


'''simple docstring'''






import mpmath  # for roots of unity
import numpy as np




class        a   :
 def __init__(       self					, __magic_name__=None					, __magic_name__=None  )    ->							Any:
      # Input as list
      _a						=							list(poly_a or [0]  )[:]
      _a						=							list(poly_b or [0]  )[:]

      # Remove leading zero coefficients
      while self.polyA[-1] == 0:
           self.polyA.pop()
      _a						=							len(self.polyA  )

      while self.polyB[-1] == 0:
           self.polyB.pop()
      _a						=							len(self.polyB  )

      # Add 0 to make lengths equal a power of 2
      _a						=							int(
          2 ** np.ceil(np.loga(len(self.polyA  ) + len(self.polyB  ) - 1  )  )  )

      while len(self.polyA  ) < self.c_max_length:
           self.polyA.append(0  )
      while len(self.polyB  ) < self.c_max_length:
           self.polyB.append(0  )
      # A complex root used for the fourier transform
      _a						=							complex(mpmath.root(x=1					, n=self.c_max_length					, k=1  )  )

      # The product
      _a						=							self.__multiply()
 def 							__UpperCAmelCase						(       self					, __magic_name__  )    ->							Optional[Any]:
      _a						=							[[x] for x in self.polyA] if which == 'A' else [[x] for x in self.polyB]
      # Corner case
      if len(__SCREAMING_SNAKE_CASE  ) <= 1:
           return dft[0]
      #
      _a						=							self.c_max_length // 2
      while next_ncol > 0:
           _a						=							[[] for i in range(__SCREAMING_SNAKE_CASE  )]
           _a						=							self.root**next_ncol

           # First half of next step
           _a						=							1
           for j in range(self.c_max_length // (next_ncol * 2)  ):
                for i in range(__SCREAMING_SNAKE_CASE  ):
                     new_dft[i].append(dft[i][j] + current_root * dft[i + next_ncol][j]  )
                current_root *= root
           # Second half of next step
           _a						=							1
           for j in range(self.c_max_length // (next_ncol * 2)  ):
                for i in range(__SCREAMING_SNAKE_CASE  ):
                     new_dft[i].append(dft[i][j] - current_root * dft[i + next_ncol][j]  )
                current_root *= root
           # Update
           _a						=							new_dft
           _a						=							next_ncol // 2
      return dft[0]
 def 							__UpperCAmelCase						(       self  )    ->							List[str]:
      _a						=							self.__dft('A'  )
      _a						=							self.__dft('B'  )
      _a						=							[[dft_a[i] * dft_b[i] for i in range(self.c_max_length  )]]
      del dft_a
      del dft_b

      # Corner Case
      if len(inverce_c[0]  ) <= 1:
           return inverce_c[0]
      # Inverse DFT
      _a						=							2
      while next_ncol <= self.c_max_length:
           _a						=							[[] for i in range(__SCREAMING_SNAKE_CASE  )]
           _a						=							self.root ** (next_ncol // 2)
           _a						=							1
           # First half of next step
           for j in range(self.c_max_length // next_ncol  ):
                for i in range(next_ncol // 2  ):
                     # Even positions
                     new_inverse_c[i].append(
                         (
                             inverce_c[i][j]
                             + inverce_c[i][j + self.c_max_length // next_ncol]
                         )
                         / 2  )
                     # Odd positions
                     new_inverse_c[i + next_ncol // 2].append(
                         (
                             inverce_c[i][j]
                             - inverce_c[i][j + self.c_max_length // next_ncol]
                         )
                         / (2 * current_root)  )
                current_root *= root
           # Update
           _a						=							new_inverse_c
           next_ncol *= 2
      # Unpack
      _a						=							[round(x[0].real					, 8  ) + round(x[0].imag					, 8  ) * 1J for x in inverce_c]

      # Remove leading 0's
      while inverce_c[-1] == 0:
           inverce_c.pop()
      return inverce_c




 def __str__(       self  )    ->							Dict:
      _a						=							'A = ' + ' + '.join(
          f'{coef}*x^{i}' for coef, i in enumerate(self.polyA[: self.len_A]  )  )
      _a						=							'B = ' + ' + '.join(
          f'{coef}*x^{i}' for coef, i in enumerate(self.polyB[: self.len_B]  )  )
      _a						=							'A*B = ' + ' + '.join(
          f'{coef}*x^{i}' for coef, i in enumerate(self.product  )  )

      return f'{a}\n{b}\n{c}'


# Unit tests
if __name__ == "__main__":
 import doctest

 doctest.testmod()









"""simple docstring"""





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer


_SCREAMING_SNAKE_CASE					:				Union[str, Any]					    =						{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

_SCREAMING_SNAKE_CASE					:				Union[str, Any]					    =						{
    '''vocab_file''': {
        '''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/vocab.txt''',
    },
    '''tokenizer_file''': {
        '''unc-nlp/lxmert-base-uncased''': (
            '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/tokenizer.json'''
        ),
    },
}

