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  __magic_name__  (		tf.keras.layers.Layer    ):





   """simple docstring"""




   def __init__(	self					:  List[Any]		,  _lowercase					:  Dict[str, int]		,  _lowercase					:  List[str]		,  _lowercase					:  int = None		,  _lowercase					:  int = None							):



    """simple docstring"""



    super().__init__()
    _UpperCamelCase:     List[str]							= pad_token_id
    _UpperCamelCase:     Any							= max_length
    _UpperCamelCase:     str							= vocab
    _UpperCamelCase:     int							= merges
    _UpperCamelCase:     Any							= BytePairTokenizer(_lowercase		,  _lowercase		,  sequence_length=_lowercase							)



   @classmethod
   def   lowerCAmelCase						(	cls					:  Tuple		,  _lowercase					:  GPTaTokenizer		,  *_lowercase					:  Union[str, Any]		,  **_lowercase					:  Optional[Any]							):



    """simple docstring"""



    _UpperCamelCase:     List[str]							= [''' '''.join(_lowercase							) for m in tokenizer.bpe_ranks.keys()]
    _UpperCamelCase:     int							= tokenizer.get_vocab()
    return cls(_lowercase		,  _lowercase		,  *_lowercase		,  **_lowercase							)



   @classmethod
   def   lowerCAmelCase						(	cls					:  Union[str, Any]		,  _lowercase					:  Union[str, os.PathLike]		,  *_lowercase					:  List[str]		,  **_lowercase					:  List[Any]							):



    """simple docstring"""



    _UpperCamelCase:     Union[str, Any]							= GPTaTokenizer.from_pretrained(_lowercase		,  *_lowercase		,  **_lowercase							)
    return cls.from_tokenizer(_lowercase		,  *_lowercase		,  **_lowercase							)



   @classmethod
   def   lowerCAmelCase						(	cls					:  Union[str, Any]		,  _lowercase					:  Tuple							):



    """simple docstring"""



    return cls(**_lowercase							)



   def   lowerCAmelCase						(	self					:  Any							):



    """simple docstring"""



    return {
        "vocab": self.vocab,
        "merges": self.merges,
        "max_length": self.max_length,
        "pad_token_id": self.pad_token_id,
    }



   def   lowerCAmelCase						(	self					:  Optional[Any]		,  _lowercase					:  Any		,  _lowercase					:  int = None							):



    """simple docstring"""



    _UpperCamelCase:     Dict							= self.tf_tokenizer(_lowercase							)
    _UpperCamelCase:     Dict							= tf.ones_like(_lowercase							)

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

     if max_length is not None:
      _UpperCamelCase	,							_UpperCamelCase:     str							= pad_model_inputs(
          _lowercase		,  max_seq_length=_lowercase		,  pad_value=self.pad_token_id							)

    return {"attention_mask": attention_mask, "input_ids": input_ids}
from __future__ import annotations




def       lowerCAmelCase_     (		lowercase:							int = 4		)    ->				list[list[int]]:







 '''simple docstring'''
 _UpperCamelCase:     Dict							= abs(lowercase		) or 4
 return [[1 + x + y * row_size for x in range(lowercase		)] for y in range(lowercase		)]




def       lowerCAmelCase_     (		lowercase:							list[list[int]]		)    ->				list[list[int]]:







 '''simple docstring'''
 return reverse_row(transpose(lowercase		)		)
 # OR.. transpose(reverse_column(matrix))




def       lowerCAmelCase_     (		lowercase:							list[list[int]]		)    ->				list[list[int]]:







 '''simple docstring'''
 return reverse_row(reverse_column(lowercase		)		)
 # OR.. reverse_column(reverse_row(matrix))




def       lowerCAmelCase_     (		lowercase:							list[list[int]]		)    ->				list[list[int]]:







 '''simple docstring'''
 return reverse_column(transpose(lowercase		)		)
 # OR.. transpose(reverse_row(matrix))




def       lowerCAmelCase_     (		lowercase:							list[list[int]]		)    ->				list[list[int]]:







 '''simple docstring'''
 _UpperCamelCase:     int							= [list(lowercase		) for x in zip(*lowercase		)]
 return matrix




def       lowerCAmelCase_     (		lowercase:							list[list[int]]		)    ->				list[list[int]]:







 '''simple docstring'''
 _UpperCamelCase:     str							= matrix[::-1]
 return matrix




def       lowerCAmelCase_     (		lowercase:							list[list[int]]		)    ->				list[list[int]]:







 '''simple docstring'''
 _UpperCamelCase:     str							= [x[::-1] for x in matrix]
 return matrix




def       lowerCAmelCase_     (		lowercase:							list[list[int]]		)    ->				None:







 '''simple docstring'''
 for i in matrix:
  print(*lowercase		)


if __name__ == "__main__":
  UpperCAmelCase_			    =							make_matrix()
  print('''\norigin:\n''')
  print_matrix(matrix)
  print('''\nrotate 90 counterclockwise:\n''')
  print_matrix(rotate_aa(matrix))

  UpperCAmelCase_			    =							make_matrix()
  print('''\norigin:\n''')
  print_matrix(matrix)
  print('''\nrotate 180:\n''')
  print_matrix(rotate_aaa(matrix))

  UpperCAmelCase_			    =							make_matrix()
  print('''\norigin:\n''')
  print_matrix(matrix)
  print('''\nrotate 270 counterclockwise:\n''')
  print_matrix(rotate_aaa(matrix))