





'''simple docstring'''




import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union

import numpy as np

from ...utils import is_tf_available, is_torch_available, logging


if TYPE_CHECKING:
  if is_torch_available():
    import torch
  if is_tf_available():
    import tensorflow as tf

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_codegen import CodeGenTokenizer


lowercase__       : Optional[Any]         =       logging.get_logger(__name__)

lowercase__       : List[str]         =       {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

lowercase__       : List[Any]         =       {
    '''vocab_file''': {
        '''Salesforce/codegen-350M-mono''': '''https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''Salesforce/codegen-350M-mono''': '''https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''Salesforce/codegen-350M-mono''': (
            '''https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/tokenizer.json'''
        ),
    },
}

lowercase__       : Optional[int]         =       {
    '''Salesforce/codegen-350M-mono''': 20_48,
}


class 					SCREAMING_SNAKE_CASE       (a__				):
     lowerCAmelCase						     =			VOCAB_FILES_NAMES
     lowerCAmelCase						     =			PRETRAINED_VOCAB_FILES_MAP
     lowerCAmelCase						     =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCAmelCase						     =			['''input_ids''', '''attention_mask''']
     lowerCAmelCase						     =			CodeGenTokenizer


     def __init__(		self		,      _UpperCAmelCase=None		,      _UpperCAmelCase=None		,      _UpperCAmelCase=None		,      _UpperCAmelCase="<|endoftext|>"		,      _UpperCAmelCase="<|endoftext|>"		,      _UpperCAmelCase="<|endoftext|>"		,      _UpperCAmelCase=False		,      **_UpperCAmelCase		,      ):

          '''simple docstring'''






          super().__init__(
              _UpperCAmelCase		,      _UpperCAmelCase		,      tokenizer_file=_UpperCAmelCase		,      unk_token=_UpperCAmelCase		,      bos_token=_UpperCAmelCase		,      eos_token=_UpperCAmelCase		,      add_prefix_space=_UpperCAmelCase		,      **_UpperCAmelCase		,      )

          if kwargs.pop('add_bos_token'		,      _UpperCAmelCase):
               __A		:					List[Any]						=			kwargs.pop('name_or_path'		,      '')
               raise ValueError(
                   'Currenty GPT2\'s fast tokenizer does NOT support adding a BOS token.'
                   'Instead you should use GPT2\'s slow tokenizer class `CodeGenTokenizer` as follows: \n'
                   F'`CodeGenTokenizer.from_pretrained(\'{model_id}\')`\nor\n'
                   F'`AutoTokenizer.from_pretrained(\'{model_id}\', use_fast=False)`\n'
                   'This issue will be fixed soon, see: https://github.com/huggingface/tokenizers/pull/1005.'
                   ' so that the fast tokenizer works correctly.')

          __A		:					List[str]						=			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
          if pre_tok_state.get('add_prefix_space'		,      _UpperCAmelCase) != add_prefix_space:
               __A		:					Dict						=			getattr(_UpperCAmelCase		,      pre_tok_state.pop('type'))
               __A		:					Optional[int]						=			add_prefix_space
               __A		:					Union[str, Any]						=			pre_tok_class(**_UpperCAmelCase)

          __A		:					Tuple						=			add_prefix_space


     def 				SCREAMING_SNAKE_CASE    (		self		,      *_UpperCAmelCase		,      **_UpperCAmelCase):

          '''simple docstring'''






          __A		:					Dict						=			kwargs.get('is_split_into_words'		,      _UpperCAmelCase)
          assert self.add_prefix_space or not is_split_into_words, (
              F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
              "to use it with pretokenized inputs."
          )

          return super()._batch_encode_plus(*_UpperCAmelCase		,      **_UpperCAmelCase)


     def 				SCREAMING_SNAKE_CASE    (		self		,      *_UpperCAmelCase		,      **_UpperCAmelCase):

          '''simple docstring'''






          __A		:					str						=			kwargs.get('is_split_into_words'		,      _UpperCAmelCase)

          assert self.add_prefix_space or not is_split_into_words, (
              F'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
              "to use it with pretokenized inputs."
          )

          return super()._encode_plus(*_UpperCAmelCase		,      **_UpperCAmelCase)


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase = None):

          '''simple docstring'''






          __A		:					List[str]						=			self._tokenizer.model.save(_UpperCAmelCase		,      name=_UpperCAmelCase)
          return tuple(_UpperCAmelCase)


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase = False		,      _UpperCAmelCase = None		,      _UpperCAmelCase = None		,      **_UpperCAmelCase		,      ):

          '''simple docstring'''






          __A		:					List[str]						=			super().decode(
              token_ids=_UpperCAmelCase		,      skip_special_tokens=_UpperCAmelCase		,      clean_up_tokenization_spaces=_UpperCAmelCase		,      **_UpperCAmelCase		,      )

          if truncate_before_pattern is not None and len(_UpperCAmelCase) > 0:
               __A		:					Union[str, Any]						=			self.truncate(_UpperCAmelCase		,      _UpperCAmelCase)

          return decoded_text


     def 				SCREAMING_SNAKE_CASE    (		self		,      _UpperCAmelCase		,      _UpperCAmelCase):

          '''simple docstring'''






          def find_re(_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase):
               __A		:					Union[str, Any]						=			pattern.search(_UpperCAmelCase		,      _UpperCAmelCase)
               return m.start() if m else -1

          __A		:					int						=			[re.compile(_UpperCAmelCase		,      re.MULTILINE) for pattern in truncate_before_pattern]

          __A		:					Union[str, Any]						=			list(re.finditer('^print'		,      _UpperCAmelCase		,      re.MULTILINE))

          if len(_UpperCAmelCase) > 1:
               __A		:					Dict						=			completion[: prints[1].start()]

          __A		:					List[Any]						=			list(re.finditer('^def'		,      _UpperCAmelCase		,      re.MULTILINE))

          if len(_UpperCAmelCase) > 1:
               __A		:					Any						=			completion[: defs[1].start()]

          __A		:					Union[str, Any]						=			0

          __A		:					int						=			[
              pos for pos in [find_re(_UpperCAmelCase		,      _UpperCAmelCase		,      _UpperCAmelCase) for terminal in terminals] if pos != -1
          ]

          if len(_UpperCAmelCase) > 0:
               return completion[: min(_UpperCAmelCase)]
          else:
               return completion






'''simple docstring'''




import math
import sys






def 			_lowerCAmelCase     (    __snake_case    :					int     )	->	int:
     if number != int(__snake_case     ):
          raise ValueError('the value of input must be a natural number'     )
     if number < 0:
          raise ValueError('the value of input must not be a negative number'     )
     if number == 0:
          return 1
     __A		:					str						=			[-1] * (number + 1)
     __A		:					Dict						=			0
     for i in range(1					,				number + 1     ):
          __A		:					int						=			sys.maxsize
          __A		:					int						=			int(math.sqrt(__snake_case     )     )
          for j in range(1					,				root + 1     ):
               __A		:					str						=			1 + answers[i - (j**2)]
               __A		:					Dict						=			min(__snake_case					,				__snake_case     )
          __A		:					Union[str, Any]						=			answer
     return answers[number]


if __name__ == "__main__":
  import doctest

  doctest.testmod()