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Add ALBERT to AutoClasses

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This commit is contained in:
Elad Segal
2019-11-29 12:48:41 +02:00
committed by Lysandre Debut
parent 4a666885b5
commit ecf15ebf3b
3 changed files with 46 additions and 17 deletions
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15
transformers/configuration_auto.py
View File

@@ -28,6 +28,7 @@ from .configuration_roberta import RobertaConfig
from .configuration_distilbert import DistilBertConfig from .configuration_distilbert import DistilBertConfig
from .configuration_ctrl import CTRLConfig from .configuration_ctrl import CTRLConfig
from .configuration_camembert import CamembertConfig from .configuration_camembert import CamembertConfig
from .configuration_albert import AlbertConfig
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@@ -44,14 +45,15 @@ class AutoConfig(object):
The base model class to instantiate is selected as the first pattern matching The base model class to instantiate is selected as the first pattern matching
in the `pretrained_model_name_or_path` string (in the following order): in the `pretrained_model_name_or_path` string (in the following order):
- contains `distilbert`: DistilBertConfig (DistilBERT model) - contains `distilbert`: DistilBertConfig (DistilBERT model)
- contains `albert`: AlbertConfig (ALBERT model)
- contains `camembert`: CamembertConfig (CamemBERT model)
- contains `roberta`: RobertaConfig (RoBERTa model)
- contains `bert`: BertConfig (Bert model) - contains `bert`: BertConfig (Bert model)
- contains `openai-gpt`: OpenAIGPTConfig (OpenAI GPT model) - contains `openai-gpt`: OpenAIGPTConfig (OpenAI GPT model)
- contains `gpt2`: GPT2Config (OpenAI GPT-2 model) - contains `gpt2`: GPT2Config (OpenAI GPT-2 model)
- contains `transfo-xl`: TransfoXLConfig (Transformer-XL model) - contains `transfo-xl`: TransfoXLConfig (Transformer-XL model)
- contains `xlnet`: XLNetConfig (XLNet model) - contains `xlnet`: XLNetConfig (XLNet model)
- contains `xlm`: XLMConfig (XLM model) - contains `xlm`: XLMConfig (XLM model)
- contains `roberta`: RobertaConfig (RoBERTa model)
- contains `camembert`: CamembertConfig (CamemBERT model)
- contains `ctrl` : CTRLConfig (CTRL model) - contains `ctrl` : CTRLConfig (CTRL model)
This class cannot be instantiated using `__init__()` (throw an error). This class cannot be instantiated using `__init__()` (throw an error).
""" """
@@ -67,14 +69,15 @@ class AutoConfig(object):
The configuration class to instantiate is selected as the first pattern matching The configuration class to instantiate is selected as the first pattern matching
in the `pretrained_model_name_or_path` string (in the following order): in the `pretrained_model_name_or_path` string (in the following order):
- contains `distilbert`: DistilBertConfig (DistilBERT model) - contains `distilbert`: DistilBertConfig (DistilBERT model)
- contains `albert`: AlbertConfig (ALBERT model)
- contains `camembert`: CamembertConfig (CamemBERT model)
- contains `roberta`: RobertaConfig (RoBERTa model)
- contains `bert`: BertConfig (Bert model) - contains `bert`: BertConfig (Bert model)
- contains `openai-gpt`: OpenAIGPTConfig (OpenAI GPT model) - contains `openai-gpt`: OpenAIGPTConfig (OpenAI GPT model)
- contains `gpt2`: GPT2Config (OpenAI GPT-2 model) - contains `gpt2`: GPT2Config (OpenAI GPT-2 model)
- contains `transfo-xl`: TransfoXLConfig (Transformer-XL model) - contains `transfo-xl`: TransfoXLConfig (Transformer-XL model)
- contains `xlnet`: XLNetConfig (XLNet model) - contains `xlnet`: XLNetConfig (XLNet model)
- contains `xlm`: XLMConfig (XLM model) - contains `xlm`: XLMConfig (XLM model)
- contains `roberta`: RobertaConfig (RoBERTa model)
- contains `camembert`: CamembertConfig (CamemBERT model)
- contains `ctrl` : CTRLConfig (CTRL model) - contains `ctrl` : CTRLConfig (CTRL model)
Params: Params:
pretrained_model_name_or_path: either: pretrained_model_name_or_path: either:
@@ -122,6 +125,8 @@ class AutoConfig(object):
""" """
if 'distilbert' in pretrained_model_name_or_path: if 'distilbert' in pretrained_model_name_or_path:
