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Unverified Commit 90ecc296 authored by Daniel Hug's avatar Daniel Hug Committed by GitHub
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Refactoring checkpoint names for multiple models (#10527) 

* Refactor checkpoint name in ALBERT and ALBERT_tf

* Refactor checkpoint name in BART and BART_tf

* Refactor checkpoint name in BERT generation

* Refactor checkpoint name in Blenderbot_tf

* Refactor checkpoint name in Blenderbot_small_tf

* Refactor checkpoint name in ConvBERT AND CONVBERT_TF

* Refactor checkpoint name in CTRL AND CTRL_TF

* Refactor checkpoint name in DistilBERT AND DistilBERT_TF

* Refactor checkpoint name in DistilBERT redo

* Refactor checkpoint name in Electra and Electra_tf

* Refactor checkpoint name in FlauBERT and FlauBERT_tf

* Refactor checkpoint name in FSMT

* Refactor checkpoint name in GPT2 and GPT2_tf

* Refactor checkpoint name in IBERT

* Refactor checkpoint name in LED and LED_tf

* Refactor checkpoint name in Longformer and Longformer_tf

* Refactor checkpoint name in Lxmert and Lxmert_tf

* Refactor checkpoint name in Marian_tf

* Refactor checkpoint name in MBART and MBART_tf

* Refactor checkpoint name in MobileBERT and MobileBERT_tf

* Refactor checkpoint name in mpnet and mpnet_tf

* Refactor checkpoint name in openai and openai_tf

* Refactor checkpoint name in pegasus_tf

* Refactor checkpoint name in reformer

* Refactor checkpoint name in Roberta and Roberta_tf

* Refactor checkpoint name in SqueezeBert

* Refactor checkpoint name in Transformer_xl and Transformer_xl_tf

* Refactor checkpoint name in XLM and XLM_tf

* Refactor checkpoint name in XLNET and XLNET_tf

* Refactor checkpoint name in BERT_tf

* run make tests, style, quality, fixup
parent defe9e20
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Showing with 93 additions and 75 deletions
src/transformers/models/albert/modeling_albert.py
View file @ 90ecc296
......@@ -52,6 +52,7 @@ from .configuration_albert import AlbertConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "albert-base-v2"
_CONFIG_FOR_DOC = "AlbertConfig"
_TOKENIZER_FOR_DOC = "AlbertTokenizer"
......@@ -658,7 +659,7 @@ class AlbertModel(AlbertPreTrainedModel):
@add_start_docstrings_to_model_forward(ALBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="albert-base-v2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithPooling,
config_class=_CONFIG_FOR_DOC,
)
......@@ -901,7 +902,7 @@ class AlbertForMaskedLM(AlbertPreTrainedModel):
@add_start_docstrings_to_model_forward(ALBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="albert-base-v2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -979,7 +980,7 @@ class AlbertForSequenceClassification(AlbertPreTrainedModel):
@add_start_docstrings_to_model_forward(ALBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="albert-base-v2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1067,7 +1068,7 @@ class AlbertForTokenClassification(AlbertPreTrainedModel):
@add_start_docstrings_to_model_forward(ALBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="albert-base-v2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1155,7 +1156,7 @@ class AlbertForQuestionAnswering(AlbertPreTrainedModel):
@add_start_docstrings_to_model_forward(ALBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="albert-base-v2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1254,7 +1255,7 @@ class AlbertForMultipleChoice(AlbertPreTrainedModel):
@add_start_docstrings_to_model_forward(ALBERT_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="albert-base-v2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/albert/modeling_tf_albert.py
View file @ 90ecc296
......@@ -59,6 +59,7 @@ from .configuration_albert import AlbertConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "albert-base-v2"
_CONFIG_FOR_DOC = "AlbertConfig"
_TOKENIZER_FOR_DOC = "AlbertTokenizer"
......@@ -780,7 +781,7 @@ class TFAlbertModel(TFAlbertPreTrainedModel):
@add_start_docstrings_to_model_forward(ALBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="albert-base-v2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFBaseModelOutputWithPooling,
config_class=_CONFIG_FOR_DOC,
)
......@@ -998,7 +999,7 @@ class TFAlbertForMaskedLM(TFAlbertPreTrainedModel, TFMaskedLanguageModelingLoss)
@add_start_docstrings_to_model_forward(ALBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="albert-base-v2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1103,7 +1104,7 @@ class TFAlbertForSequenceClassification(TFAlbertPreTrainedModel, TFSequenceClass
@add_start_docstrings_to_model_forward(ALBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="albert-base-v2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1207,7 +1208,7 @@ class TFAlbertForTokenClassification(TFAlbertPreTrainedModel, TFTokenClassificat
