




import copy
import re





class   __a      :
 __lowercase			:							Optional[Any]       					=			'hp'
 __lowercase			:							Tuple       					=			{}
 __lowercase			:							Optional[Any]       					=			None
 @classmethod
 def 		SCREAMING_SNAKE_CASE__       (       cls    ,			lowerCAmelCase__    ,			lowerCAmelCase__			) ->    Optional[int]:




        '''simple docstring'''
        lowercase__:       int        =       prefix
        lowercase__:       int        =       defaults
        cls.build_naming_info()
 @staticmethod
 def 		SCREAMING_SNAKE_CASE__       (       lowerCAmelCase__    ,			lowerCAmelCase__			) ->    Optional[int]:




        '''simple docstring'''
        if len(__lowerCamelCase			) == 0:
               return ""
        lowercase__:       Optional[Any]        =       None
        if any(char.isdigit() for char in word			):
               raise Exception(F'Parameters should not contain numbers: \'{word}\' contains a number'			)
        if word in info["short_word"]:
               return info["short_word"][word]
        for prefix_len in range(1    ,			len(__lowerCamelCase			) + 1			):
               lowercase__:       str        =       word[:prefix_len]
               if prefix in info["reverse_short_word"]:
                      continue
               else:
                      lowercase__:       Dict        =       prefix
                      break

        if short_word is None:
               # Paranoid fallback
               def int_to_alphabetic(lowerCAmelCase__			):
                      lowercase__:       Any        =       ''
                      while integer != 0:
                             lowercase__:       Dict        =       chr(ord('A'			) + integer % 10			) + s
                             integer //= 10
                      return s

               lowercase__:       Union[str, Any]        =       0
               while True:
                      lowercase__:       Optional[int]        =       word + '#' + int_to_alphabetic(__lowerCamelCase			)
                      if sword in info["reverse_short_word"]:
                             continue
                      else:
                             lowercase__:       Union[str, Any]        =       sword
                             break

        lowercase__:       List[Any]        =       short_word
        lowercase__:       Optional[int]        =       word
        return short_word
 @staticmethod
 def 		SCREAMING_SNAKE_CASE__       (       lowerCAmelCase__    ,			lowerCAmelCase__			) ->    List[Any]:




        '''simple docstring'''
        lowercase__:       Union[str, Any]        =       param_name.split('_'			)

        lowercase__:       Dict        =       [TrialShortNamer.shortname_for_word(__lowerCamelCase    ,			__lowerCamelCase			) for word in words]

        # We try to create a separatorless short name, but if there is a collision we have to fallback
        # to a separated short name
        lowercase__:       List[Any]        =       ['', '_']

        for separator in separators:
               lowercase__:       Union[str, Any]        =       separator.join(__lowerCamelCase			)
               if shortname not in info["reverse_short_param"]:
                      lowercase__:       List[Any]        =       shortname
                      lowercase__:       Optional[Any]        =       param_name
                      return shortname

        return param_name
 @staticmethod
 def 		SCREAMING_SNAKE_CASE__       (       lowerCAmelCase__    ,			lowerCAmelCase__			) ->    Optional[Any]:




        '''simple docstring'''
        lowercase__:       Tuple        =       TrialShortNamer.shortname_for_key(__lowerCamelCase    ,			__lowerCamelCase			)
        lowercase__:       Union[str, Any]        =       short_name
        lowercase__:       int        =       param_name
 @classmethod
 def 		SCREAMING_SNAKE_CASE__       (       cls			) ->    List[Any]:




        '''simple docstring'''
        if cls.NAMING_INFO is not None:
               return

        lowercase__:       Dict        =       {
            'short_word': {},
            'reverse_short_word': {},
            'short_param': {},
            'reverse_short_param': {},
        }

        lowercase__:       Optional[Any]        =       list(cls.DEFAULTS.keys()			)

        for k in field_keys:
               cls.add_new_param_name(__lowerCamelCase    ,			__lowerCamelCase			)

        lowercase__:       Optional[int]        =       info
 @classmethod
 def 		SCREAMING_SNAKE_CASE__       (       cls    ,			lowerCAmelCase__			) ->    Optional[int]:




        '''simple docstring'''
        cls.build_naming_info()
        assert cls.PREFIX is not None
        lowercase__:       Any        =       [copy.copy(cls.PREFIX			)]

        for k, v in params.items():
               if k not in cls.DEFAULTS:
                      raise Exception(F'You should provide a default value for the param name {k} with value {v}'			)
               if v == cls.DEFAULTS[k]:
                      # The default value is not added to the name
                      continue

               lowercase__:       List[Any]        =       cls.NAMING_INFO['short_param'][k]

               if isinstance(__lowerCamelCase    ,			__lowerCamelCase			):
                      lowercase__:       int        =       1 if v else 0

               lowercase__:       int        =       '' if isinstance(__lowerCamelCase    ,			(int, float)			) else '-'
               lowercase__:       Optional[int]        =       F'{key}{sep}{v}'
               name.append(__lowerCamelCase			)

        return "_".join(__lowerCamelCase			)
 @classmethod
 def 		SCREAMING_SNAKE_CASE__       (       cls    ,			lowerCAmelCase__			) ->    Any:




        '''simple docstring'''
        lowercase__:       str        =       repr[len(cls.PREFIX			) + 1 :]
        if repr == "":
               lowercase__:       Dict        =       []
        else:
               lowercase__:       str        =       repr.split('_'			)

        lowercase__:       str        =       {}

        for value in values:
               if "-" in value:
                      lowercase__      ,						lowercase__:       str        =       value.split('-'			)
               else:
                      lowercase__:       Optional[Any]        =       re.sub('[0-9.]'    ,			''    ,			__lowerCamelCase			)
                      lowercase__:       Any        =       float(re.sub('[^0-9.]'    ,			''    ,			__lowerCamelCase			)			)

               lowercase__:       List[Any]        =       cls.NAMING_INFO['reverse_short_param'][p_k]

               lowercase__:       int        =       p_v

        for k in cls.DEFAULTS:
               if k not in parameters:
                      lowercase__:       Tuple        =       cls.DEFAULTS[k]

        return parameters






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    ,			lowerCAmelCase__    ,			lowerCAmelCase__    ,			lowerCAmelCase__ = None    ,			lowerCAmelCase__ = None			) ->    int:




        '''simple docstring'''
        super().__init__()
        lowercase__:       Union[str, Any]        =       pad_token_id
        lowercase__:       List[str]        =       max_length
        lowercase__:       int        =       vocab
        lowercase__:       List[Any]        =       merges
        lowercase__:       str        =       BytePairTokenizer(lowerCAmelCase__    ,			lowerCAmelCase__    ,			sequence_length=lowerCAmelCase__			)
 @classmethod
 def 		SCREAMING_SNAKE_CASE__       (       cls    ,			lowerCAmelCase__    ,			*lowerCAmelCase__    ,			**lowerCAmelCase__			) ->    Any:




        '''simple docstring'''
        lowercase__:       Tuple        =       [' '.join(lowerCAmelCase__			) for m in tokenizer.bpe_ranks.keys()]
        lowercase__:       List[Any]        =       tokenizer.get_vocab()
        return cls(lowerCAmelCase__    ,			lowerCAmelCase__    ,			*lowerCAmelCase__    ,			**lowerCAmelCase__			)
 @classmethod
 def 		SCREAMING_SNAKE_CASE__       (       cls    ,			lowerCAmelCase__    ,			*lowerCAmelCase__    ,			**lowerCAmelCase__			) ->    List[Any]:




        '''simple docstring'''
        lowercase__:       int        =       GPTaTokenizer.from_pretrained(lowerCAmelCase__    ,			*lowerCAmelCase__    ,			**lowerCAmelCase__			)
        return cls.from_tokenizer(lowerCAmelCase__    ,			*lowerCAmelCase__    ,			**lowerCAmelCase__			)
 @classmethod
 def 		SCREAMING_SNAKE_CASE__       (       cls    ,			lowerCAmelCase__			) ->    Dict:




        '''simple docstring'''
        return cls(**lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self			) ->    List[Any]:




        '''simple docstring'''
        return {
            "vocab": self.vocab,
            "merges": self.merges,
            "max_length": self.max_length,
            "pad_token_id": self.pad_token_id,
        }
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			lowerCAmelCase__    ,			lowerCAmelCase__ = None			) ->    Optional[Any]:




        '''simple docstring'''
        lowercase__:       Optional[Any]        =       self.tf_tokenizer(lowerCAmelCase__			)
        lowercase__:       List[Any]        =       tf.ones_like(lowerCAmelCase__			)

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

               if max_length is not None:
                      lowercase__      ,						lowercase__:       List[Any]        =       pad_model_inputs(
                          lowerCAmelCase__    ,			max_seq_length=lowerCAmelCase__    ,			pad_value=self.pad_token_id			)

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