return DistilBertConfig.from_pretrained(pretrained_model_name_or_path, **kwargs) return DistilBertConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
elif 'albert' in pretrained_model_name_or_path:
return AlbertConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
elif 'camembert' in pretrained_model_name_or_path: elif 'camembert' in pretrained_model_name_or_path:
return CamembertConfig.from_pretrained(pretrained_model_name_or_path, **kwargs) return CamembertConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
elif 'roberta' in pretrained_model_name_or_path: elif 'roberta' in pretrained_model_name_or_path:
@@ -142,4 +147,4 @@ class AutoConfig(object):
return CTRLConfig.from_pretrained(pretrained_model_name_or_path, **kwargs) return CTRLConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
raise ValueError("Unrecognized model identifier in {}. Should contains one of " raise ValueError("Unrecognized model identifier in {}. Should contains one of "
"'bert', 'openai-gpt', 'gpt2', 'transfo-xl', 'xlnet', " "'bert', 'openai-gpt', 'gpt2', 'transfo-xl', 'xlnet', "
"'xlm', 'roberta', 'camembert', 'ctrl'".format(pretrained_model_name_or_path)) "'xlm', 'roberta', 'distilbert', 'camembert', 'ctrl', 'albert'".format(pretrained_model_name_or_path))

33
transformers/modeling_auto.py
View File

@@ -28,6 +28,8 @@ from .modeling_xlm import XLMModel, XLMWithLMHeadModel, XLMForSequenceClassifica
from .modeling_roberta import RobertaModel, RobertaForMaskedLM, RobertaForSequenceClassification from .modeling_roberta import RobertaModel, RobertaForMaskedLM, RobertaForSequenceClassification
from .modeling_distilbert import DistilBertModel, DistilBertForQuestionAnswering, DistilBertForMaskedLM, DistilBertForSequenceClassification from .modeling_distilbert import DistilBertModel, DistilBertForQuestionAnswering, DistilBertForMaskedLM, DistilBertForSequenceClassification
from .modeling_camembert import CamembertModel, CamembertForMaskedLM, CamembertForSequenceClassification, CamembertForMultipleChoice from .modeling_camembert import CamembertModel, CamembertForMaskedLM, CamembertForSequenceClassification, CamembertForMultipleChoice
from .modeling_camembert import CamembertModel, CamembertForMaskedLM, CamembertForSequenceClassification, CamembertForMultipleChoice
from .modeling_albert import AlbertModel, AlbertForMaskedLM, AlbertForSequenceClassification, AlbertForQuestionAnswering
from .modeling_utils import PreTrainedModel, SequenceSummary from .modeling_utils import PreTrainedModel, SequenceSummary
@@ -49,15 +51,16 @@ class AutoModel(object):
The base model class to instantiate is selected as the first pattern matching The base model class to instantiate is selected as the first pattern matching
in the `pretrained_model_name_or_path` string (in the following order): in the `pretrained_model_name_or_path` string (in the following order):
- contains `distilbert`: DistilBertModel (DistilBERT model) - contains `distilbert`: DistilBertModel (DistilBERT model)
- contains `albert`: AlbertModel (ALBERT model)
- contains `camembert`: CamembertModel (CamemBERT model) - contains `camembert`: CamembertModel (CamemBERT model)
- contains `roberta`: RobertaModel (RoBERTa model) - contains `roberta`: RobertaModel (RoBERTa model)
- contains `bert`: BertModel (Bert model) - contains `bert`: BertModel (Bert model)
- contains `openai-gpt`: OpenAIGPTModel (OpenAI GPT model) - contains `openai-gpt`: OpenAIGPTModel (OpenAI GPT model)
- contains `gpt2`: GPT2Model (OpenAI GPT-2 model) - contains `gpt2`: GPT2Model (OpenAI GPT-2 model)
- contains `ctrl`: CTRLModel (Salesforce CTRL model)
- contains `transfo-xl`: TransfoXLModel (Transformer-XL model) - contains `transfo-xl`: TransfoXLModel (Transformer-XL model)
- contains `xlnet`: XLNetModel (XLNet model) - contains `xlnet`: XLNetModel (XLNet model)
- contains `xlm`: XLMModel (XLM model) - contains `xlm`: XLMModel (XLM model)
- contains `ctrl`: CTRLModel (Salesforce CTRL model)
This class cannot be instantiated using `__init__()` (throws an error). This class cannot be instantiated using `__init__()` (throws an error).
