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Added RoBERTa to AutoModel/AutoConfig

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This commit is contained in:
LysandreJik 2019-08-15 14:02:11 -04:00
parent fe02e45e48
commit e24e19ce3b
1 changed files with 21 additions and 12 deletions
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33
pytorch_transformers/modeling_auto.py
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@ -29,6 +29,7 @@ from .modeling_gpt2 import GPT2Config, GPT2Model
from .modeling_transfo_xl import TransfoXLConfig, TransfoXLModel from .modeling_transfo_xl import TransfoXLConfig, TransfoXLModel
from .modeling_xlnet import XLNetConfig, XLNetModel from .modeling_xlnet import XLNetConfig, XLNetModel
from .modeling_xlm import XLMConfig, XLMModel from .modeling_xlm import XLMConfig, XLMModel
from .modeling_roberta import RobertaConfig, RobertaModel
from .modeling_utils import PreTrainedModel, SequenceSummary from .modeling_utils import PreTrainedModel, SequenceSummary
@ -51,6 +52,7 @@ class AutoConfig(object):
- 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)
This class cannot be instantiated using `__init__()` (throw an error). This class cannot be instantiated using `__init__()` (throw an error).
""" """
@ -71,6 +73,7 @@ class AutoConfig(object):
- 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)
Params: Params:
**pretrained_model_name_or_path**: either: **pretrained_model_name_or_path**: either:
@ -119,6 +122,8 @@ class AutoConfig(object):
return XLNetConfig.from_pretrained(pretrained_model_name_or_path, **kwargs) return XLNetConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
elif 'xlm' in pretrained_model_name_or_path: elif 'xlm' in pretrained_model_name_or_path:
return XLMConfig.from_pretrained(pretrained_model_name_or_path, **kwargs) return XLMConfig.from_pretrained(pretrained_model_name_or_path, **kwargs)
elif 'roberta' in pretrained_model_name_or_path:
return RobertaConfig.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', "
@ -137,12 +142,13 @@ 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 `bert`: BertConfig (Bert model) - contains `bert`: BertModel (Bert model)
- contains `openai-gpt`: OpenAIGPTConfig (OpenAI GPT model) - contains `openai-gpt`: OpenAIGPTModel (OpenAI GPT model)
- contains `gpt2`: GPT2Config (OpenAI GPT-2 model) - contains `gpt2`: GPT2Model (OpenAI GPT-2 model)
- contains `transfo-xl`: TransfoXLConfig (Transformer-XL model) - contains `transfo-xl`: TransfoXLModel (Transformer-XL model)
- contains `xlnet`: XLNetConfig (XLNet model) - contains `xlnet`: XLNetModel (XLNet model)
- contains `xlm`: XLMConfig (XLM model) - contains `xlm`: XLMModel (XLM model)
- contains `roberta`: RobertaModel (RoBERTa model)
This class cannot be instantiated using `__init__()` (throw an error). This class cannot be instantiated using `__init__()` (throw an error).
""" """
@ -157,12 +163,13 @@ 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 `bert`: BertConfig (Bert model) - contains `bert`: BertModel (Bert model)
- contains `openai-gpt`: OpenAIGPTConfig (OpenAI GPT model) - contains `openai-gpt`: OpenAIGPTModel (OpenAI GPT model)
- contains `gpt2`: GPT2Config (OpenAI GPT-2 model) - contains `gpt2`: GPT2Model (OpenAI GPT-2 model)
- contains `transfo-xl`: TransfoXLConfig (Transformer-XL model) - contains `transfo-xl`: TransfoXLModel (Transformer-XL model)
- contains `xlnet`: XLNetConfig (XLNet model) - contains `xlnet`: XLNetModel (XLNet model)
- contains `xlm`: XLMConfig (XLM model) - contains `xlm`: XLMModel (XLM model)
- contains `roberta`: RobertaModel (RoBERTa 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()`
@ -230,6 +237,8 @@ class AutoModel(object):
return XLNetModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return XLNetModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'xlm' in pretrained_model_name_or_path: elif 'xlm' in pretrained_model_name_or_path:
return XLMModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs) return XLMModel.from_pretrained(pretrained_model_name_or_path, *model_args, **kwargs)
elif 'roberta' in pretrained_model_name_or_path:
return RobertaModel.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', "