@add_start_docstrings_to_model_forward(ALBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="albert-base-v2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFTokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1308,7 +1309,7 @@ class TFAlbertForQuestionAnswering(TFAlbertPreTrainedModel, TFQuestionAnsweringL
@add_start_docstrings_to_model_forward(ALBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="albert-base-v2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFQuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1436,7 +1437,7 @@ class TFAlbertForMultipleChoice(TFAlbertPreTrainedModel, TFMultipleChoiceLoss):
@add_start_docstrings_to_model_forward(ALBERT_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="albert-base-v2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/bart/modeling_bart.py
View file @ 90ecc296
......@@ -49,6 +49,7 @@ from .configuration_bart import BartConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "facebook/bart-large"
_CONFIG_FOR_DOC = "BartConfig"
_TOKENIZER_FOR_DOC = "BartTokenizer"
......@@ -1109,7 +1110,7 @@ class BartModel(BartPretrainedModel):
@add_start_docstrings_to_model_forward(BART_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="facebook/bart-large",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=Seq2SeqModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1377,7 +1378,7 @@ class BartForSequenceClassification(BartPretrainedModel):
@add_start_docstrings_to_model_forward(BART_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="facebook/bart-large",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=Seq2SeqSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1482,7 +1483,7 @@ class BartForQuestionAnswering(BartPretrainedModel):
@add_start_docstrings_to_model_forward(BART_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="facebook/bart-large",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=Seq2SeqQuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/bart/modeling_tf_bart.py
View file @ 90ecc296
......@@ -52,6 +52,7 @@ from .configuration_bart import BartConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "facebook/bart-large"
_CONFIG_FOR_DOC = "BartConfig"
_TOKENIZER_FOR_DOC = "BartTokenizer"
......@@ -1170,7 +1171,7 @@ class TFBartModel(TFBartPretrainedModel):
@add_start_docstrings_to_model_forward(BART_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="facebook/bart-large",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFSeq2SeqModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/bert/modeling_tf_bert.py
View file @ 90ecc296
......@@ -64,6 +64,7 @@ from .configuration_bert import BertConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "bert-base-cased"
_CONFIG_FOR_DOC = "BertConfig"
_TOKENIZER_FOR_DOC = "BertTokenizer"
......@@ -850,7 +851,7 @@ class TFBertModel(TFBertPreTrainedModel):
@add_start_docstrings_to_model_forward(BERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="bert-base-cased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFBaseModelOutputWithPooling,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1067,7 +1068,7 @@ class TFBertForMaskedLM(TFBertPreTrainedModel, TFMaskedLanguageModelingLoss):
@add_start_docstrings_to_model_forward(BERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="bert-base-cased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1171,7 +1172,7 @@ class TFBertLMHeadModel(TFBertPreTrainedModel, TFCausalLanguageModelingLoss):
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="bert-base-cased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFCausalLMOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1382,7 +1383,7 @@ class TFBertForSequenceClassification(TFBertPreTrainedModel, TFSequenceClassific
@add_start_docstrings_to_model_forward(BERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="bert-base-cased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1492,7 +1493,7 @@ class TFBertForMultipleChoice(TFBertPreTrainedModel, TFMultipleChoiceLoss):
@add_start_docstrings_to_model_forward(BERT_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="bert-base-cased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1648,7 +1649,7 @@ class TFBertForTokenClassification(TFBertPreTrainedModel, TFTokenClassificationL
@add_start_docstrings_to_model_forward(BERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="bert-base-cased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFTokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1755,7 +1756,7 @@ class TFBertForQuestionAnswering(TFBertPreTrainedModel, TFQuestionAnsweringLoss)
@add_start_docstrings_to_model_forward(BERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="bert-base-cased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFQuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/bert_generation/modeling_bert_generation.py
