





from typing import Any

import numpy as np


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase					):
       return np.array_equal(lowerCAmelCase    ,       matrix.conjugate().T					)


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase    ,       lowerCAmelCase					):
       _UpperCamelCase              =						v.conjugate().T
       _UpperCamelCase              =						v_star.dot(lowerCAmelCase					)
       assert isinstance(lowerCAmelCase    ,       np.ndarray					)
       return (v_star_dot.dot(lowerCAmelCase					)) / (v_star.dot(lowerCAmelCase					))


def     SCREAMING_SNAKE_CASE			(      ):
       _UpperCamelCase              =						np.array([[2, 2 + 1j, 4], [2 - 1j, 3, 1j], [4, -1j, 1]]					)
       _UpperCamelCase              =						np.array([[1], [2], [3]]					)
       assert is_hermitian(lowerCAmelCase					), f'''{a} is not hermitian.'''
       print(rayleigh_quotient(lowerCAmelCase    ,       lowerCAmelCase					)					)

       _UpperCamelCase              =						np.array([[1, 2, 4], [2, 3, -1], [4, -1, 1]]					)
       assert is_hermitian(lowerCAmelCase					), f'''{a} is not hermitian.'''
       assert rayleigh_quotient(lowerCAmelCase    ,       lowerCAmelCase					) == float(3					)


if __name__ == "__main__":
       import doctest

       doctest.testmod()
       tests()













import json
import os
from typing import Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


lowercase    : str    	=  logging.get_logger(__name__)

lowercase    : Tuple    	=  {"""vocab_file""": """vocab.json"""}

lowercase    : int    	=  {
    """vocab_file""": {
        """mgp-str""": """https://huggingface.co/alibaba-damo/mgp-str-base/blob/main/vocab.json""",
    }
}

lowercase    : int    	=  {"""mgp-str""": 27}

class  __A(						__UpperCAmelCase ):
     __A	  =       VOCAB_FILES_NAMES
     __A	  =       PRETRAINED_VOCAB_FILES_MAP
     __A	  =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES

     def __init__(      self,       A,       A="[GO]",       A="[GO]",       A="[s]",       A="[GO]",       **A      ):





            """simple docstring"""

            super().__init__(
                unk_token=A,       bos_token=A,       eos_token=A,       pad_token=A,       **A,       )

            with open(A,       encoding='''utf-8'''      ) as vocab_handle:
                   _UpperCamelCase              =						json.load(A      )
            _UpperCamelCase              =						{v: k for k, v in self.vocab.items()}

     @property
     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            return len(self.vocab      )

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            return dict(self.vocab,       **self.added_tokens_encoder      )

     def 	_UpperCamelCase     (      self,       A      ):





            """simple docstring"""

            _UpperCamelCase              =						[]
            for s in text:
                   char_tokens.extend(A      )
            return char_tokens

     def 	_UpperCamelCase     (      self,       A      ):





            """simple docstring"""

            return self.vocab.get(A,       self.vocab.get(self.unk_token      )      )

     def 	_UpperCamelCase     (      self,       A      ):





            """simple docstring"""

            return self.decoder.get(A      )



     def 	_UpperCamelCase     (      self,       A,       A = None      ):





            """simple docstring"""

            if not os.path.isdir(A      ):
                   logger.error('''Vocabulary path ({}) should be a directory'''.format(A      )      )
                   return
            _UpperCamelCase              =						os.path.join(
                A,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )

            with open(A,       '''w''',       encoding='''utf-8'''      ) as f:
                   f.write(json.dumps(self.vocab,       indent=2,       sort_keys=A,       ensure_ascii=A      ) + '''\n'''      )

            return (vocab_file,)






