Wiki103_fastai_v1-SP_Tokenizer-Example.ipynb

Any Idea why I may be having this error?

KeyError                                  Traceback (most recent call last)

<ipython-input-90-08d0dd5c9f7c> in <module>()
----> 1 data.show_batch()

4 frames

/usr/local/lib/python3.6/dist-packages/fastai/text/transform.py in <listcomp>(.0)
    132     def textify(self, nums:Collection[int], sep=' ') -> List[str]:
    133         "Convert a list of `nums` to their tokens."
--> 134         return sep.join([self.itos[i] for i in nums]) if sep is not None else [self.itos[i] for i in nums]
    135 
    136     def __getstate__(self):

KeyError: tensor(219)

I am not too sure. I have moved past this example and now have better code for the custom tokenizer. (which allows it to be saved and applies EncodeAsPieces which will return components of the sub-word rather than the ID (the numericaliztion!) See if this help at all or if you get the same errors:

class SPTokenizer(BaseTokenizer):
    "Wrapper around a SentncePiece tokenizer to make it a `BaseTokenizer`."
    def __init__(self, model_prefix:str):
        self.tok = spm.SentencePieceProcessor()
        self.tok.load(f'{model_prefix}.model')

    def tokenizer(self, t:str) -> List[str]:
        return self.tok.EncodeAsPieces(t)
    
class CustomTokenizer():
    '''Wrapper for SentencePiece toeknizer to fit into Fast.ai V1'''
    def __init__(self,tok_func:Callable,model_prefix:str, pre_rules:ListRules=None):
        self.tok_func,self.model_prefix = tok_func,model_prefix
        self.pre_rules  = ifnone(pre_rules,  defaults.text_pre_rules )
        
    def __repr__(self) -> str:
        res = f'Tokenizer {self.tok_func.__name__} using `{self.model_prefix}` model with the following rules:\n'
        for rule in self.pre_rules: res += f' - {rule.__name__}\n'
        return res        

    def process_text(self, t:str,tok:BaseTokenizer) -> List[str]:
        "Processe one text `t` with tokenizer `tok`."
        for rule in self.pre_rules: t = rule(t)  
        toks = tok.tokenizer(t)
        #post rules?
        return toks 
    
    def _process_all_1(self,texts:Collection[str]) -> List[List[str]]:
        'Process a list of `texts` in one process'
        tok = self.tok_func(self.model_prefix)
        return [self.process_text(t,tok) for t in texts]
                                                                     
    def process_all(self, texts:Collection[str]) -> List[List[str]]: 
        "Process a list of `texts`."                                 
        return self._process_all_1(texts)

i believe this is how i should use it:
mycust_tok = CustomTokenizer(SPTokenizer,model_prefix)
But i still have the error. Can you help with the full modified code?

itos was wrong also. I updated the example above.

Thank you so much. Sorry I didnt notice the change earlier. It works. Much appreciated.

No problem. I am glad I cleaned it up for my own good!