""" """
@@ -73,15 +76,16 @@ class AutoModel(object):
The model class to instantiate is selected as the first pattern matching The model class to instantiate is selected as the first pattern matching
in the `pretrained_model_name_or_path` string (in the following order): in the `pretrained_model_name_or_path` string (in the following order):
- contains `distilbert`: DistilBertModel (DistilBERT model) - contains `distilbert`: DistilBertModel (DistilBERT model)
- contains `albert`: AlbertModel (ALBERT model)
- contains `camembert`: CamembertModel (CamemBERT model) - contains `camembert`: CamembertModel (CamemBERT model)
- contains `roberta`: RobertaModel (RoBERTa model) - contains `roberta`: RobertaModel (RoBERTa model)
- contains `bert`: BertModel (Bert model) - contains `bert`: BertModel (Bert model)
- contains `openai-gpt`: OpenAIGPTModel (OpenAI GPT model) - contains `openai-gpt`: OpenAIGPTModel (OpenAI GPT model)
- contains `gpt2`: GPT2Model (OpenAI GPT-2 model) - contains `gpt2`: GPT2Model (OpenAI GPT-2 model)
- contains `ctrl`: CTRLModel (Salesforce CTRL model)
- contains `transfo-xl`: TransfoXLModel (Transformer-XL model) - contains `transfo-xl`: TransfoXLModel (Transformer-XL model)
- contains `xlnet`: XLNetModel (XLNet model) - contains `xlnet`: XLNetModel (XLNet model)
- contains `xlm`: XLMModel (XLM model) - contains `xlm`: XLMModel (XLM model)
- contains `ctrl`: CTRLModel (Salesforce CTRL model)
The model is set in evaluation mode by default using `model.eval()` (Dropout modules are deactivated) The model is set in evaluation mode by default using `model.eval()` (Dropout modules are deactivated)
To train the model, you should first set it back in training mode with `model.train()` To train the model, you should first set it back in training mode with `model.train()`
@@ -144,6 +148,8 @@ class AutoModel(object):
""" """
if 'distilbert' in pretrained_model_name_or_path: if 'distilbert' in pretrained_model_name_or_path:
return DistilBertModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return DistilBertModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'albert' in pretrained_model_name_or_path:
return AlbertModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'camembert' in pretrained_model_name_or_path: elif 'camembert' in pretrained_model_name_or_path:
return CamembertModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return CamembertModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'roberta' in pretrained_model_name_or_path: elif 'roberta' in pretrained_model_name_or_path:
@@ -164,7 +170,7 @@ class AutoModel(object):
return CTRLModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return CTRLModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
raise ValueError("Unrecognized model identifier in {}. Should contains one of " raise ValueError("Unrecognized model identifier in {}. Should contains one of "
"'bert', 'openai-gpt', 'gpt2', 'transfo-xl', 'xlnet', " "'bert', 'openai-gpt', 'gpt2', 'transfo-xl', 'xlnet', "
"'xlm', 'roberta, 'ctrl'".format(pretrained_model_name_or_path)) "'xlm', 'roberta, 'ctrl', 'distilbert', 'camembert', 'albert'".format(pretrained_model_name_or_path))
class AutoModelWithLMHead(object): class AutoModelWithLMHead(object):
@@ -180,15 +186,16 @@ class AutoModelWithLMHead(object):
The model class to instantiate is selected as the first pattern matching The model class to instantiate is selected as the first pattern matching
in the `pretrained_model_name_or_path` string (in the following order): in the `pretrained_model_name_or_path` string (in the following order):
- contains `distilbert`: DistilBertForMaskedLM (DistilBERT model) - contains `distilbert`: DistilBertForMaskedLM (DistilBERT model)
- contains `albert`: AlbertForMaskedLM (ALBERT model)
- contains `camembert`: CamembertForMaskedLM (CamemBERT model) - contains `camembert`: CamembertForMaskedLM (CamemBERT model)
- contains `roberta`: RobertaForMaskedLM (RoBERTa model) - contains `roberta`: RobertaForMaskedLM (RoBERTa model)
- contains `bert`: BertForMaskedLM (Bert model) - contains `bert`: BertForMaskedLM (Bert model)
- contains `openai-gpt`: OpenAIGPTLMHeadModel (OpenAI GPT model) - contains `openai-gpt`: OpenAIGPTLMHeadModel (OpenAI GPT model)