View file @ 90ecc296
......@@ -35,6 +35,7 @@ from .configuration_bert_generation import BertGenerationConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "google/bert_for_seq_generation_L-24_bbc_encoder"
_CONFIG_FOR_DOC = "BertGenerationConfig"
_TOKENIZER_FOR_DOC = "BertGenerationTokenizer"
......@@ -300,7 +301,7 @@ class BertGenerationEncoder(BertGenerationPreTrainedModel):
@add_start_docstrings_to_model_forward(BERT_GENERATION_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/bert_for_seq_generation_L-24_bbc_encoder",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithPastAndCrossAttentions,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/blenderbot/modeling_tf_blenderbot.py
View file @ 90ecc296
......@@ -54,6 +54,7 @@ from .configuration_blenderbot import BlenderbotConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "facebook/blenderbot-400M-distill"
_CONFIG_FOR_DOC = "BlenderbotConfig"
_TOKENIZER_FOR_DOC = "BlenderbotTokenizer"
......@@ -1186,7 +1187,7 @@ class TFBlenderbotModel(TFBlenderbotPreTrainedModel):
@add_start_docstrings_to_model_forward(BLENDERBOT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="facebook/blenderbot-400M-distill",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFSeq2SeqModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/blenderbot_small/modeling_tf_blenderbot_small.py
View file @ 90ecc296
......@@ -52,6 +52,7 @@ from .configuration_blenderbot_small import BlenderbotSmallConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "facebook/blenderbot_small-90M"
_CONFIG_FOR_DOC = "BlenderbotSmallConfig"
_TOKENIZER_FOR_DOC = "BlenderbotSmallTokenizer"
......@@ -1174,7 +1175,7 @@ class TFBlenderbotSmallModel(TFBlenderbotSmallPreTrainedModel):
@add_start_docstrings_to_model_forward(BLENDERBOT_SMALL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="facebook/blenderbot_small-90M",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFSeq2SeqModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/convbert/modeling_convbert.py
View file @ 90ecc296
......@@ -47,6 +47,7 @@ from .configuration_convbert import ConvBertConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "YituTech/conv-bert-base"
_CONFIG_FOR_DOC = "ConvBertConfig"
_TOKENIZER_FOR_DOC = "ConvBertTokenizer"
......@@ -773,7 +774,7 @@ class ConvBertModel(ConvBertPreTrainedModel):
@add_start_docstrings_to_model_forward(CONVBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="YituTech/conv-bert-base",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithCrossAttentions,
config_class=_CONFIG_FOR_DOC,
)
......@@ -870,7 +871,7 @@ class ConvBertForMaskedLM(ConvBertPreTrainedModel):
@add_start_docstrings_to_model_forward(CONVBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="YituTech/conv-bert-base",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -969,7 +970,7 @@ class ConvBertForSequenceClassification(ConvBertPreTrainedModel):
@add_start_docstrings_to_model_forward(CONVBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="YituTech/conv-bert-base",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1053,7 +1054,7 @@ class ConvBertForMultipleChoice(ConvBertPreTrainedModel):
)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="YituTech/conv-bert-base",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1145,7 +1146,7 @@ class ConvBertForTokenClassification(ConvBertPreTrainedModel):
@add_start_docstrings_to_model_forward(CONVBERT_INPUTS_DOCSTRING.format("(batch_size, sequence_length)"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="YituTech/conv-bert-base",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1232,7 +1233,7 @@ class ConvBertForQuestionAnswering(ConvBertPreTrainedModel):
@add_start_docstrings_to_model_forward(CONVBERT_INPUTS_DOCSTRING.format("(batch_size, sequence_length)"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="YituTech/conv-bert-base",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/convbert/modeling_tf_convbert.py
View file @ 90ecc296
......@@ -51,6 +51,7 @@ from .configuration_convbert import ConvBertConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "YituTech/conv-bert-base"
_CONFIG_FOR_DOC = "ConvBertConfig"
_TOKENIZER_FOR_DOC = "ConvBertTokenizer"
......@@ -750,7 +751,7 @@ class TFConvBertModel(TFConvBertPreTrainedModel):
@add_start_docstrings_to_model_forward(CONVBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="YituTech/conv-bert-base",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFBaseModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -882,7 +883,7 @@ class TFConvBertForMaskedLM(TFConvBertPreTrainedModel, TFMaskedLanguageModelingL
