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Refactor checkpoint name in BERT and MobileBERT (#10424)

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* Refactor checkpoint name in BERT and MobileBERT

* Add option to check copies

* Add QuestionAnswering

* Add last models

* Make black happy
This commit is contained in:
Sylvain Gugger
2021-03-03 11:21:17 -05:00
committed by GitHub
parent 39f70a4058
commit 801ff969ce
3 changed files with 43 additions and 18 deletions
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13
src/transformers/models/bert/modeling_bert.py
View File

@@ -58,6 +58,7 @@ from .configuration_bert import BertConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "bert-base-uncased"
_CONFIG_FOR_DOC = "BertConfig"
_TOKENIZER_FOR_DOC = "BertTokenizer"
@@ -862,7 +863,7 @@ class BertModel(BertPreTrainedModel):
@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-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithPoolingAndCrossAttentions,
config_class=_CONFIG_FOR_DOC,
)
@@ -1273,7 +1274,7 @@ class BertForMaskedLM(BertPreTrainedModel):
@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-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
@@ -1468,7 +1469,7 @@ class BertForSequenceClassification(BertPreTrainedModel):
@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-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
@@ -1552,7 +1553,7 @@ class BertForMultipleChoice(BertPreTrainedModel):
@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-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
)
@@ -1647,7 +1648,7 @@ class BertForTokenClassification(BertPreTrainedModel):
@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-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
@@ -1737,7 +1738,7 @@ class BertForQuestionAnswering(BertPreTrainedModel):
@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-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)

22
src/transformers/models/mobilebert/modeling_mobilebert.py
View File

@@ -56,6 +56,7 @@ from .configuration_mobilebert import MobileBertConfig
logger = logging.get_logger(__name__)
_CHECKPOINT_FOR_DOC = "google/mobilebert-uncased"
_CONFIG_FOR_DOC = "MobileBertConfig"
_TOKENIZER_FOR_DOC = "MobileBertTokenizer"
@@ -818,7 +819,7 @@ class MobileBertModel(MobileBertPreTrainedModel):
@add_start_docstrings_to_model_forward(MOBILEBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/mobilebert-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=BaseModelOutputWithPooling,
config_class=_CONFIG_FOR_DOC,
)
@@ -1033,7 +1034,7 @@ class MobileBertForMaskedLM(MobileBertPreTrainedModel):
@add_start_docstrings_to_model_forward(MOBILEBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/mobilebert-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MaskedLMOutput,
config_class=_CONFIG_FOR_DOC,
)
@@ -1204,20 +1205,22 @@ class MobileBertForNextSentencePrediction(MobileBertPreTrainedModel):
""",
MOBILEBERT_START_DOCSTRING,
)
# Copied from transformers.models.bert.modeling_bert.BertForSequenceClassification with Bert->MobileBert all-casing
class MobileBertForSequenceClassification(MobileBertPreTrainedModel):
def __init__(self, config):
super().__init__(config)
self.num_labels = config.num_labels
self.mobilebert = MobileBertModel(config)
self.dropout = nn.Dropout(config.hidden_dropout_prob)
self.classifier = nn.Linear(config.hidden_size, self.num_labels)
self.classifier = nn.Linear(config.hidden_size, config.num_labels)
self.init_weights()
@add_start_docstrings_to_model_forward(MOBILEBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/mobilebert-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=SequenceClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)
@@ -1253,7 +1256,9 @@ class MobileBertForSequenceClassification(MobileBertPreTrainedModel):
output_hidden_states=output_hidden_states,
return_dict=return_dict,
)
pooled_output = outputs[1]
pooled_output = self.dropout(pooled_output)
logits = self.classifier(pooled_output)
@@ -1286,6 +1291,7 @@ class MobileBertForSequenceClassification(MobileBertPreTrainedModel):
""",
MOBILEBERT_START_DOCSTRING,
)
# Copied from transformers.models.bert.modeling_bert.BertForQuestionAnswering with Bert->MobileBert all-casing
class MobileBertForQuestionAnswering(MobileBertPreTrainedModel):
_keys_to_ignore_on_load_unexpected = [r"pooler"]
@@ -1302,7 +1308,7 @@ class MobileBertForQuestionAnswering(MobileBertPreTrainedModel):
@add_start_docstrings_to_model_forward(MOBILEBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/mobilebert-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=QuestionAnsweringModelOutput,
config_class=_CONFIG_FOR_DOC,
)
@@ -1403,10 +1409,11 @@ class MobileBertForMultipleChoice(MobileBertPreTrainedModel):
)
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/mobilebert-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=MultipleChoiceModelOutput,
config_class=_CONFIG_FOR_DOC,
)
# Copied from transformers.models.bert.modeling_bert.BertForMultipleChoice.forward with Bert->MobileBert all-casing
def forward(
self,
input_ids=None,
@@ -1481,6 +1488,7 @@ class MobileBertForMultipleChoice(MobileBertPreTrainedModel):
""",
MOBILEBERT_START_DOCSTRING,
)
# Copied from transformers.models.bert.modeling_bert.BertForTokenClassification with Bert->MobileBert all-casing
class MobileBertForTokenClassification(MobileBertPreTrainedModel):
_keys_to_ignore_on_load_unexpected = [r"pooler"]
@@ -1498,7 +1506,7 @@ class MobileBertForTokenClassification(MobileBertPreTrainedModel):
@add_start_docstrings_to_model_forward(MOBILEBERT_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
@add_code_sample_docstrings(
tokenizer_class=_TOKENIZER_FOR_DOC,
checkpoint="google/mobilebert-uncased",
checkpoint=_CHECKPOINT_FOR_DOC,
output_type=TokenClassifierOutput,
config_class=_CONFIG_FOR_DOC,
)