






"""simple docstring"""




import json
import os
from typing import Optional, Tuple

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


_snake_case          =   logging.get_logger(__name__)

_snake_case          =   {'vocab_file': 'vocab.json'}

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

_snake_case          =   {'mgp-str': 27}






class        UpperCamelCase			(	snake_case_      ):
 UpperCamelCase					:       List[str]			=					VOCAB_FILES_NAMES
 UpperCamelCase					:       Union[str, Any]			=					PRETRAINED_VOCAB_FILES_MAP
 UpperCamelCase					:       Optional[int]			=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES


 def __init__(     self		:						Optional[int]							,						UpperCAmelCase__		:						List[str]							,						UpperCAmelCase__		:						List[Any]="[GO]"							,						UpperCAmelCase__		:						Tuple="[GO]"							,						UpperCAmelCase__		:						Optional[int]="[s]"							,						UpperCAmelCase__		:						int="[GO]"							,						**UpperCAmelCase__		:						Dict							)					->       int:
   super().__init__(
       unk_token=UpperCAmelCase__							,						bos_token=UpperCAmelCase__							,						eos_token=UpperCAmelCase__							,						pad_token=UpperCAmelCase__							,						**UpperCAmelCase__							,						)

   with open(UpperCAmelCase__							,						encoding="""utf-8"""							) as vocab_handle:
     _a  :       int             =	json.load(UpperCAmelCase__							)
   _a  :       Optional[int]             =	{v: k for k, v in self.vocab.items()}


 @property
 def _lowercase	(     self		:						Dict							)					->       Union[str, Any]:
   return len(self.vocab							)


 def _lowercase	(     self		:						Union[str, Any]							)					->       str:
   return dict(self.vocab							,						**self.added_tokens_encoder							)


 def _lowercase	(     self		:						Dict							,						UpperCAmelCase__		:						str							)					->       Union[str, Any]:
   _a  :       Tuple             =	[]
   for s in text:
     char_tokens.extend(UpperCAmelCase__							)
   return char_tokens


 def _lowercase	(     self		:						List[Any]							,						UpperCAmelCase__		:						str							)					->       Dict:
   return self.vocab.get(UpperCAmelCase__							,						self.vocab.get(self.unk_token							)							)


 def _lowercase	(     self		:						Optional[int]							,						UpperCAmelCase__		:						Tuple							)					->       List[Any]:
   return self.decoder.get(UpperCAmelCase__							)







 def _lowercase	(     self		:						Optional[int]							,						UpperCAmelCase__		:						str							,						UpperCAmelCase__		:						Optional[str] = None							)					->       Tuple[str]:
   if not os.path.isdir(UpperCAmelCase__							):
     logger.error("""Vocabulary path ({}) should be a directory""".format(UpperCAmelCase__							)							)
     return
   _a  :       Tuple             =	os.path.join(
       UpperCAmelCase__							,						(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]							)

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

   return (vocab_file,)









"""simple docstring"""




import unittest

import numpy as np

def 			lowerCAmelCase__     (     UpperCamelCase__     ,   UpperCamelCase__     ,   UpperCamelCase__     ,   UpperCamelCase__ = None     ,   ):



  '''simple docstring'''
  _a  :       List[Any]             =	np.shape(UpperCamelCase__				)
  _a  :       Any             =	np.shape(UpperCamelCase__				)
  _a  :       Union[str, Any]             =	np.shape(UpperCamelCase__				)

  if shape_a[0] != shape_b[0]:
    _a  :       int             =	(
        """Expected the same number of rows for A and B. """
        F"""Instead found A of size {shape_a} and B of size {shape_b}"""
    )
    raise ValueError(UpperCamelCase__				)

  if shape_b[1] != shape_c[1]:
    _a  :       Tuple             =	(
        """Expected the same number of columns for B and C. """
        F"""Instead found B of size {shape_b} and C of size {shape_c}"""
    )
    raise ValueError(UpperCamelCase__				)

  _a  :       int             =	pseudo_inv
  if a_inv is None:
    try:
      _a  :       Optional[int]             =	np.linalg.inv(UpperCamelCase__				)
    except np.linalg.LinAlgError:
      raise ValueError(
          """Input matrix A is not invertible. Cannot compute Schur complement."""				)

  return mat_c - mat_b.T @ a_inv @ mat_b






class        UpperCamelCase			(	unittest.TestCase      ):


 def _lowercase	(     self		:						int							)					->       None:
   _a  :       str             =	np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]							)
   _a  :       Tuple             =	np.array([[0, 3], [3, 0], [2, 3]]							)
   _a  :       Optional[int]             =	np.array([[2, 1], [6, 3]]							)

   _a  :       Optional[Any]             =	schur_complement(UpperCAmelCase__							,						UpperCAmelCase__							,						UpperCAmelCase__							)

   _a  :       Union[str, Any]             =	np.block([[a, b], [b.T, c]]							)

   _a  :       int             =	np.linalg.det(UpperCAmelCase__							)
   _a  :       Union[str, Any]             =	np.linalg.det(UpperCAmelCase__							)
   _a  :       List[Any]             =	np.linalg.det(UpperCAmelCase__							)

   self.assertAlmostEqual(UpperCAmelCase__							,						det_a * det_s							)


 def _lowercase	(     self		:						int							)					->       None:
   _a  :       Optional[int]             =	np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]							)
   _a  :       Optional[int]             =	np.array([[0, 3], [3, 0], [2, 3]]							)
   _a  :       Union[str, Any]             =	np.array([[2, 1], [6, 3]]							)

   with self.assertRaises(UpperCAmelCase__							):
     schur_complement(UpperCAmelCase__							,						UpperCAmelCase__							,						UpperCAmelCase__							)







 def _lowercase	(     self		:						List[Any]							)					->       None:
   _a  :       Any             =	np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]							)
   _a  :       Dict             =	np.array([[0, 3], [3, 0], [2, 3]]							)
   _a  :       List[Any]             =	np.array([[2, 1, 3], [6, 3, 5]]							)

   with self.assertRaises(UpperCAmelCase__							):
     schur_complement(UpperCAmelCase__							,						UpperCAmelCase__							,						UpperCAmelCase__							)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 unittest.main()