@add_start_docstrings_to_model_forward(CONVBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="YituTech/conv-bert-base",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1003,7 +1004,7 @@ class TFConvBertForSequenceClassification(TFConvBertPreTrainedModel, TFSequenceC
@add_start_docstrings_to_model_forward(CONVBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="YituTech/conv-bert-base",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1112,7 +1113,7 @@ class TFConvBertForMultipleChoice(TFConvBertPreTrainedModel, TFMultipleChoiceLos
)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="YituTech/conv-bert-base",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1247,7 +1248,7 @@ class TFConvBertForTokenClassification(TFConvBertPreTrainedModel, TFTokenClassif
@add_start_docstrings_to_model_forward(CONVBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="YituTech/conv-bert-base",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFTokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1342,7 +1343,7 @@ class TFConvBertForQuestionAnswering(TFConvBertPreTrainedModel, TFQuestionAnswer
@add_start_docstrings_to_model_forward(CONVBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="YituTech/conv-bert-base",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFQuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/ctrl/modeling_ctrl.py
View file @ 90ecc296
......@@ -31,6 +31,7 @@ from .configuration_ctrl import CTRLConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "ctrl"
_CONFIG_FOR_DOC = "CTRLConfig"
_TOKENIZER_FOR_DOC = "CTRLTokenizer"
......@@ -355,7 +356,7 @@ class CTRLModel(CTRLPreTrainedModel):
@add_start_docstrings_to_model_forward(CTRL_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="ctrl",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithPast,
config_class=_CONFIG_FOR_DOC,
)
......@@ -515,7 +516,7 @@ class CTRLLMHeadModel(CTRLPreTrainedModel):
@add_start_docstrings_to_model_forward(CTRL_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="ctrl",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=CausalLMOutputWithPast,
config_class=_CONFIG_FOR_DOC,
)
......@@ -618,7 +619,7 @@ class CTRLForSequenceClassification(CTRLPreTrainedModel):
@add_start_docstrings_to_model_forward(CTRL_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="ctrl",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/ctrl/modeling_tf_ctrl.py
View file @ 90ecc296
......@@ -38,6 +38,7 @@ from .configuration_ctrl import CTRLConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "ctrl"
_CONFIG_FOR_DOC = "CTRLConfig"
_TOKENIZER_FOR_DOC = "CTRLTokenizer"
......@@ -543,7 +544,7 @@ class TFCTRLModel(TFCTRLPreTrainedModel):
@add_start_docstrings_to_model_forward(CTRL_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="ctrl",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFBaseModelOutputWithPast,
config_class=_CONFIG_FOR_DOC,
)
......@@ -671,7 +672,7 @@ class TFCTRLLMHeadModel(TFCTRLPreTrainedModel, TFCausalLanguageModelingLoss):
@add_start_docstrings_to_model_forward(CTRL_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="ctrl",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFCausalLMOutputWithPast,
config_class=_CONFIG_FOR_DOC,
)
......@@ -795,7 +796,7 @@ class TFCTRLForSequenceClassification(TFCTRLPreTrainedModel, TFSequenceClassific
@add_start_docstrings_to_model_forward(CTRL_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="ctrl",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/distilbert/modeling_distilbert.py
View file @ 90ecc296
......@@ -52,7 +52,7 @@ from .configuration_distilbert import DistilBertConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "distilbert-base-uncased"
_CONFIG_FOR_DOC = "DistilBertConfig"
_TOKENIZER_FOR_DOC = "DistilBertTokenizer"
......@@ -441,11 +441,10 @@ class DistilBertModel(DistilBertPreTrainedModel):
@add_start_docstrings_to_model_forward(DISTILBERT_INPUTS_DOCSTRING.format("batch_size, num_choices"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="distilbert-base-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutput,
config_class=_CONFIG_FOR_DOC,
)
@add_code_sample_docstrings(tokenizer_class=_TOKENIZER_FOR_DOC, checkpoint="distilbert-base-uncased")
def forward(
self,
input_ids=None,
......@@ -517,7 +516,7 @@ class DistilBertForMaskedLM(DistilBertPreTrainedModel):
@add_start_docstrings_to_model_forward(DISTILBERT_INPUTS_DOCSTRING.format("batch_size, num_choices"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="distilbert-base-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -593,7 +592,7 @@ class DistilBertForSequenceClassification(DistilBertPreTrainedModel):
@add_start_docstrings_to_model_forward(DISTILBERT_INPUTS_DOCSTRING.format("batch_size, num_choices"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="distilbert-base-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -674,7 +673,7 @@ class DistilBertForQuestionAnswering(DistilBertPreTrainedModel):
