





'''simple docstring'''




import os
from typing import Dict, List, Union

import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs

from .tokenization_gpta import GPTaTokenizer







class   A_	(  tf.keras.layers.Layer			):




 def __init__(					self       :    Tuple	,			snake_case_       :    Dict[str, int]	,			snake_case_       :    List[str]	,			snake_case_       :    int = None	,			snake_case_       :    int = None    ):
      super().__init__()
      _UpperCAmelCase     							=   pad_token_id
      _UpperCAmelCase     							=   max_length
      _UpperCAmelCase     							=   vocab
      _UpperCAmelCase     							=   merges
      _UpperCAmelCase     							=   BytePairTokenizer(snake_case_	,			snake_case_	,			sequence_length=snake_case_    )




 @classmethod
 def      lowercase	(					cls       :    Optional[int]	,			snake_case_       :    GPTaTokenizer	,			*snake_case_       :    List[Any]	,			**snake_case_       :    Any    ):
      _UpperCAmelCase     							=   [" ".join(snake_case_    ) for m in tokenizer.bpe_ranks.keys()]
      _UpperCAmelCase     							=   tokenizer.get_vocab()
      return cls(snake_case_	,			snake_case_	,			*snake_case_	,			**snake_case_    )




 @classmethod
 def      lowercase	(					cls       :    Optional[int]	,			snake_case_       :    Union[str, os.PathLike]	,			*snake_case_       :    Union[str, Any]	,			**snake_case_       :    List[Any]    ):
      _UpperCAmelCase     							=   GPTaTokenizer.from_pretrained(snake_case_	,			*snake_case_	,			**snake_case_    )
      return cls.from_tokenizer(snake_case_	,			*snake_case_	,			**snake_case_    )




 @classmethod
 def      lowercase	(					cls       :    int	,			snake_case_       :    List[Any]    ):
      return cls(**snake_case_    )




 def      lowercase	(					self       :    str    ):
      return {
          "vocab": self.vocab,
          "merges": self.merges,
          "max_length": self.max_length,
          "pad_token_id": self.pad_token_id,
      }




 def      lowercase	(					self       :    List[str]	,			snake_case_       :    Union[str, Any]	,			snake_case_       :    int = None    ):
      _UpperCAmelCase     							=   self.tf_tokenizer(snake_case_    )
      _UpperCAmelCase     							=   tf.ones_like(snake_case_    )

      if self.pad_token_id is not None:
           # pad the tokens up to max length
           _UpperCAmelCase     							=   max_length if max_length is not None else self.max_length

           if max_length is not None:
                _UpperCAmelCase							,  _UpperCAmelCase     							=   pad_model_inputs(
                    snake_case_	,			max_seq_length=snake_case_	,			pad_value=self.pad_token_id    )

      return {"attention_mask": attention_mask, "input_ids": input_ids}











'''simple docstring'''




import string
from math import logaa
def 	UpperCAmelCase_							(					__lowercase							:      str			,     __lowercase							:      str       )		->       int:


     '''simple docstring'''



     _UpperCAmelCase     							=   document.translate(
         str.maketrans(""			,     ""			,     string.punctuation       )       ).replace("\n"			,     ""       )
     _UpperCAmelCase     							=   document_without_punctuation.split(" "       )  # word tokenization
     return len([word for word in tokenize_document if word.lower() == term.lower()]       )
def 	UpperCAmelCase_							(					__lowercase							:      str			,     __lowercase							:      str       )		->       tuple[int, int]:


     '''simple docstring'''



     _UpperCAmelCase     							=   corpus.lower().translate(
         str.maketrans(""			,     ""			,     string.punctuation       )       )  # strip all punctuation and replace it with ''
     _UpperCAmelCase     							=   corpus_without_punctuation.split("\n"       )
     _UpperCAmelCase     							=   term.lower()
     return (len([doc for doc in docs if term in doc]       ), len(__lowercase       ))
def 	UpperCAmelCase_							(					__lowercase							:      int			,     __lowercase							:      int			,     __lowercase							:      Union[str, Any]=False       )		->       float:


     '''simple docstring'''



     if smoothing:
          if n == 0:
               raise ValueError("log10(0) is undefined."       )
          return round(1 + logaa(n / (1 + df)       )			,     3       )

     if df == 0:
          raise ZeroDivisionError("df must be > 0"       )
     elif n == 0:
          raise ValueError("log10(0) is undefined."       )
     return round(logaa(n / df       )			,     3       )






def 	UpperCAmelCase_							(					__lowercase							:      int			,     __lowercase							:      int       )		->       float:


     '''simple docstring'''



     return round(tf * idf			,     3       )




