本文整理汇总了Python中tokenization.validate_case_matches_checkpoint方法的典型用法代码示例。如果您正苦于以下问题:Python tokenization.validate_case_matches_checkpoint方法的具体用法?Python tokenization.validate_case_matches_checkpoint怎么用?Python tokenization.validate_case_matches_checkpoint使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类tokenization
的用法示例。
在下文中一共展示了tokenization.validate_case_matches_checkpoint方法的6个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: validate_flags_or_throw
# 需要导入模块: import tokenization [as 别名]
# 或者: from tokenization import validate_case_matches_checkpoint [as 别名]
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))
开发者ID:Nagakiran1,项目名称:Extending-Google-BERT-as-Question-and-Answering-model-and-Chatbot,代码行数:29,代码来源:run_squad.py
示例2: validate_flags_or_throw
# 需要导入模块: import tokenization [as 别名]
# 或者: from tokenization import validate_case_matches_checkpoint [as 别名]
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_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.do_eval:
if not FLAGS.eval_file:
raise ValueError(
"If `do_eval` is True, then `eval_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3: validate_flags_or_throw
# 需要导入模块: import tokenization [as 别名]
# 或者: from tokenization import validate_case_matches_checkpoint [as 别名]
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.precision:
bert_config.precision = FLAGS.precision
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: validate_flags_or_throw
# 需要导入模块: import tokenization [as 别名]
# 或者: from tokenization import validate_case_matches_checkpoint [as 别名]
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 FLAGS.disable_v2_bevior:
tf.compat.v1.disable_v2_behavior()
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.")
bert_config.set_additional_options(FLAGS.precision,
FLAGS.experimental_gelu,
FLAGS.optimized_softmax)
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: validate_flags_or_throw
# 需要导入模块: import tokenization [as 别名]
# 或者: from tokenization import validate_case_matches_checkpoint [as 别名]
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 FLAGS.disable_v2_bevior:
tf.compat.v1.disable_v2_behavior()
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.")
bert_config.set_additional_options(FLAGS.precision,
FLAGS.experimental_gelu)
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: validate_flags_or_throw
# 需要导入模块: import tokenization [as 别名]
# 或者: from tokenization import validate_case_matches_checkpoint [as 别名]
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_faile:
# 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))