/
registry.py
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/
registry.py
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import logging
from typing import Dict, Text, Type
# Explicitly set logging level for this module before any import
# because otherwise it logs tensorflow/pytorch versions
logging.getLogger("transformers.file_utils").setLevel(logging.WARNING)
from transformers import ( # noqa: E402
TFPreTrainedModel,
TFBertModel,
TFOpenAIGPTModel,
TFGPT2Model,
TFXLNetModel,
# TFXLMModel,
TFDistilBertModel,
TFRobertaModel,
TFCamembertModel,
PreTrainedTokenizer,
BertTokenizer,
OpenAIGPTTokenizer,
GPT2Tokenizer,
XLNetTokenizer,
# XLMTokenizer,
DistilBertTokenizer,
RobertaTokenizer,
CamembertTokenizer,
)
from rasa.nlu.utils.hugging_face.transformers_pre_post_processors import ( # noqa: E402, E501
bert_tokens_pre_processor,
gpt_tokens_pre_processor,
xlnet_tokens_pre_processor,
roberta_tokens_pre_processor,
bert_embeddings_post_processor,
gpt_embeddings_post_processor,
xlnet_embeddings_post_processor,
roberta_embeddings_post_processor,
bert_tokens_cleaner,
openaigpt_tokens_cleaner,
gpt2_tokens_cleaner,
xlnet_tokens_cleaner,
camembert_tokens_pre_processor,
)
model_class_dict: Dict[Text, Type[TFPreTrainedModel]] = {
"bert": TFBertModel,
"gpt": TFOpenAIGPTModel,
"gpt2": TFGPT2Model,
"xlnet": TFXLNetModel,
# "xlm": TFXLMModel, # Currently doesn't work because of a bug in transformers
# library https://github.com/huggingface/transformers/issues/2729
"distilbert": TFDistilBertModel,
"roberta": TFRobertaModel,
"camembert": TFCamembertModel,
}
model_tokenizer_dict: Dict[Text, Type[PreTrainedTokenizer]] = {
"bert": BertTokenizer,
"gpt": OpenAIGPTTokenizer,
"gpt2": GPT2Tokenizer,
"xlnet": XLNetTokenizer,
# "xlm": XLMTokenizer,
"distilbert": DistilBertTokenizer,
"roberta": RobertaTokenizer,
"camembert": CamembertTokenizer,
}
model_weights_defaults = {
"bert": "rasa/LaBSE",
"gpt": "openai-gpt",
"gpt2": "gpt2",
"xlnet": "xlnet-base-cased",
# "xlm": "xlm-mlm-enfr-1024",
"distilbert": "distilbert-base-uncased",
"roberta": "roberta-base",
"camembert": "camembert-base",
}
model_special_tokens_pre_processors = {
"bert": bert_tokens_pre_processor,
"gpt": gpt_tokens_pre_processor,
"gpt2": gpt_tokens_pre_processor,
"xlnet": xlnet_tokens_pre_processor,
# "xlm": xlm_tokens_pre_processor,
"distilbert": bert_tokens_pre_processor,
"roberta": roberta_tokens_pre_processor,
"camembert": camembert_tokens_pre_processor,
}
model_tokens_cleaners = {
"bert": bert_tokens_cleaner,
"gpt": openaigpt_tokens_cleaner,
"gpt2": gpt2_tokens_cleaner,
"xlnet": xlnet_tokens_cleaner,
# "xlm": xlm_tokens_pre_processor,
"distilbert": bert_tokens_cleaner, # uses the same as BERT
"roberta": gpt2_tokens_cleaner, # Uses the same as GPT2
"camembert": xlnet_tokens_cleaner, # Removing underscores _
}
model_embeddings_post_processors = {
"bert": bert_embeddings_post_processor,
"gpt": gpt_embeddings_post_processor,
"gpt2": gpt_embeddings_post_processor,
"xlnet": xlnet_embeddings_post_processor,
# "xlm": xlm_embeddings_post_processor,
"distilbert": bert_embeddings_post_processor,
"roberta": roberta_embeddings_post_processor,
"camembert": roberta_embeddings_post_processor,
}