- contains `gpt2`: GPT2LMHeadModel (OpenAI GPT-2 model) - contains `gpt2`: GPT2LMHeadModel (OpenAI GPT-2 model)
- contains `ctrl`: CTRLLMModel (Salesforce CTRL model)
- contains `transfo-xl`: TransfoXLLMHeadModel (Transformer-XL model) - contains `transfo-xl`: TransfoXLLMHeadModel (Transformer-XL model)
- contains `xlnet`: XLNetLMHeadModel (XLNet model) - contains `xlnet`: XLNetLMHeadModel (XLNet model)
- contains `xlm`: XLMWithLMHeadModel (XLM model) - contains `xlm`: XLMWithLMHeadModel (XLM model)
- contains `ctrl`: CTRLLMHeadModel (Salesforce CTRL model)
This class cannot be instantiated using `__init__()` (throws an error). This class cannot be instantiated using `__init__()` (throws an error).
""" """
@@ -207,6 +214,7 @@ class AutoModelWithLMHead(object):
The model class to instantiate is selected as the first pattern matching The model class to instantiate is selected as the first pattern matching
in the `pretrained_model_name_or_path` string (in the following order): in the `pretrained_model_name_or_path` string (in the following order):
- contains `distilbert`: DistilBertForMaskedLM (DistilBERT model) - contains `distilbert`: DistilBertForMaskedLM (DistilBERT model)
- contains `albert`: AlbertForMaskedLM (ALBERT model)
- contains `camembert`: CamembertForMaskedLM (CamemBERT model) - contains `camembert`: CamembertForMaskedLM (CamemBERT model)
- contains `roberta`: RobertaForMaskedLM (RoBERTa model) - contains `roberta`: RobertaForMaskedLM (RoBERTa model)
- contains `bert`: BertForMaskedLM (Bert model) - contains `bert`: BertForMaskedLM (Bert model)
@@ -215,6 +223,7 @@ class AutoModelWithLMHead(object):
- contains `transfo-xl`: TransfoXLLMHeadModel (Transformer-XL model) - contains `transfo-xl`: TransfoXLLMHeadModel (Transformer-XL model)
- contains `xlnet`: XLNetLMHeadModel (XLNet model) - contains `xlnet`: XLNetLMHeadModel (XLNet model)
- contains `xlm`: XLMWithLMHeadModel (XLM model) - contains `xlm`: XLMWithLMHeadModel (XLM model)
- contains `ctrl`: CTRLLMHeadModel (Salesforce CTRL model)
The model is set in evaluation mode by default using `model.eval()` (Dropout modules are deactivated) The model is set in evaluation mode by default using `model.eval()` (Dropout modules are deactivated)
To train the model, you should first set it back in training mode with `model.train()` To train the model, you should first set it back in training mode with `model.train()`
@@ -276,6 +285,8 @@ class AutoModelWithLMHead(object):
""" """
if 'distilbert' in pretrained_model_name_or_path: if 'distilbert' in pretrained_model_name_or_path:
return DistilBertForMaskedLM.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return DistilBertForMaskedLM.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'albert' in pretrained_model_name_or_path:
return AlbertForMaskedLM.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'camembert' in pretrained_model_name_or_path: elif 'camembert' in pretrained_model_name_or_path:
return CamembertForMaskedLM.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return CamembertForMaskedLM.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'roberta' in pretrained_model_name_or_path: elif 'roberta' in pretrained_model_name_or_path:
@@ -296,7 +307,7 @@ class AutoModelWithLMHead(object):
return CTRLLMHeadModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return CTRLLMHeadModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
raise ValueError("Unrecognized model identifier in {}. Should contains one of " raise ValueError("Unrecognized model identifier in {}. Should contains one of "
"'bert', 'openai-gpt', 'gpt2', 'transfo-xl', 'xlnet', " "'bert', 'openai-gpt', 'gpt2', 'transfo-xl', 'xlnet', "
"'xlm', 'roberta','ctrl'".format(pretrained_model_name_or_path)) "'xlm', 'roberta','ctrl', 'distilbert', 'camembert', 'albert'".format(pretrained_model_name_or_path))
class AutoModelForSequenceClassification(object): class AutoModelForSequenceClassification(object):
@@ -312,6 +323,7 @@ class AutoModelForSequenceClassification(object):
The model class to instantiate is selected as the first pattern matching The model class to instantiate is selected as the first pattern matching
in the `pretrained_model_name_or_path` string (in the following order): in the `pretrained_model_name_or_path` string (in the following order):