_SCREAMING_SNAKE_CASE					:				Any					    =						{
    '''unc-nlp/lxmert-base-uncased''': 512,
}

_SCREAMING_SNAKE_CASE					:				int					    =						{
    '''unc-nlp/lxmert-base-uncased''': {'''do_lower_case''': True},
}






class      a						(					__snake_case		):
    SCREAMING_SNAKE_CASE						:     int						= VOCAB_FILES_NAMES
    SCREAMING_SNAKE_CASE						:     Optional[Any]						= PRETRAINED_VOCAB_FILES_MAP
    SCREAMING_SNAKE_CASE						:     Any						= PRETRAINED_INIT_CONFIGURATION
    SCREAMING_SNAKE_CASE						:     Any						= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    SCREAMING_SNAKE_CASE						:     Optional[Any]						= LxmertTokenizer






    def __init__(       self     :							str       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]=None       ,						__SCREAMING_SNAKE_CASE     :							Optional[Any]=None       ,						__SCREAMING_SNAKE_CASE     :							str=True       ,						__SCREAMING_SNAKE_CASE     :							List[Any]="[UNK]"       ,						__SCREAMING_SNAKE_CASE     :							int="[SEP]"       ,						__SCREAMING_SNAKE_CASE     :							int="[PAD]"       ,						__SCREAMING_SNAKE_CASE     :							List[Any]="[CLS]"       ,						__SCREAMING_SNAKE_CASE     :							Any="[MASK]"       ,						__SCREAMING_SNAKE_CASE     :							List[str]=True       ,						__SCREAMING_SNAKE_CASE     :							List[str]=None       ,						**__SCREAMING_SNAKE_CASE     :							Any       ,						)     ->		Any:
      super().__init__(
          __SCREAMING_SNAKE_CASE       ,						tokenizer_file=__SCREAMING_SNAKE_CASE       ,						do_lower_case=__SCREAMING_SNAKE_CASE       ,						unk_token=__SCREAMING_SNAKE_CASE       ,						sep_token=__SCREAMING_SNAKE_CASE       ,						pad_token=__SCREAMING_SNAKE_CASE       ,						cls_token=__SCREAMING_SNAKE_CASE       ,						mask_token=__SCREAMING_SNAKE_CASE       ,						tokenize_chinese_chars=__SCREAMING_SNAKE_CASE       ,						strip_accents=__SCREAMING_SNAKE_CASE       ,						**__SCREAMING_SNAKE_CASE       ,						)

      lowerCamelCase_         =						json.loads(self.backend_tokenizer.normalizer.__getstate__()					)
      if (
          normalizer_state.get('lowercase'       ,						__SCREAMING_SNAKE_CASE					) != do_lower_case
          or normalizer_state.get('strip_accents'       ,						__SCREAMING_SNAKE_CASE					) != strip_accents
          or normalizer_state.get('handle_chinese_chars'       ,						__SCREAMING_SNAKE_CASE					) != tokenize_chinese_chars
      ):
        lowerCamelCase_         =						getattr(__SCREAMING_SNAKE_CASE       ,						normalizer_state.pop('type'					)					)
        lowerCamelCase_         =						do_lower_case
        lowerCamelCase_         =						strip_accents
        lowerCamelCase_         =						tokenize_chinese_chars
        lowerCamelCase_         =						normalizer_class(**__SCREAMING_SNAKE_CASE					)

      lowerCamelCase_         =						do_lower_case






    def    UpperCamelCase       (       self     :							Tuple       ,						__SCREAMING_SNAKE_CASE     :							Union[str, Any]       ,						__SCREAMING_SNAKE_CASE     :							Tuple=None					)     ->		Dict:
      lowerCamelCase_         =						[self.cls_token_id] + token_ids_a + [self.sep_token_id]

      if token_ids_a:
        output += token_ids_a + [self.sep_token_id]

      return output






    def    UpperCamelCase       (       self     :							str       ,						__SCREAMING_SNAKE_CASE     :							List[int]       ,						__SCREAMING_SNAKE_CASE     :							Optional[List[int]] = None					)     ->		List[int]:
      lowerCamelCase_         =						[self.sep_token_id]
      lowerCamelCase_         =						[self.cls_token_id]
      if token_ids_a is None:
        return len(cls + token_ids_a + sep					) * [0]
      return len(cls + token_ids_a + sep					) * [0] + len(token_ids_a + sep					) * [1]






    def    UpperCamelCase       (       self     :							List[str]       ,						__SCREAMING_SNAKE_CASE     :							str       ,						__SCREAMING_SNAKE_CASE     :							Optional[str] = None					)     ->		Tuple[str]:
      lowerCamelCase_         =						self._tokenizer.model.save(__SCREAMING_SNAKE_CASE       ,						name=__SCREAMING_SNAKE_CASE					)
      return tuple(__SCREAMING_SNAKE_CASE					)




