





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer


UpperCAmelCase_ 							=       logging.get_logger(__name__)

UpperCAmelCase_ 							=       {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

UpperCAmelCase_ 							=       {
    """vocab_file""": {
        """bert-base-uncased""": """https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt""",
        """bert-large-uncased""": """https://huggingface.co/bert-large-uncased/resolve/main/vocab.txt""",
        """bert-base-cased""": """https://huggingface.co/bert-base-cased/resolve/main/vocab.txt""",
        """bert-large-cased""": """https://huggingface.co/bert-large-cased/resolve/main/vocab.txt""",
        """bert-base-multilingual-uncased""": (
            """https://huggingface.co/bert-base-multilingual-uncased/resolve/main/vocab.txt"""
        ),
        """bert-base-multilingual-cased""": """https://huggingface.co/bert-base-multilingual-cased/resolve/main/vocab.txt""",
        """bert-base-chinese""": """https://huggingface.co/bert-base-chinese/resolve/main/vocab.txt""",
        """bert-base-german-cased""": """https://huggingface.co/bert-base-german-cased/resolve/main/vocab.txt""",
        """bert-large-uncased-whole-word-masking""": (
            """https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/vocab.txt"""
        ),
        """bert-large-cased-whole-word-masking""": (
            """https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/vocab.txt"""
        ),
        """bert-large-uncased-whole-word-masking-finetuned-squad""": (
            """https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt"""
        ),
        """bert-large-cased-whole-word-masking-finetuned-squad""": (
            """https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt"""
        ),
        """bert-base-cased-finetuned-mrpc""": (
            """https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/vocab.txt"""
        ),
        """bert-base-german-dbmdz-cased""": """https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/vocab.txt""",
        """bert-base-german-dbmdz-uncased""": (
            """https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/vocab.txt"""
        ),
        """TurkuNLP/bert-base-finnish-cased-v1""": (
            """https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/vocab.txt"""
        ),
        """TurkuNLP/bert-base-finnish-uncased-v1""": (
            """https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/vocab.txt"""
        ),
        """wietsedv/bert-base-dutch-cased""": (
            """https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/vocab.txt"""
        ),
    },
    """tokenizer_file""": {
        """bert-base-uncased""": """https://huggingface.co/bert-base-uncased/resolve/main/tokenizer.json""",
        """bert-large-uncased""": """https://huggingface.co/bert-large-uncased/resolve/main/tokenizer.json""",
        """bert-base-cased""": """https://huggingface.co/bert-base-cased/resolve/main/tokenizer.json""",
        """bert-large-cased""": """https://huggingface.co/bert-large-cased/resolve/main/tokenizer.json""",
        """bert-base-multilingual-uncased""": (
            """https://huggingface.co/bert-base-multilingual-uncased/resolve/main/tokenizer.json"""
        ),
        """bert-base-multilingual-cased""": (
            """https://huggingface.co/bert-base-multilingual-cased/resolve/main/tokenizer.json"""
        ),
        """bert-base-chinese""": """https://huggingface.co/bert-base-chinese/resolve/main/tokenizer.json""",
        """bert-base-german-cased""": """https://huggingface.co/bert-base-german-cased/resolve/main/tokenizer.json""",
        """bert-large-uncased-whole-word-masking""": (
            """https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/tokenizer.json"""
        ),
        """bert-large-cased-whole-word-masking""": (
            """https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/tokenizer.json"""
        ),
        """bert-large-uncased-whole-word-masking-finetuned-squad""": (
            """https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json"""
        ),
        """bert-large-cased-whole-word-masking-finetuned-squad""": (
            """https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json"""
        ),
        """bert-base-cased-finetuned-mrpc""": (
            """https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/tokenizer.json"""
        ),
        """bert-base-german-dbmdz-cased""": (
            """https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/tokenizer.json"""
        ),
        """bert-base-german-dbmdz-uncased""": (
            """https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/tokenizer.json"""
        ),
        """TurkuNLP/bert-base-finnish-cased-v1""": (
            """https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/tokenizer.json"""
        ),
        """TurkuNLP/bert-base-finnish-uncased-v1""": (
            """https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/tokenizer.json"""
        ),
        """wietsedv/bert-base-dutch-cased""": (
            """https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/tokenizer.json"""
        ),
    },
}

