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Unverified Commit f5af8736 authored by Patrick von Platen's avatar Patrick von Platen Committed by GitHub
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[Docs] More general docstrings (#14028) 

* up

* finish

* up

* up

* finish
parent 47489a69
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Showing with 83 additions and 83 deletions
src/transformers/models/deberta_v2/modeling_deberta_v2.py
View file @ f5af8736
......@@ -974,7 +974,7 @@ class DebertaV2Model(DebertaV2PreTrainedModel):
@add_start_docstrings_to_model_forward(DEBERTA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1081,7 +1081,7 @@ class DebertaV2ForMaskedLM(DebertaV2PreTrainedModel):
@add_start_docstrings_to_model_forward(DEBERTA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1222,7 +1222,7 @@ class DebertaV2ForSequenceClassification(DebertaV2PreTrainedModel):
@add_start_docstrings_to_model_forward(DEBERTA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1318,7 +1318,7 @@ class DebertaV2ForTokenClassification(DebertaV2PreTrainedModel):
@add_start_docstrings_to_model_forward(DEBERTA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1406,7 +1406,7 @@ class DebertaV2ForQuestionAnswering(DebertaV2PreTrainedModel):
@add_start_docstrings_to_model_forward(DEBERTA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/deberta_v2/modeling_tf_deberta_v2.py
View file @ f5af8736
......@@ -1223,7 +1223,7 @@ class TFDebertaV2Model(TFDebertaV2PreTrainedModel):
@add_start_docstrings_to_model_forward(DEBERTA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFBaseModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1296,7 +1296,7 @@ class TFDebertaV2ForMaskedLM(TFDebertaV2PreTrainedModel, TFMaskedLanguageModelin
@add_start_docstrings_to_model_forward(DEBERTA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1399,7 +1399,7 @@ class TFDebertaV2ForSequenceClassification(TFDebertaV2PreTrainedModel, TFSequenc
@add_start_docstrings_to_model_forward(DEBERTA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1497,7 +1497,7 @@ class TFDebertaV2ForTokenClassification(TFDebertaV2PreTrainedModel, TFTokenClass
@add_start_docstrings_to_model_forward(DEBERTA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFTokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1591,7 +1591,7 @@ class TFDebertaV2ForQuestionAnswering(TFDebertaV2PreTrainedModel, TFQuestionAnsw
@add_start_docstrings_to_model_forward(DEBERTA_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFQuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/distilbert/modeling_distilbert.py
View file @ f5af8736
......@@ -508,7 +508,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -604,7 +604,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -702,7 +702,7 @@ class DistilBertForSequenceClassification(DistilBertPreTrainedModel):
@add_start_docstrings_to_model_forward(DISTILBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -818,7 +818,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -935,7 +935,7 @@ class DistilBertForTokenClassification(DistilBertPreTrainedModel):
@add_start_docstrings_to_model_forward(DISTILBERT_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/distilbert/modeling_tf_distilbert.py
View file @ f5af8736
......@@ -543,7 +543,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFBaseModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -658,7 +658,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -759,7 +759,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -854,7 +854,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFTokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -962,7 +962,7 @@ class TFDistilBertForMultipleChoice(TFDistilBertPreTrainedModel, TFMultipleChoic
DISTILBERT_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length")
)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1088,7 +1088,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFQuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/electra/modeling_electra.py
View file @ f5af8736
......@@ -833,7 +833,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithCrossAttentions,
config_class=_CONFIG_FOR_DOC,
......@@ -941,7 +941,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1136,7 +1136,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1218,7 +1218,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1307,7 +1307,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1408,7 +1408,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/electra/modeling_tf_electra.py
View file @ f5af8736
......@@ -950,7 +950,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFBaseModelOutputWithPastAndCrossAttentions,
config_class=_CONFIG_FOR_DOC,
......@@ -1211,7 +1211,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1336,7 +1336,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1444,7 +1444,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFMultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1584,7 +1584,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFTokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1681,7 +1681,7 @@ 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,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFQuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/flaubert/modeling_flaubert.py
View file @ f5af8736
......@@ -148,7 +148,7 @@ class FlaubertModel(XLMModel):
@add_start_docstrings_to_model_forward(FLAUBERT_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/flaubert/modeling_tf_flaubert.py
View file @ f5af8736
......@@ -236,7 +236,7 @@ class TFFlaubertModel(TFFlaubertPreTrainedModel):
