




"""simple docstring"""





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


A				=							logging.get_logger(__name__)

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

A				=							{
    """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"""
        ),
    },
}

A				=							{
    """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,
}

A				=							{
    """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   a__					(						__magic_name__ ):
			lowercase_		=						VOCAB_FILES_NAMES
			lowercase_		=						PRETRAINED_VOCAB_FILES_MAP
			lowercase_		=						PRETRAINED_INIT_CONFIGURATION
			lowercase_		=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowercase_		=						BertTokenizer


			def __init__(   self   :     Any   ,	UpperCamelCase_   :     List[Any]=None   ,	UpperCamelCase_   :     List[str]=None   ,	UpperCamelCase_   :     Tuple=True   ,	UpperCamelCase_   :     Union[str, Any]="[UNK]"   ,	UpperCamelCase_   :     Union[str, Any]="[SEP]"   ,	UpperCamelCase_   :     List[Any]="[PAD]"   ,	UpperCamelCase_   :     List[Any]="[CLS]"   ,	UpperCamelCase_   :     Tuple="[MASK]"   ,	UpperCamelCase_   :     Union[str, Any]=True   ,	UpperCamelCase_   :     Optional[int]=None   ,	**UpperCamelCase_   :     Optional[int]   ,	):


						"""simple docstring"""




						super().__init__(
						    UpperCamelCase_   ,	tokenizer_file=UpperCamelCase_   ,	do_lower_case=UpperCamelCase_   ,	unk_token=UpperCamelCase_   ,	sep_token=UpperCamelCase_   ,	pad_token=UpperCamelCase_   ,	cls_token=UpperCamelCase_   ,	mask_token=UpperCamelCase_   ,	tokenize_chinese_chars=UpperCamelCase_   ,	strip_accents=UpperCamelCase_   ,	**UpperCamelCase_   ,	)

						__UpperCAmelCase						:			Union[str, Any]												=       json.loads(self.backend_tokenizer.normalizer.__getstate__())
						if (
						    normalizer_state.get("lowercase"   ,	UpperCamelCase_) != do_lower_case
						    or normalizer_state.get("strip_accents"   ,	UpperCamelCase_) != strip_accents
						    or normalizer_state.get("handle_chinese_chars"   ,	UpperCamelCase_) != tokenize_chinese_chars
						):
									__UpperCAmelCase						:			Dict												=       getattr(UpperCamelCase_   ,	normalizer_state.pop("type"))
									__UpperCAmelCase						:			Any												=       do_lower_case
									__UpperCAmelCase						:			List[str]												=       strip_accents
									__UpperCAmelCase						:			Any												=       tokenize_chinese_chars
									__UpperCAmelCase						:			Union[str, Any]												=       normalizer_class(**UpperCamelCase_)

						__UpperCAmelCase						:			List[Any]												=       do_lower_case


			def    a_  (   self   :     Optional[int]   ,	UpperCamelCase_   :     List[Any]   ,	UpperCamelCase_   :     Optional[Any]=None):


						"""simple docstring"""




						__UpperCAmelCase						:			int												=       [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    a_  (   self   :     Any   ,	UpperCamelCase_   :     List[int]   ,	UpperCamelCase_   :     Optional[List[int]] = None):


						"""simple docstring"""




						__UpperCAmelCase						:			Optional[int]												=       [self.sep_token_id]
						__UpperCAmelCase						:			List[str]												=       [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    a_  (   self   :     str   ,	UpperCamelCase_   :     str   ,	UpperCamelCase_   :     Optional[str] = None):


						"""simple docstring"""




						__UpperCAmelCase						:			int												=       self._tokenizer.model.save(UpperCamelCase_   ,	name=UpperCamelCase_)
						return tuple(UpperCamelCase_)







'''simple docstring'''