UpperCAmelCase_ 							=       {
    """bert-base-uncased""": 512,
    """bert-large-uncased""": 512,
    """bert-base-cased""": 512,
    """bert-large-cased""": 512,
    """bert-base-multilingual-uncased""": 512,
    """bert-base-multilingual-cased""": 512,
    """bert-base-chinese""": 512,
    """bert-base-german-cased""": 512,
    """bert-large-uncased-whole-word-masking""": 512,
    """bert-large-cased-whole-word-masking""": 512,
    """bert-large-uncased-whole-word-masking-finetuned-squad""": 512,
    """bert-large-cased-whole-word-masking-finetuned-squad""": 512,
    """bert-base-cased-finetuned-mrpc""": 512,
    """bert-base-german-dbmdz-cased""": 512,
    """bert-base-german-dbmdz-uncased""": 512,
    """TurkuNLP/bert-base-finnish-cased-v1""": 512,
    """TurkuNLP/bert-base-finnish-uncased-v1""": 512,
    """wietsedv/bert-base-dutch-cased""": 512,
}

UpperCAmelCase_ 							=       {
    """bert-base-uncased""": {"""do_lower_case""": True},
    """bert-large-uncased""": {"""do_lower_case""": True},
    """bert-base-cased""": {"""do_lower_case""": False},
    """bert-large-cased""": {"""do_lower_case""": False},
    """bert-base-multilingual-uncased""": {"""do_lower_case""": True},
    """bert-base-multilingual-cased""": {"""do_lower_case""": False},
    """bert-base-chinese""": {"""do_lower_case""": False},
    """bert-base-german-cased""": {"""do_lower_case""": False},
    """bert-large-uncased-whole-word-masking""": {"""do_lower_case""": True},
    """bert-large-cased-whole-word-masking""": {"""do_lower_case""": False},
    """bert-large-uncased-whole-word-masking-finetuned-squad""": {"""do_lower_case""": True},
    """bert-large-cased-whole-word-masking-finetuned-squad""": {"""do_lower_case""": False},
    """bert-base-cased-finetuned-mrpc""": {"""do_lower_case""": False},
    """bert-base-german-dbmdz-cased""": {"""do_lower_case""": False},
    """bert-base-german-dbmdz-uncased""": {"""do_lower_case""": True},
    """TurkuNLP/bert-base-finnish-cased-v1""": {"""do_lower_case""": False},
    """TurkuNLP/bert-base-finnish-uncased-v1""": {"""do_lower_case""": True},
    """wietsedv/bert-base-dutch-cased""": {"""do_lower_case""": False},
}
class      UpperCamelCase_						(					_lowerCamelCase   ):
					lowerCAmelCase_							=		VOCAB_FILES_NAMES
					lowerCAmelCase_							=		PRETRAINED_VOCAB_FILES_MAP
					lowerCAmelCase_							=		PRETRAINED_INIT_CONFIGURATION
					lowerCAmelCase_							=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowerCAmelCase_							=		BertTokenizer




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

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

										_snake_case													=			do_lower_case




					def 		lowerCAmelCase     (						self			,  lowerCAmelCase_			,  lowerCAmelCase_=None					)						->							Any:
										_snake_case													=			[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 		lowerCAmelCase     (						self			,  lowerCAmelCase_			,  lowerCAmelCase_ = None					)						->							List[int]:
										_snake_case													=			[self.sep_token_id]
										_snake_case													=			[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 		lowerCAmelCase     (						self			,  lowerCAmelCase_			,  lowerCAmelCase_ = None					)						->							Tuple[str]:
										_snake_case													=			self._tokenizer.model.save(lowerCAmelCase_			,  name=lowerCAmelCase_					)
										return tuple(lowerCAmelCase_					)








import random





def   lowerCamelCase__       (       UpperCamelCase__     :    int    ,      UpperCamelCase__     :    float    ,      UpperCamelCase__     :    bool = False  )     ->	dict:



					'''simple docstring'''




					_snake_case													=			{i: [] for i in range(UpperCamelCase__  )}

					# if probability is greater or equal than 1, then generate a complete graph
					if probability >= 1:
										return complete_graph(UpperCamelCase__  )
					# if probability is lower or equal than 0, then return a graph without edges
					if probability <= 0:
										return graph

					# for each couple of nodes, add an edge from u to v
					# if the number randomly generated is greater than probability probability
					for i in range(UpperCamelCase__  ):
										for j in range(i + 1    ,      UpperCamelCase__  ):
															if random.random() < probability:
																				graph[i].append(UpperCamelCase__  )
																				if not directed:
																									# if the graph is undirected, add an edge in from j to i, either
																									graph[j].append(UpperCamelCase__  )
					return graph





def   lowerCamelCase__       (       UpperCamelCase__     :    int  )     ->	dict:



					'''simple docstring'''




					return {
					    i: [j for j in range(UpperCamelCase__  ) if i != j] for i in range(UpperCamelCase__  )
					}


if __name__ == "__main__":
					import doctest

					doctest.testmod()