@add_start_docstrings_to_model_forward(FLAUBERT_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFBaseModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -820,7 +820,7 @@ class TFFlaubertWithLMHeadModel(TFFlaubertPreTrainedModel):
@add_start_docstrings_to_model_forward(FLAUBERT_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFFlaubertWithLMHeadModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/fnet/modeling_fnet.py
View file @ f5af8736
......@@ -545,7 +545,7 @@ class FNetModel(FNetPreTrainedModel):
@add_start_docstrings_to_model_forward(FNET_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -733,7 +733,7 @@ class FNetForMaskedLM(FNetPreTrainedModel):
@add_start_docstrings_to_model_forward(FNET_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -889,7 +889,7 @@ class FNetForSequenceClassification(FNetPreTrainedModel):
@add_start_docstrings_to_model_forward(FNET_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -961,7 +961,7 @@ class FNetForMultipleChoice(FNetPreTrainedModel):
@add_start_docstrings_to_model_forward(FNET_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1042,7 +1042,7 @@ class FNetForTokenClassification(FNetPreTrainedModel):
@add_start_docstrings_to_model_forward(FNET_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1111,7 +1111,7 @@ class FNetForQuestionAnswering(FNetPreTrainedModel):
@add_start_docstrings_to_model_forward(FNET_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/fsmt/modeling_fsmt.py
View file @ f5af8736
......@@ -1007,7 +1007,7 @@ class FSMTModel(PretrainedFSMTModel):
@add_start_docstrings_to_model_forward(FSMT_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=Seq2SeqModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/funnel/modeling_funnel.py
View file @ f5af8736
......@@ -910,7 +910,7 @@ class FunnelBaseModel(FunnelPreTrainedModel):
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="funnel-transformer/small-base",
output_type=BaseModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -987,7 +987,7 @@ class FunnelModel(FunnelPreTrainedModel):
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1174,7 +1174,7 @@ class FunnelForMaskedLM(FunnelPreTrainedModel):
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1248,7 +1248,7 @@ class FunnelForSequenceClassification(FunnelPreTrainedModel):
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="funnel-transformer/small-base",
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1338,7 +1338,7 @@ class FunnelForMultipleChoice(FunnelPreTrainedModel):
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="funnel-transformer/small-base",
output_type=MultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1424,7 +1424,7 @@ class FunnelForTokenClassification(FunnelPreTrainedModel):
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1506,7 +1506,7 @@ class FunnelForQuestionAnswering(FunnelPreTrainedModel):
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/funnel/modeling_tf_funnel.py
View file @ f5af8736
......@@ -1126,7 +1126,7 @@ class TFFunnelBaseModel(TFFunnelPreTrainedModel):
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="funnel-transformer/small-base",
output_type=TFBaseModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1187,7 +1187,7 @@ class TFFunnelModel(TFFunnelPreTrainedModel):
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="funnel-transformer/small",
output_type=TFBaseModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1337,7 +1337,7 @@ class TFFunnelForMaskedLM(TFFunnelPreTrainedModel, TFMaskedLanguageModelingLoss)
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="funnel-transformer/small",
output_type=TFMaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1426,7 +1426,7 @@ class TFFunnelForSequenceClassification(TFFunnelPreTrainedModel, TFSequenceClass
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="funnel-transformer/small-base",
output_type=TFSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1525,7 +1525,7 @@ class TFFunnelForMultipleChoice(TFFunnelPreTrainedModel, TFMultipleChoiceLoss):
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="funnel-transformer/small-base",
output_type=TFMultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1655,7 +1655,7 @@ class TFFunnelForTokenClassification(TFFunnelPreTrainedModel, TFTokenClassificat
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="funnel-transformer/small",
output_type=TFTokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1747,7 +1747,7 @@ class TFFunnelForQuestionAnswering(TFFunnelPreTrainedModel, TFQuestionAnsweringL
@add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="funnel-transformer/small",
output_type=TFQuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/gpt2/modeling_gpt2.py
View file @ f5af8736
......@@ -732,7 +732,7 @@ class GPT2Model(GPT2PreTrainedModel):
@add_start_docstrings_to_model_forward(GPT2_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithPastAndCrossAttentions,
config_class=_CONFIG_FOR_DOC,
......@@ -1009,7 +1009,7 @@ class GPT2LMHeadModel(GPT2PreTrainedModel):
@add_start_docstrings_to_model_forward(GPT2_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=CausalLMOutputWithCrossAttentions,
config_class=_CONFIG_FOR_DOC,
......@@ -1338,7 +1338,7 @@ class GPT2ForSequenceClassification(GPT2PreTrainedModel):
@add_start_docstrings_to_model_forward(GPT2_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="microsoft/DialogRPT-updown",
output_type=SequenceClassifierOutputWithPast,
config_class=_CONFIG_FOR_DOC,
......@@ -1457,7 +1457,7 @@ class GPT2ForTokenClassification(GPT2PreTrainedModel):