@add_start_docstrings_to_model_forward(DISTILBERT_INPUTS_DOCSTRING.format("batch_size, num_choices"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="distilbert-base-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -770,7 +769,7 @@ class DistilBertForTokenClassification(DistilBertPreTrainedModel):
@add_start_docstrings_to_model_forward(DISTILBERT_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="distilbert-base-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/distilbert/modeling_tf_distilbert.py
View file @ 90ecc296
......@@ -53,6 +53,7 @@ from .configuration_distilbert import DistilBertConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "distilbert-base-uncased"
_CONFIG_FOR_DOC = "DistilBertConfig"
_TOKENIZER_FOR_DOC = "DistilBertTokenizer"
......@@ -545,7 +546,7 @@ class TFDistilBertModel(TFDistilBertPreTrainedModel):
@add_start_docstrings_to_model_forward(DISTILBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="distilbert-base-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFBaseModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -660,7 +661,7 @@ class TFDistilBertForMaskedLM(TFDistilBertPreTrainedModel, TFMaskedLanguageModel
@add_start_docstrings_to_model_forward(DISTILBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="distilbert-base-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -761,7 +762,7 @@ class TFDistilBertForSequenceClassification(TFDistilBertPreTrainedModel, TFSeque
@add_start_docstrings_to_model_forward(DISTILBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="distilbert-base-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -856,7 +857,7 @@ class TFDistilBertForTokenClassification(TFDistilBertPreTrainedModel, TFTokenCla
@add_start_docstrings_to_model_forward(DISTILBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="distilbert-base-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFTokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -964,7 +965,7 @@ class TFDistilBertForMultipleChoice(TFDistilBertPreTrainedModel, TFMultipleChoic
)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="distilbert-base-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1090,7 +1091,7 @@ class TFDistilBertForQuestionAnswering(TFDistilBertPreTrainedModel, TFQuestionAn
@add_start_docstrings_to_model_forward(DISTILBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="distilbert-base-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFQuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/electra/modeling_electra.py
View file @ 90ecc296
......@@ -54,6 +54,7 @@ from .configuration_electra import ElectraConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "google/electra-small-discriminator"
_CONFIG_FOR_DOC = "ElectraConfig"
_TOKENIZER_FOR_DOC = "ElectraTokenizer"
......@@ -812,7 +813,7 @@ class ElectraModel(ElectraPreTrainedModel):
@add_start_docstrings_to_model_forward(ELECTRA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/electra-small-discriminator",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithCrossAttentions,
config_class=_CONFIG_FOR_DOC,
)
......@@ -910,7 +911,7 @@ class ElectraForSequenceClassification(ElectraPreTrainedModel):
@add_start_docstrings_to_model_forward(ELECTRA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/electra-small-discriminator",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1092,7 +1093,7 @@ class ElectraForMaskedLM(ElectraPreTrainedModel):
@add_start_docstrings_to_model_forward(ELECTRA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/electra-small-discriminator",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1171,7 +1172,7 @@ class ElectraForTokenClassification(ElectraPreTrainedModel):
@add_start_docstrings_to_model_forward(ELECTRA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/electra-small-discriminator",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1258,7 +1259,7 @@ class ElectraForQuestionAnswering(ElectraPreTrainedModel):
@add_start_docstrings_to_model_forward(ELECTRA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/electra-small-discriminator",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1359,7 +1360,7 @@ class ElectraForMultipleChoice(ElectraPreTrainedModel):
@add_start_docstrings_to_model_forward(ELECTRA_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/electra-small-discriminator",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/electra/modeling_tf_electra.py
View file @ 90ecc296
......@@ -57,6 +57,7 @@ from .configuration_electra import ElectraConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "google/electra-small-discriminator"
_CONFIG_FOR_DOC = "ElectraConfig"
