import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
						from .tokenization_xlnet import XLNetTokenizer
else:
						_lowercase		:				Tuple	       =		None


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

_lowercase		:				Optional[Any]	       =		{"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

_lowercase		:				Optional[int]	       =		{
    """vocab_file""": {
        """xlnet-base-cased""": """https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model""",
        """xlnet-large-cased""": """https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model""",
    },
    """tokenizer_file""": {
        """xlnet-base-cased""": """https://huggingface.co/xlnet-base-cased/resolve/main/tokenizer.json""",
        """xlnet-large-cased""": """https://huggingface.co/xlnet-large-cased/resolve/main/tokenizer.json""",
    },
}

_lowercase		:				Any	       =		{
    """xlnet-base-cased""": None,
    """xlnet-large-cased""": None,
}

_lowercase		:				Optional[int]	       =		"""▁"""

# Segments (not really needed)
_lowercase		:				List[str]	       =		0
_lowercase		:				List[Any]	       =		1
_lowercase		:				Dict	       =		2
_lowercase		:				Union[str, Any]	       =		3
_lowercase		:				Dict	       =		4





class 					__magic_name__		(					_UpperCAmelCase):
			UpperCamelCase__       = VOCAB_FILES_NAMES
			UpperCamelCase__       = PRETRAINED_VOCAB_FILES_MAP
			UpperCamelCase__       = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			UpperCamelCase__       = "left"
			UpperCamelCase__       = XLNetTokenizer







			def __init__(			self       :						Optional[Any]       ,    lowercase_       :						int=None       ,    lowercase_       :						int=None       ,    lowercase_       :						List[str]=False       ,    lowercase_       :						str=True       ,    lowercase_       :						int=False       ,    lowercase_       :						Tuple="<s>"       ,    lowercase_       :						Dict="</s>"       ,    lowercase_       :						List[Any]="<unk>"       ,    lowercase_       :						Optional[int]="<sep>"       ,    lowercase_       :						Any="<pad>"       ,    lowercase_       :						Optional[Any]="<cls>"       ,    lowercase_       :						Dict="<mask>"       ,    lowercase_       :						List[Any]=["<eop>", "<eod>"]       ,    **lowercase_       :						str       ,    ):
										lowercase_      :    List[str]       		= AddedToken(UpperCamelCase__       ,    lstrip=UpperCamelCase__       ,    rstrip=UpperCamelCase__					) if isinstance(UpperCamelCase__       ,    UpperCamelCase__					) else mask_token

										super().__init__(
										    vocab_file=UpperCamelCase__       ,    tokenizer_file=UpperCamelCase__       ,    do_lower_case=UpperCamelCase__       ,    remove_space=UpperCamelCase__       ,    keep_accents=UpperCamelCase__       ,    bos_token=UpperCamelCase__       ,    eos_token=UpperCamelCase__       ,    unk_token=UpperCamelCase__       ,    sep_token=UpperCamelCase__       ,    pad_token=UpperCamelCase__       ,    cls_token=UpperCamelCase__       ,    mask_token=UpperCamelCase__       ,    additional_special_tokens=UpperCamelCase__       ,    **UpperCamelCase__       ,    )

										lowercase_      :    Tuple       		= 3
										lowercase_      :    List[str]       		= do_lower_case
										lowercase_      :    Optional[int]       		= remove_space
										lowercase_      :    str       		= keep_accents
										lowercase_      :    Any       		= vocab_file
										lowercase_      :    List[Any]       		= False if not self.vocab_file else True







			def 			SCREAMING_SNAKE_CASE_  (			self       :						int       ,    lowercase_       :						str       ,    lowercase_       :						List[str] = None					):
										lowercase_      :    str       		= [self.sep_token_id]
										lowercase_      :    Optional[int]       		= [self.cls_token_id]
										if token_ids_a is None:
																	return token_ids_a + sep + cls
										return token_ids_a + sep + token_ids_a + sep + cls







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Dict       ,    lowercase_       :						Optional[Any]       ,    lowercase_       :						List[Any] = None					):
										lowercase_      :    Tuple       		= [self.sep_token_id]
										lowercase_      :    Optional[int]       		= [2]

										if token_ids_a is None:
																	return len(token_ids_a + sep					) * [0] + cls_segment_id
										return len(token_ids_a + sep					) * [0] + len(token_ids_a + sep					) * [1] + cls_segment_id







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Tuple       ,    lowercase_       :						List[Any]       ,    lowercase_       :						List[Any] = None					):





										if not self.can_save_slow_tokenizer:
																	raise ValueError(
																	    """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
																	    """tokenizer."""					)

										if not os.path.isdir(UpperCamelCase__					):
																	logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''					)
																	return
										lowercase_      :    Optional[Any]       		= os.path.join(
										    UpperCamelCase__       ,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]					)

										if os.path.abspath(self.vocab_file					) != os.path.abspath(UpperCamelCase__					):
																	copyfile(self.vocab_file       ,    UpperCamelCase__					)

										return (out_vocab_file,)






'''simple docstring'''




import unittest

import numpy as np




def 							lowerCamelCase			(   UpperCAmelCase__ :      np.ndarray   ,   UpperCAmelCase__ :      np.ndarray   ,   UpperCAmelCase__ :      np.ndarray   ,   UpperCAmelCase__ :      np.ndarray | None = None   ,   )    ->   np.ndarray:
							lowercase_      :    List[Any]       		= np.shape(UpperCAmelCase__				)
							lowercase_      :    Dict       		= np.shape(UpperCAmelCase__				)
							lowercase_      :    int       		= np.shape(UpperCAmelCase__				)

							if shape_a[0] != shape_b[0]:
														lowercase_      :    Optional[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]:
														lowercase_      :    Optional[Any]       		= (
														    """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__				)

							lowercase_      :    Any       		= pseudo_inv
							if a_inv is None:
														try:
																					lowercase_      :    List[str]       		= 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 					__magic_name__		(					unittest.TestCase):







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Optional[int]					):
										lowercase_      :    Tuple       		= np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]					)
										lowercase_      :    int       		= np.array([[0, 3], [3, 0], [2, 3]]					)
										lowercase_      :    Dict       		= np.array([[2, 1], [6, 3]]					)

										lowercase_      :    Union[str, Any]       		= schur_complement(lowercase_       ,    lowercase_       ,    lowercase_					)

										lowercase_      :    List[Any]       		= np.block([[a, b], [b.T, c]]					)

										lowercase_      :    Optional[int]       		= np.linalg.det(lowercase_					)
										lowercase_      :    int       		= np.linalg.det(lowercase_					)
										lowercase_      :    int       		= np.linalg.det(lowercase_					)

										self.assertAlmostEqual(lowercase_       ,    det_a * det_s					)







			def 			SCREAMING_SNAKE_CASE_  (			self       :						str					):
										lowercase_      :    int       		= np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]					)
										lowercase_      :    Optional[Any]       		= np.array([[0, 3], [3, 0], [2, 3]]					)
										lowercase_      :    Union[str, Any]       		= np.array([[2, 1], [6, 3]]					)

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







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Any					):
										lowercase_      :    List[Any]       		= np.array([[1, 2, 1], [2, 1, 2], [3, 2, 4]]					)
										lowercase_      :    List[Any]       		= np.array([[0, 3], [3, 0], [2, 3]]					)
										lowercase_      :    str       		= np.array([[2, 1, 3], [6, 3, 5]]					)

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


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						unittest.main()





