code: def _test_dataset(num_features, num_test_points=None):
      return dict(
          train_features=tf.zeros([10, num_features]),
          test_features=(
              tf.zeros([num_test_points, num_features])
              if num_test_points
              else None
          ),
          train_labels=tf.zeros([10], dtype=tf.int32),
          test_labels=(
              tf.zeros([num_test_points], dtype=tf.int32)
              if num_test_points
              else None
          ),
      )
  
file_path: probability/spinoffs/inference_gym/inference_gym/targets/logistic_regression_test.py
imports: from absl.testing import parameterized
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from inference_gym.internal import test_util
  from inference_gym.targets import logistic_regression
label_desc: Use image node_id 1 for calling a global function with example usage: _test_dataset(num_features, num_test_points) and returns: dict