本文整理汇总了Python中transformers.AlbertConfig方法的典型用法代码示例。如果您正苦于以下问题：Python transformers.AlbertConfig方法的具体用法？Python transformers.AlbertConfig怎么用？Python transformers.AlbertConfig使用的例子？那么恭喜您, 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transformers的用法示例。
在下文中一共展示了transformers.AlbertConfig方法的2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: prepare_config_and_inputs
# 需要导入模块: import transformers [as 别名]
# 或者: from transformers import AlbertConfig [as 别名]
def prepare_config_and_inputs(self):
input_ids = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
input_mask = None
if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2)
token_type_ids = None
if self.use_token_type_ids:
token_type_ids = ids_tensor([self.batch_size, self.seq_length], self.type_vocab_size)
sequence_labels = None
token_labels = None
choice_labels = None
if self.use_labels:
sequence_labels = ids_tensor([self.batch_size], self.type_sequence_label_size)
token_labels = ids_tensor([self.batch_size, self.seq_length], self.num_labels)
choice_labels = ids_tensor([self.batch_size], self.num_choices)
config = AlbertConfig(
vocab_size=self.vocab_size,
hidden_size=self.hidden_size,
num_hidden_layers=self.num_hidden_layers,
num_attention_heads=self.num_attention_heads,
intermediate_size=self.intermediate_size,
hidden_act=self.hidden_act,
hidden_dropout_prob=self.hidden_dropout_prob,
attention_probs_dropout_prob=self.attention_probs_dropout_prob,
max_position_embeddings=self.max_position_embeddings,
type_vocab_size=self.type_vocab_size,
initializer_range=self.initializer_range,
)
return config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels 示例2: setUp
# 需要导入模块: import transformers [as 别名]
# 或者: from transformers import AlbertConfig [as 别名]
def setUp(self):
self.model_tester = TFAlbertModelTest.TFAlbertModelTester(self)
self.config_tester = ConfigTester(self, config_class=AlbertConfig, hidden_size=37)