- contains `distilbert`: DistilBertForSequenceClassification (DistilBERT model) - contains `distilbert`: DistilBertForSequenceClassification (DistilBERT model)
- contains `albert`: AlbertForSequenceClassification (ALBERT model)
- contains `camembert`: CamembertForSequenceClassification (CamemBERT model) - contains `camembert`: CamembertForSequenceClassification (CamemBERT model)
- contains `roberta`: RobertaForSequenceClassification (RoBERTa model) - contains `roberta`: RobertaForSequenceClassification (RoBERTa model)
- contains `bert`: BertForSequenceClassification (Bert model) - contains `bert`: BertForSequenceClassification (Bert model)
@@ -335,6 +347,7 @@ class AutoModelForSequenceClassification(object):
The model class to instantiate is selected as the first pattern matching The model class to instantiate is selected as the first pattern matching
in the `pretrained_model_name_or_path` string (in the following order): in the `pretrained_model_name_or_path` string (in the following order):
- contains `distilbert`: DistilBertForSequenceClassification (DistilBERT model) - contains `distilbert`: DistilBertForSequenceClassification (DistilBERT model)
- contains `albert`: AlbertForSequenceClassification (ALBERT model)
- contains `camembert`: CamembertForSequenceClassification (CamemBERT model) - contains `camembert`: CamembertForSequenceClassification (CamemBERT model)
- contains `roberta`: RobertaForSequenceClassification (RoBERTa model) - contains `roberta`: RobertaForSequenceClassification (RoBERTa model)
- contains `bert`: BertForSequenceClassification (Bert model) - contains `bert`: BertForSequenceClassification (Bert model)
@@ -402,6 +415,8 @@ class AutoModelForSequenceClassification(object):
""" """
if 'distilbert' in pretrained_model_name_or_path: if 'distilbert' in pretrained_model_name_or_path:
return DistilBertForSequenceClassification.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return DistilBertForSequenceClassification.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'albert' in pretrained_model_name_or_path:
return AlbertForSequenceClassification.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'camembert' in pretrained_model_name_or_path: elif 'camembert' in pretrained_model_name_or_path:
return CamembertForSequenceClassification.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return CamembertForSequenceClassification.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'roberta' in pretrained_model_name_or_path: elif 'roberta' in pretrained_model_name_or_path:
@@ -414,7 +429,7 @@ class AutoModelForSequenceClassification(object):
return XLMForSequenceClassification.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return XLMForSequenceClassification.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
raise ValueError("Unrecognized model identifier in {}. Should contains one of " raise ValueError("Unrecognized model identifier in {}. Should contains one of "
"'bert', 'xlnet', 'xlm', 'roberta'".format(pretrained_model_name_or_path)) "'bert', 'xlnet', 'xlm', 'roberta', 'distilbert', 'camembert', 'albert'".format(pretrained_model_name_or_path))
class AutoModelForQuestionAnswering(object): class AutoModelForQuestionAnswering(object):
@@ -430,6 +445,7 @@ class AutoModelForQuestionAnswering(object):
The model class to instantiate is selected as the first pattern matching The model class to instantiate is selected as the first pattern matching
in the `pretrained_model_name_or_path` string (in the following order): in the `pretrained_model_name_or_path` string (in the following order):
- contains `distilbert`: DistilBertForQuestionAnswering (DistilBERT model) - contains `distilbert`: DistilBertForQuestionAnswering (DistilBERT model)
- contains `albert`: AlbertForQuestionAnswering (ALBERT model)
- contains `bert`: BertForQuestionAnswering (Bert model) - contains `bert`: BertForQuestionAnswering (Bert model)
- contains `xlnet`: XLNetForQuestionAnswering (XLNet model) - contains `xlnet`: XLNetForQuestionAnswering (XLNet model)
- contains `xlm`: XLMForQuestionAnswering (XLM model) - contains `xlm`: XLMForQuestionAnswering (XLM model)
@@ -451,6 +467,7 @@ class AutoModelForQuestionAnswering(object):
The model class to instantiate is selected as the first pattern matching The model class to instantiate is selected as the first pattern matching
