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Construct a Perceiver tokenizer. The Perceiver simply uses raw bytes utf-8 encoding.
This tokenizer inherits from [`PreTrainedTokenizer`] which contains most of the main methods. Users should refer to
this superclass for more information regarding those methods.
Args:
pad_token (`str`, *optional*, defaults to `"[PAD]"`):
The token used for padding, for example when batching sequences of different lengths.
bos_token (`str`, *optional*, defaults to `"[BOS]"`):
The BOS token (reserved in the vocab, but not actually used).
eos_token (`str`, *optional*, defaults to `"[EOS]"`):
The end of sequence token (reserved in the vocab, but not actually used).
When building a sequence using special tokens, this is not the token that is used for the end of sequence.
The token used is the `sep_token`.
mask_token (`str`, *optional*, defaults to `"[MASK]"`):
The MASK token, useful for masked language modeling.
cls_token (`str`, *optional*, defaults to `"[CLS]"`):
The CLS token (reserved in the vocab, but not actually used).
sep_token (`str`, *optional*, defaults to `"[SEP]"`):
The separator token, which is used when building a sequence from two sequences.
input_idsattention_mask[PAD][BOS][EOS][MASK][CLS][SEP] returnNc t |t rt |dd n|}t |t rt |dd n|}t |t rt |dd n|}t |t rt |dd n|}t |t rt |dd n|}t |t rt |dd n|}d| _ ||||||d| _ t | j | _ t j d|||||||d| d S )NF)lstriprstrip )r r ) pad_token bos_token eos_token
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Retrieve sequence ids from a token list that has no special tokens added. This method is called when adding
special tokens using the tokenizer `prepare_for_model` method.
Args:
token_ids_0 (`list[int]`):
List of IDs.
token_ids_1 (`list[int]`, *optional*):
Optional second list of IDs for sequence pairs.
already_has_special_tokens (`bool`, *optional*, defaults to `False`):
Whether or not the token list is already formatted with special tokens for the model.
Returns:
`list[int]`: A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token.
T)r= r> r? Nr r )r* get_special_tokens_maskr( )r, r= r> r? r. s r/ rA z*PerceiverTokenizer.get_special_tokens_maskp s $ & 7722 '[]a 3
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Build model inputs from a sequence or a pair of sequence for sequence classification tasks. A sequence has the
following format:
- single sequence: `[CLS] X [SEP]`
- pair of sequences: `[CLS] A [SEP] B [SEP]`
Args:
token_ids_0 (`list[int]`):
List of IDs to which the special tokens will be added.
token_ids_1 (`list[int]`, *optional*):
Optional second list of IDs for sequence pairs.
Returns:
`list[int]`: List of [input IDs](../glossary#input-ids) with the appropriate special tokens.
) cls_token_id sep_token_id)r, r= r> s r/ build_inputs_with_special_tokensz3PerceiverTokenizer.build_inputs_with_special_tokens sS & %&48I7JJ J%&48I7JJ[X\`\m[nn nr0 textc D d | d D }|S )zPTake as input a string and return a list of strings (tokens) for words/sub-wordsc , g | ]}t | S r# )r4 ).0r8 s r/
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r0 c j t | dk r| j }nt | | j z }|S )z0Converts a token (str) in an id using the vocab.r )r( unk_token_idordr) )r, r9 token_ids r/ _convert_token_to_idz'PerceiverTokenizer._convert_token_to_id s3 u::??(HH5zzD$< $ $ X$ sxU U 9U3;DI3FUkoU
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