@add_start_docstrings_to_model_forward(GPT2_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="microsoft/DialogRPT-updown",
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/gpt2/modeling_tf_gpt2.py
View file @ f5af8736
......@@ -587,7 +587,7 @@ class TFGPT2Model(TFGPT2PreTrainedModel):
@add_start_docstrings_to_model_forward(GPT2_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFBaseModelOutputWithPast,
config_class=_CONFIG_FOR_DOC,
......@@ -679,7 +679,7 @@ class TFGPT2LMHeadModel(TFGPT2PreTrainedModel, TFCausalLanguageModelingLoss):
@add_start_docstrings_to_model_forward(GPT2_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFCausalLMOutputWithPast,
config_class=_CONFIG_FOR_DOC,
......@@ -959,7 +959,7 @@ class TFGPT2ForSequenceClassification(TFGPT2PreTrainedModel, TFSequenceClassific
@add_start_docstrings_to_model_forward(GPT2_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint="microsoft/DialogRPT-updown",
output_type=TFSequenceClassifierOutputWithPast,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/gpt_neo/modeling_gpt_neo.py
View file @ f5af8736
......@@ -497,7 +497,7 @@ class GPTNeoModel(GPTNeoPreTrainedModel):
@add_start_docstrings_to_model_forward(GPT_NEO_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithPastAndCrossAttentions,
config_class=_CONFIG_FOR_DOC,
......@@ -713,7 +713,7 @@ class GPTNeoForCausalLM(GPTNeoPreTrainedModel):
@add_start_docstrings_to_model_forward(GPT_NEO_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=CausalLMOutputWithCrossAttentions,
config_class=_CONFIG_FOR_DOC,
......@@ -827,7 +827,7 @@ class GPTNeoForSequenceClassification(GPTNeoPreTrainedModel):
@add_start_docstrings_to_model_forward(GPT_NEO_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutputWithPast,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/gptj/modeling_gptj.py
View file @ f5af8736
......@@ -491,7 +491,7 @@ class GPTJModel(GPTJPreTrainedModel):
@add_start_docstrings_to_model_forward(GPTJ_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithPast,
config_class=_CONFIG_FOR_DOC,
......@@ -743,7 +743,7 @@ class GPTJForCausalLM(GPTJPreTrainedModel):
@add_start_docstrings_to_model_forward(GPTJ_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=CausalLMOutputWithPast,
config_class=_CONFIG_FOR_DOC,
......@@ -864,7 +864,7 @@ class GPTJForSequenceClassification(GPTJPreTrainedModel):
@add_start_docstrings_to_model_forward(GPTJ_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutputWithPast,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/ibert/modeling_ibert.py
View file @ f5af8736
......@@ -772,7 +772,7 @@ class IBertModel(IBertPreTrainedModel):
@add_start_docstrings_to_model_forward(IBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithPoolingAndCrossAttentions,
config_class=_CONFIG_FOR_DOC,
......@@ -875,7 +875,7 @@ class IBertForMaskedLM(IBertPreTrainedModel):
@add_start_docstrings_to_model_forward(IBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -983,7 +983,7 @@ class IBertForSequenceClassification(IBertPreTrainedModel):
@add_start_docstrings_to_model_forward(IBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1066,7 +1066,7 @@ class IBertForMultipleChoice(IBertPreTrainedModel):
@add_start_docstrings_to_model_forward(IBERT_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1160,7 +1160,7 @@ class IBertForTokenClassification(IBertPreTrainedModel):
@add_start_docstrings_to_model_forward(IBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -1269,7 +1269,7 @@ class IBertForQuestionAnswering(IBertPreTrainedModel):
@add_start_docstrings_to_model_forward(IBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/led/modeling_led.py
View file @ f5af8736
......@@ -2174,7 +2174,7 @@ class LEDModel(LEDPreTrainedModel):
@add_start_docstrings_to_model_forward(LED_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=Seq2SeqModelOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -2468,7 +2468,7 @@ class LEDForSequenceClassification(LEDPreTrainedModel):
@add_start_docstrings_to_model_forward(LED_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=Seq2SeqSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -2578,7 +2578,7 @@ class LEDForQuestionAnswering(LEDPreTrainedModel):
@add_start_docstrings_to_model_forward(LED_INPUTS_DOCSTRING)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=Seq2SeqQuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/led/modeling_tf_led.py
View file @ f5af8736
......@@ -2230,7 +2230,7 @@ class TFLEDModel(TFLEDPreTrainedModel):
@add_start_docstrings_to_model_forward(LED_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TFLEDSeq2SeqModelOutput,
config_class=_CONFIG_FOR_DOC,
......
src/transformers/models/longformer/modeling_longformer.py
View file @ f5af8736
......@@ -1822,7 +1822,7 @@ class LongformerForSequenceClassification(LongformerPreTrainedModel):
@add_start_docstrings_to_model_forward(LONGFORMER_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=LongformerSequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -2084,7 +2084,7 @@ class LongformerForTokenClassification(LongformerPreTrainedModel):
@add_start_docstrings_to_model_forward(LONGFORMER_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=LongformerTokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
......@@ -2176,7 +2176,7 @@ class LongformerForMultipleChoice(LongformerPreTrainedModel):
LONGFORMER_INPUTS_DOCSTRING.format("batch_size, num_choices, sequence_length")
)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
processor_class=_TOKENIZER_FOR_DOC,
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=LongformerMultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
......
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