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Python源码示例：bert.tokenization.validate_case_matches_checkpoint()

示例1

def validate_flags_or_throw(bert_config):
  """Validate the input FLAGS or throw an exception."""
  tokenization.validate_case_matches_checkpoint(FLAGS.do_lower_case,
                                                FLAGS.init_checkpoint)

  if not FLAGS.do_train and not FLAGS.do_predict:
    raise ValueError("At least one of `do_train` or `do_predict` must be True.")

  if FLAGS.do_train:
    if not FLAGS.train_file:
      raise ValueError(
          "If `do_train` is True, then `train_file` must be specified.")
  if FLAGS.do_predict:
    if not FLAGS.predict_file:
      raise ValueError(
          "If `do_predict` is True, then `predict_file` must be specified.")

  if FLAGS.max_seq_length > bert_config.max_position_embeddings:
    raise ValueError(
        "Cannot use sequence length %d because the BERT model "
        "was only trained up to sequence length %d" %
        (FLAGS.max_seq_length, bert_config.max_position_embeddings))

  if FLAGS.max_seq_length <= FLAGS.max_query_length + 3:
    raise ValueError(
        "The max_seq_length (%d) must be greater than max_query_length "
        "(%d) + 3" % (FLAGS.max_seq_length, FLAGS.max_query_length))

示例2

def validate_flags_or_throw(bert_config):
  """Validate the input FLAGS or throw an exception."""
  tokenization.validate_case_matches_checkpoint(FLAGS.do_lower_case,
                                                FLAGS.init_checkpoint)

  if not FLAGS.do_train and not FLAGS.do_predict:
    raise ValueError("At least one of `do_train` or `do_predict` must be True.")

  if FLAGS.do_train:
    if not FLAGS.train_file:
      raise ValueError(
          "If `do_train` is True, then `train_file` must be specified.")
  if FLAGS.do_predict:
    if not FLAGS.predict_input_file:
      raise ValueError(
          "If `do_predict` is True, then specify `predict_input_file`")

  if FLAGS.max_seq_length > bert_config.max_position_embeddings:
    raise ValueError(
        "Cannot use sequence length %d because the BERT model "
        "was only trained up to sequence length %d" %
        (FLAGS.max_seq_length, bert_config.max_position_embeddings))

  if FLAGS.max_seq_length <= FLAGS.max_query_length + 3:
    raise ValueError(
        "The max_seq_length (%d) must be greater than max_query_length "
        "(%d) + 3" % (FLAGS.max_seq_length, FLAGS.max_query_length))

示例3

def validate_flags_or_throw(bert_config):
  """Validate the input FLAGS or throw an exception."""
  tokenization.validate_case_matches_checkpoint(FLAGS.do_lower_case,
                                                FLAGS.init_checkpoint)

  if not FLAGS.do_train and not FLAGS.do_predict and not FLAGS.do_eval:
    raise ValueError(
        "At least one of `do_train` or `do_eval` or `do_predict` must be True.")

  if FLAGS.do_train:
    if not FLAGS.train_file:
      raise ValueError(
          "If `do_train` is True, then `train_file` must be specified.")
  if FLAGS.do_eval:
    if not FLAGS.dev_file:
      raise ValueError(
          "If `do_eval` is True, then `dev_file` must be specified.")
  if FLAGS.do_predict:
    if not FLAGS.predict_input_file:
      raise ValueError(
          "If `do_predict` is True, then specify `predict_input_file`")

  if FLAGS.max_seq_length > bert_config.max_position_embeddings:
    raise ValueError(
        "Cannot use sequence length %d because the BERT model "
        "was only trained up to sequence length %d" %
        (FLAGS.max_seq_length, bert_config.max_position_embeddings))

  if FLAGS.max_seq_length <= FLAGS.max_query_length + 3:
    raise ValueError(
        "The max_seq_length (%d) must be greater than max_query_length "
        "(%d) + 3" % (FLAGS.max_seq_length, FLAGS.max_query_length))

示例4

def validate_flags_or_throw(bert_config):
  """Validate the input FLAGS or throw an exception."""
  tokenization.validate_case_matches_checkpoint(FLAGS.do_lower_case,
                                                FLAGS.init_checkpoint)

  if not FLAGS.do_train and not FLAGS.do_predict:
    raise ValueError("At least one of `do_train` or `do_predict` must be True.")

  if FLAGS.do_train:
    if not FLAGS.train_file:
      raise ValueError(
          "If `do_train` is True, then `train_file` must be specified.")
  if FLAGS.do_predict:
    if not FLAGS.predict_file:
      raise ValueError(
          "If `do_predict` is True, then `predict_file` must be specified.")

  if FLAGS.max_seq_length > bert_config.max_position_embeddings:
    raise ValueError(
        "Cannot use sequence length %d because the BERT model "
        "was only trained up to sequence length %d" %
        (FLAGS.max_seq_length, bert_config.max_position_embeddings))

  if FLAGS.max_seq_length <= FLAGS.max_query_length + 3:
    raise ValueError(
        "The max_seq_length (%d) must be greater than max_query_length "
        "(%d) + 3" % (FLAGS.max_seq_length, FLAGS.max_query_length))

示例5

def validate_flags_or_throw(bert_config):
  """Validate the input FLAGS or throw an exception."""
  tokenization.validate_case_matches_checkpoint(FLAGS.do_lower_case,
                                                FLAGS.init_checkpoint)

  if not FLAGS.do_train and not FLAGS.do_predict:
    raise ValueError("At least one of `do_train` or `do_predict` must be True.")

  if FLAGS.do_train:
    if not FLAGS.train_file:
      raise ValueError(
          "If `do_train` is True, then `train_file` must be specified.")
  if FLAGS.do_predict:
    if not FLAGS.predict_file:
      raise ValueError(
          "If `do_predict` is True, then `predict_file` must be specified.")

  if FLAGS.max_seq_length > bert_config.max_position_embeddings:
    raise ValueError(
        "Cannot use sequence length %d because the BERT model "
        "was only trained up to sequence length %d" %
        (FLAGS.max_seq_length, bert_config.max_position_embeddings))

  if FLAGS.max_seq_length <= FLAGS.max_query_length + 3:
    raise ValueError(
        "The max_seq_length (%d) must be greater than max_query_length "
        "(%d) + 3" % (FLAGS.max_seq_length, FLAGS.max_query_length))

示例6

def validate_flags_or_throw(bert_config):
    """Validate the input FLAGS or throw an exception."""
    tokenization.validate_case_matches_checkpoint(FLAGS.do_lower_case,
                                                  FLAGS.init_checkpoint)

    if not FLAGS.do_train and not FLAGS.do_predict:
        raise ValueError(
            "At least one of `do_train` or `do_predict` must be True.")

    if FLAGS.do_train:
        if not FLAGS.train_file:
            raise ValueError(
                "If `do_train` is True, then `train_file` must be specified.")
    if FLAGS.do_predict:
        if not FLAGS.predict_file:
            raise ValueError(
                "If `do_predict` is True, then `predict_file` must be specified.")

    if FLAGS.max_seq_length > bert_config.max_position_embeddings:
        raise ValueError(
            "Cannot use sequence length %d because the BERT model "
            "was only trained up to sequence length %d" %
            (FLAGS.max_seq_length, bert_config.max_position_embeddings))

    if FLAGS.max_seq_length <= FLAGS.max_query_length + 3:
        raise ValueError(
            "The max_seq_length (%d) must be greater than max_query_length "
            "(%d) + 3" % (FLAGS.max_seq_length, FLAGS.max_query_length))

Python源码示例：bert.tokenization.validate_case_matches_checkpoint()

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