in the `pretrained_model_name_or_path` string (in the following order): in the `pretrained_model_name_or_path` string (in the following order):
- contains `distilbert`: DistilBertForQuestionAnswering (DistilBERT model) - contains `distilbert`: DistilBertForQuestionAnswering (DistilBERT model)
- contains `albert`: AlbertForQuestionAnswering (ALBERT model)
- contains `bert`: BertForQuestionAnswering (Bert model) - contains `bert`: BertForQuestionAnswering (Bert model)
- contains `xlnet`: XLNetForQuestionAnswering (XLNet model) - contains `xlnet`: XLNetForQuestionAnswering (XLNet model)
- contains `xlm`: XLMForQuestionAnswering (XLM model) - contains `xlm`: XLMForQuestionAnswering (XLM model)
@@ -513,6 +530,8 @@ class AutoModelForQuestionAnswering(object):
""" """
if 'distilbert' in pretrained_model_name_or_path: if 'distilbert' in pretrained_model_name_or_path:
return DistilBertForQuestionAnswering.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return DistilBertForQuestionAnswering.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'albert' in pretrained_model_name_or_path:
return AlbertForQuestionAnswering.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'bert' in pretrained_model_name_or_path: elif 'bert' in pretrained_model_name_or_path:
return BertForQuestionAnswering.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return BertForQuestionAnswering.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'xlnet' in pretrained_model_name_or_path: elif 'xlnet' in pretrained_model_name_or_path:
@@ -521,4 +540,4 @@ class AutoModelForQuestionAnswering(object):
return XLMForQuestionAnswering.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return XLMForQuestionAnswering.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
raise ValueError("Unrecognized model identifier in {}. Should contains one of " raise ValueError("Unrecognized model identifier in {}. Should contains one of "
"'bert', 'xlnet', 'xlm'".format(pretrained_model_name_or_path)) "'bert', 'xlnet', 'xlm', 'distilbert', 'albert'".format(pretrained_model_name_or_path))

15
transformers/tokenization_auto.py
View File

@@ -28,6 +28,7 @@ from .tokenization_xlm import XLMTokenizer
from .tokenization_roberta import RobertaTokenizer from .tokenization_roberta import RobertaTokenizer
from .tokenization_distilbert import DistilBertTokenizer from .tokenization_distilbert import DistilBertTokenizer
from .tokenization_camembert import CamembertTokenizer from .tokenization_camembert import CamembertTokenizer
from .tokenization_albert import AlbertTokenizer
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@@ -42,16 +43,17 @@ class AutoTokenizer(object):
The tokenizer class to instantiate is selected as the first pattern matching The tokenizer class to instantiate is selected as the first pattern matching
in the `pretrained_model_name_or_path` string (in the following order): in the `pretrained_model_name_or_path` string (in the following order):
- contains `camembert`: CamembertTokenizer (CamemBERT model)
- contains `distilbert`: DistilBertTokenizer (DistilBert model) - contains `distilbert`: DistilBertTokenizer (DistilBert model)
- contains `albert`: AlbertTokenizer (ALBERT model)
- contains `camembert`: CamembertTokenizer (CamemBERT model)
- contains `roberta`: RobertaTokenizer (RoBERTa model) - contains `roberta`: RobertaTokenizer (RoBERTa model)
- contains `bert`: BertTokenizer (Bert model) - contains `bert`: BertTokenizer (Bert model)
- contains `openai-gpt`: OpenAIGPTTokenizer (OpenAI GPT model) - contains `openai-gpt`: OpenAIGPTTokenizer (OpenAI GPT model)
- contains `gpt2`: GPT2Tokenizer (OpenAI GPT-2 model) - contains `gpt2`: GPT2Tokenizer (OpenAI GPT-2 model)
- contains `ctrl`: CTRLTokenizer (Salesforce CTRL model)
- contains `transfo-xl`: TransfoXLTokenizer (Transformer-XL model) - contains `transfo-xl`: TransfoXLTokenizer (Transformer-XL model)
- contains `xlnet`: XLNetTokenizer (XLNet model) - contains `xlnet`: XLNetTokenizer (XLNet model)
- contains `xlm`: XLMTokenizer (XLM model) - contains `xlm`: XLMTokenizer (XLM model)
- contains `ctrl`: CTRLTokenizer (Salesforce CTRL model)
This class cannot be instantiated using `__init__()` (throw an error). This class cannot be instantiated using `__init__()` (throw an error).