_TOKENIZER_FOR_DOC = "ElectraTokenizer"
......@@ -732,7 +733,7 @@ class TFElectraModel(TFElectraPreTrainedModel):
@add_start_docstrings_to_model_forward(ELECTRA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/electra-small-discriminator",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFBaseModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -951,7 +952,7 @@ class TFElectraForMaskedLM(TFElectraPreTrainedModel, TFMaskedLanguageModelingLos
@add_start_docstrings_to_model_forward(ELECTRA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/electra-small-generator",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1071,7 +1072,7 @@ class TFElectraForSequenceClassification(TFElectraPreTrainedModel, TFSequenceCla
@add_start_docstrings_to_model_forward(ELECTRA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/electra-small-discriminator",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1179,7 +1180,7 @@ class TFElectraForMultipleChoice(TFElectraPreTrainedModel, TFMultipleChoiceLoss)
@add_start_docstrings_to_model_forward(ELECTRA_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/electra-small-discriminator",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1316,7 +1317,7 @@ class TFElectraForTokenClassification(TFElectraPreTrainedModel, TFTokenClassific
@add_start_docstrings_to_model_forward(ELECTRA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/electra-small-discriminator",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFTokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -1413,7 +1414,7 @@ class TFElectraForQuestionAnswering(TFElectraPreTrainedModel, TFQuestionAnswerin
@add_start_docstrings_to_model_forward(ELECTRA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/electra-small-discriminator",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFQuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/flaubert/modeling_flaubert.py
View file @ 90ecc296
......@@ -38,6 +38,7 @@ from .configuration_flaubert import FlaubertConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "flaubert/flaubert_base_cased"
_CONFIG_FOR_DOC = "FlaubertConfig"
_TOKENIZER_FOR_DOC = "FlaubertTokenizer"
......@@ -143,7 +144,7 @@ class FlaubertModel(XLMModel):
@add_start_docstrings_to_model_forward(FLAUBERT_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="flaubert/flaubert_base_cased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/flaubert/modeling_tf_flaubert.py
View file @ 90ecc296
......@@ -52,6 +52,7 @@ from .configuration_flaubert import FlaubertConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "flaubert/flaubert_base_cased"
_CONFIG_FOR_DOC = "FlaubertConfig"
_TOKENIZER_FOR_DOC = "FlaubertTokenizer"
......@@ -236,7 +237,7 @@ class TFFlaubertModel(TFFlaubertPreTrainedModel):
@add_start_docstrings_to_model_forward(FLAUBERT_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="jplu/tf-flaubert-small-cased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFBaseModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......@@ -822,7 +823,7 @@ class TFFlaubertWithLMHeadModel(TFFlaubertPreTrainedModel):
@add_start_docstrings_to_model_forward(FLAUBERT_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="jplu/tf-flaubert-small-cased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFFlaubertWithLMHeadModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/fsmt/modeling_fsmt.py
View file @ 90ecc296
......@@ -57,6 +57,7 @@ from .configuration_fsmt import FSMTConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "facebook/wmt19-ru-en"
_CONFIG_FOR_DOC = "FSMTConfig"
_TOKENIZER_FOR_DOC = "FSMTTokenizer"
......@@ -989,7 +990,7 @@ class FSMTModel(PretrainedFSMTModel):
@add_start_docstrings_to_model_forward(FSMT_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="facebook/wmt19-ru-en",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=Seq2SeqModelOutput,
config_class=_CONFIG_FOR_DOC,
)
......
src/transformers/models/gpt2/modeling_gpt2.py
View file @ 90ecc296
......@@ -51,6 +51,7 @@ from .configuration_gpt2 import GPT2Config
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "gpt2"
_CONFIG_FOR_DOC = "GPT2Config"
_TOKENIZER_FOR_DOC = "GPT2Tokenizer"
......@@ -599,7 +600,7 @@ class GPT2Model(GPT2PreTrainedModel):
@add_start_docstrings_to_model_forward(GPT2_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="gpt2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithPastAndCrossAttentions,
config_class=_CONFIG_FOR_DOC,
)
......@@ -871,7 +872,7 @@ class GPT2LMHeadModel(GPT2PreTrainedModel):
@add_start_docstrings_to_model_forward(GPT2_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="gpt2",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=CausalLMOutputWithCrossAttentions,
config_class=_CONFIG_FOR_DOC,
)
......
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