code: def construct_secret(
      secret_config: SecretConfig, seqs: Sequence[Any]
  ) -> SecretsSet:
      """Constructs a SecretsSet instance given a sequence of samples.
  
      Args:
        secret_config: configuration of secret.
        seqs: a sequence of samples that will be used for secrets and references.
  
      Returns:
        a SecretsSet instance.
      """
      if (
          len(seqs)
          < sum(secret_config.num_secrets_for_repetitions)
          + secret_config.num_references
      ):
          raise ValueError("seqs does not contain enough elements.")
      secrets = {}
      i = 0
      for num_repetition, num_secrets in zip(
          secret_config.num_repetitions,
          secret_config.num_secrets_for_repetitions,
      ):
          secrets[num_repetition] = seqs[i : i + num_secrets]
          i += num_secrets
      return SecretsSet(
          config=secret_config,
          secrets=secrets,
          references=seqs[-secret_config.num_references :],
      )
  
file_path: privacy/tensorflow_privacy/privacy/privacy_tests/secret_sharer/generate_secrets.py
imports: import dataclasses
  import itertools
  import string
  from typing import Any, Dict, MutableSequence, Sequence
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: construct_secret(secret_config, seqs) and returns: SecretsSet