tensorflow_privacy.privacy.keras_models import dp_keras_model
label_desc: Use image node_id 1 for calling a global function with example usage: get_data() and returns: data,  labels