code: def compute_bert_sample_inputs(
      batch_size, sequence_length, vocab_size, num_types
  ):
      """Returns a set of BERT encoder inputs."""
      word_id_sample = np.random.randint(
          vocab_size, size=(batch_size, sequence_length)
      )
      mask_sample = np.random.randint(
          2, size=(batch_size, sequence_length)
      )
      type_id_sample = np.random.randint(
          num_types,
          size=(batch_size, sequence_length),
      )
      return [word_id_sample, mask_sample, type_id_sample]
  
file_path: privacy/tensorflow_privacy/privacy/fast_gradient_clipping/bert_encoder_utils_test.py
imports: from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_models
  from tensorflow_privacy.privacy.fast_gradient_clipping import bert_encoder_utils
label_desc: Use image node_id 1 for calling a global function with example usage: compute_bert_sample_inputs(batch_size, sequence_length, vocab_size, num_types) and returns: list