""" """
@@ -66,16 +68,17 @@ class AutoTokenizer(object):
The tokenizer class to instantiate is selected as the first pattern matching The tokenizer class to instantiate is selected as the first pattern matching
in the `pretrained_model_name_or_path` string (in the following order): in the `pretrained_model_name_or_path` string (in the following order):
- contains `camembert`: CamembertTokenizer (CamemBERT model)
- contains `distilbert`: DistilBertTokenizer (DistilBert model) - contains `distilbert`: DistilBertTokenizer (DistilBert model)
- contains `albert`: AlbertTokenizer (ALBERT model)
- contains `camembert`: CamembertTokenizer (CamemBERT model)
- contains `roberta`: RobertaTokenizer (RoBERTa model) - contains `roberta`: RobertaTokenizer (RoBERTa model)
- contains `bert`: BertTokenizer (Bert model) - contains `bert`: BertTokenizer (Bert model)
- contains `openai-gpt`: OpenAIGPTTokenizer (OpenAI GPT model) - contains `openai-gpt`: OpenAIGPTTokenizer (OpenAI GPT model)
- contains `gpt2`: GPT2Tokenizer (OpenAI GPT-2 model) - contains `gpt2`: GPT2Tokenizer (OpenAI GPT-2 model)
- contains `ctrl`: CTRLTokenizer (Salesforce CTRL model)
- contains `transfo-xl`: TransfoXLTokenizer (Transformer-XL model) - contains `transfo-xl`: TransfoXLTokenizer (Transformer-XL model)
- contains `xlnet`: XLNetTokenizer (XLNet model) - contains `xlnet`: XLNetTokenizer (XLNet model)
- contains `xlm`: XLMTokenizer (XLM model) - contains `xlm`: XLMTokenizer (XLM model)
- contains `ctrl`: CTRLTokenizer (Salesforce CTRL model)
Params: Params:
pretrained_model_name_or_path: either: pretrained_model_name_or_path: either:
@@ -109,6 +112,8 @@ class AutoTokenizer(object):
""" """
if 'distilbert' in pretrained_model_name_or_path: if 'distilbert' in pretrained_model_name_or_path:
return DistilBertTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs) return DistilBertTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
elif 'albert' in pretrained_model_name_or_path:
return AlbertTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
elif 'camembert' in pretrained_model_name_or_path: elif 'camembert' in pretrained_model_name_or_path:
return CamembertTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs) return CamembertTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
elif 'roberta' in pretrained_model_name_or_path: elif 'roberta' in pretrained_model_name_or_path:
@@ -129,4 +134,4 @@ class AutoTokenizer(object):
return CTRLTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs) return CTRLTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
raise ValueError("Unrecognized model identifier in {}. Should contains one of " raise ValueError("Unrecognized model identifier in {}. Should contains one of "
"'bert', 'openai-gpt', 'gpt2', 'transfo-xl', 'xlnet', " "'bert', 'openai-gpt', 'gpt2', 'transfo-xl', 'xlnet', "
"'xlm', 'roberta', 'camembert', 'ctrl'".format(pretrained_model_name_or_path)) "'xlm', 'roberta', 'distilbert,' 'camembert', 'ctrl', 'albert'".format(pretrained_model_name_or_path))