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rasa.nlu.utils.hugging_face.transformers_pre_post_processors

cleanup_tokens

cleanup_tokens(token_ids_string: List[Tuple[int, Text]], delimiter: Text) -> Tuple[List[int], List[Text]]

Utility method to apply delimiter based cleanup on list of tokens.

Arguments:

  • token_ids_string - List of tuples with each tuple containing (token id, token string).
  • delimiter - character/string to be cleaned from token strings.

Returns:

Token ids and Token strings unpacked.

bert_tokens_pre_processor

bert_tokens_pre_processor(token_ids: List[int]) -> List[int]

Add BERT style special tokens(CLS and SEP).

Arguments:

  • token_ids - List of token ids without any special tokens.

Returns:

List of token ids augmented with special tokens.

gpt_tokens_pre_processor

gpt_tokens_pre_processor(token_ids: List[int]) -> List[int]

Add GPT style special tokens(None).

Arguments:

  • token_ids - List of token ids without any special tokens.

Returns:

List of token ids augmented with special tokens.

xlnet_tokens_pre_processor

xlnet_tokens_pre_processor(token_ids: List[int]) -> List[int]

Add XLNET style special tokens.

Arguments:

  • token_ids - List of token ids without any special tokens.

Returns:

List of token ids augmented with special tokens.

roberta_tokens_pre_processor

roberta_tokens_pre_processor(token_ids: List[int]) -> List[int]

Add RoBERTa style special tokens.

Arguments:

  • token_ids - List of token ids without any special tokens.

Returns:

List of token ids augmented with special tokens.

xlm_tokens_pre_processor

xlm_tokens_pre_processor(token_ids: List[int]) -> List[int]

Add XLM style special tokens.

Arguments:

  • token_ids - List of token ids without any special tokens.

Returns:

List of token ids augmented with special tokens.

bert_embeddings_post_processor

bert_embeddings_post_processor(sequence_embeddings: np.ndarray) -> Tuple[np.ndarray, np.ndarray]

Post-process embeddings from BERT.

by removing CLS and SEP embeddings and returning CLS token embedding as sentence representation.

Arguments:

  • sequence_embeddings - Sequence of token level embeddings received as output from BERT.

Returns:

sentence level embedding and post-processed sequence level embedding.

gpt_embeddings_post_processor

gpt_embeddings_post_processor(sequence_embeddings: np.ndarray) -> Tuple[np.ndarray, np.ndarray]

Post-process embeddings from GPT models.

by taking a mean over sequence embeddings and returning that as sentence representation.

Arguments:

  • sequence_embeddings - Sequence of token level embeddings received as output from GPT.

Returns:

sentence level embedding and post-processed sequence level embedding.

xlnet_embeddings_post_processor

xlnet_embeddings_post_processor(sequence_embeddings: np.ndarray) -> Tuple[np.ndarray, np.ndarray]

Post-process embeddings from XLNet models.

by taking a mean over sequence embeddings and returning that as sentence representation. Remove last two time steps corresponding to special tokens from the sequence embeddings.

Arguments:

  • sequence_embeddings - Sequence of token level embeddings received as output from XLNet.

Returns:

sentence level embedding and post-processed sequence level embedding.

roberta_embeddings_post_processor

roberta_embeddings_post_processor(sequence_embeddings: np.ndarray) -> Tuple[np.ndarray, np.ndarray]

Post process embeddings from Roberta models.

by taking a mean over sequence embeddings and returning that as sentence representation. Remove first and last time steps corresponding to special tokens from the sequence embeddings.

Arguments:

  • sequence_embeddings - Sequence of token level embeddings received as output from Roberta

Returns:

sentence level embedding and post-processed sequence level embedding

xlm_embeddings_post_processor

xlm_embeddings_post_processor(sequence_embeddings: np.ndarray) -> Tuple[np.ndarray, np.ndarray]

Post process embeddings from XLM models

by taking a mean over sequence embeddings and returning that as sentence representation. Remove first and last time steps corresponding to special tokens from the sequence embeddings.

Arguments:

  • sequence_embeddings - Sequence of token level embeddings received as output from XLM

Returns:

sentence level embedding and post-processed sequence level embedding

bert_tokens_cleaner

bert_tokens_cleaner(token_ids: List[int], token_strings: List[Text]) -> Tuple[List[int], List[Text]]

Token cleanup method for BERT.

Clean up tokens with the extra delimiters(##) BERT adds while breaking a token into sub-tokens.

Arguments:

  • token_ids - List of token ids received as output from BERT Tokenizer.
  • token_strings - List of token strings received as output from BERT Tokenizer.

Returns:

Cleaned token ids and token strings.

openaigpt_tokens_cleaner

openaigpt_tokens_cleaner(token_ids: List[int], token_strings: List[Text]) -> Tuple[List[int], List[Text]]

Token cleanup method for GPT.

Clean up tokens with the extra delimiters(</w>) OpenAIGPT adds while breaking a token into sub-tokens.

Arguments:

  • token_ids - List of token ids received as output from GPT Tokenizer.
  • token_strings - List of token strings received as output from GPT Tokenizer.

Returns:

Cleaned token ids and token strings.

gpt2_tokens_cleaner

gpt2_tokens_cleaner(token_ids: List[int], token_strings: List[Text]) -> Tuple[List[int], List[Text]]

Token cleanup method for GPT2.

Clean up tokens with the extra delimiters(Ġ) GPT2 adds while breaking a token into sub-tokens.

Arguments:

  • token_ids - List of token ids received as output from GPT Tokenizer.
  • token_strings - List of token strings received as output from GPT Tokenizer.

Returns:

Cleaned token ids and token strings.

xlnet_tokens_cleaner

xlnet_tokens_cleaner(token_ids: List[int], token_strings: List[Text]) -> Tuple[List[int], List[Text]]

Token cleanup method for XLNet.

Clean up tokens with the extra delimiters(▁) XLNet adds while breaking a token into sub-tokens.

Arguments:

  • token_ids - List of token ids received as output from GPT Tokenizer.
  • token_strings - List of token strings received as output from GPT Tokenizer.

Returns:

Cleaned token ids and token strings.