from binascii import hexlify
from hashlib import shaaaa
from os import urandom

# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526

lowercase_									=    {
    # 1536-bit
    5: {
        "prime": int(
            "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
            + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
            + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
            + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
            + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
            + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
            + "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
            + "670C354E4ABC9804F1746C08CA237327FFFFFFFFFFFFFFFF",
            base=16,
        ),
        "generator": 2,
    },
    # 2048-bit
    14: {
        "prime": int(
            "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
            + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
            + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
            + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
            + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
            + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
            + "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
            + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
            + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
            + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
            + "15728E5A8AACAA68FFFFFFFFFFFFFFFF",
            base=16,
        ),
        "generator": 2,
    },
    # 3072-bit
    15: {
        "prime": int(
            "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
            + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
            + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
            + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
            + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
            + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
            + "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
            + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
            + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
            + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
            + "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64"
            + "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7"
            + "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B"
            + "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
            + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31"
            + "43DB5BFCE0FD108E4B82D120A93AD2CAFFFFFFFFFFFFFFFF",
            base=16,
        ),
        "generator": 2,
    },
    # 4096-bit
    16: {
        "prime": int(
            "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
            + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
            + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
            + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
            + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
            + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
            + "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
            + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
            + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
            + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
            + "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64"
            + "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7"
            + "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B"
            + "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
            + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31"
            + "43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7"
            + "88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA"
            + "2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6"
            + "287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED"
            + "1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9"
            + "93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934063199"
            + "FFFFFFFFFFFFFFFF",
            base=16,
        ),
        "generator": 2,
    },
    # 6144-bit
    17: {
        "prime": int(
            "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD129024E08"
            + "8A67CC74020BBEA63B139B22514A08798E3404DDEF9519B3CD3A431B"
            + "302B0A6DF25F14374FE1356D6D51C245E485B576625E7EC6F44C42E9"
            + "A637ED6B0BFF5CB6F406B7EDEE386BFB5A899FA5AE9F24117C4B1FE6"
            + "49286651ECE45B3DC2007CB8A163BF0598DA48361C55D39A69163FA8"
            + "FD24CF5F83655D23DCA3AD961C62F356208552BB9ED529077096966D"
            + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3BE39E772C"
            + "180E86039B2783A2EC07A28FB5C55DF06F4C52C9DE2BCBF695581718"
            + "3995497CEA956AE515D2261898FA051015728E5A8AAAC42DAD33170D"
            + "04507A33A85521ABDF1CBA64ECFB850458DBEF0A8AEA71575D060C7D"
            + "B3970F85A6E1E4C7ABF5AE8CDB0933D71E8C94E04A25619DCEE3D226"
            + "1AD2EE6BF12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
            + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB3143DB5BFC"
            + "E0FD108E4B82D120A92108011A723C12A787E6D788719A10BDBA5B26"
            + "99C327186AF4E23C1A946834B6150BDA2583E9CA2AD44CE8DBBBC2DB"
            + "04DE8EF92E8EFC141FBECAA6287C59474E6BC05D99B2964FA090C3A2"
            + "233BA186515BE7ED1F612970CEE2D7AFB81BDD762170481CD0069127"
            + "D5B05AA993B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492"
            + "36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BDF8FF9406"
            + "AD9E530EE5DB382F413001AEB06A53ED9027D831179727B0865A8918"
            + "DA3EDBEBCF9B14ED44CE6CBACED4BB1BDB7F1447E6CC254B33205151"
            + "2BD7AF426FB8F401378CD2BF5983CA01C64B92ECF032EA15D1721D03"
            + "F482D7CE6E74FEF6D55E702F46980C82B5A84031900B1C9E59E7C97F"
            + "BEC7E8F323A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA"
            + "CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE32806A1D58B"
            + "B7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55CDA56C9EC2EF29632"
            + "387FE8D76E3C0468043E8F663F4860EE12BF2D5B0B7474D6E694F91E"
            + "6DCC4024FFFFFFFFFFFFFFFF",
            base=16,
        ),
        "generator": 2,
    },
    # 8192-bit
    18: {
        "prime": int(
            "FFFFFFFFFFFFFFFFC90FDAA22168C234C4C6628B80DC1CD1"
            + "29024E088A67CC74020BBEA63B139B22514A08798E3404DD"
            + "EF9519B3CD3A431B302B0A6DF25F14374FE1356D6D51C245"
            + "E485B576625E7EC6F44C42E9A637ED6B0BFF5CB6F406B7ED"
            + "EE386BFB5A899FA5AE9F24117C4B1FE649286651ECE45B3D"
            + "C2007CB8A163BF0598DA48361C55D39A69163FA8FD24CF5F"
            + "83655D23DCA3AD961C62F356208552BB9ED529077096966D"
            + "670C354E4ABC9804F1746C08CA18217C32905E462E36CE3B"
            + "E39E772C180E86039B2783A2EC07A28FB5C55DF06F4C52C9"
            + "DE2BCBF6955817183995497CEA956AE515D2261898FA0510"
            + "15728E5A8AAAC42DAD33170D04507A33A85521ABDF1CBA64"
            + "ECFB850458DBEF0A8AEA71575D060C7DB3970F85A6E1E4C7"
            + "ABF5AE8CDB0933D71E8C94E04A25619DCEE3D2261AD2EE6B"
            + "F12FFA06D98A0864D87602733EC86A64521F2B18177B200C"
            + "BBE117577A615D6C770988C0BAD946E208E24FA074E5AB31"
            + "43DB5BFCE0FD108E4B82D120A92108011A723C12A787E6D7"
            + "88719A10BDBA5B2699C327186AF4E23C1A946834B6150BDA"
            + "2583E9CA2AD44CE8DBBBC2DB04DE8EF92E8EFC141FBECAA6"
            + "287C59474E6BC05D99B2964FA090C3A2233BA186515BE7ED"
            + "1F612970CEE2D7AFB81BDD762170481CD0069127D5B05AA9"
            + "93B4EA988D8FDDC186FFB7DC90A6C08F4DF435C934028492"
            + "36C3FAB4D27C7026C1D4DCB2602646DEC9751E763DBA37BD"
            + "F8FF9406AD9E530EE5DB382F413001AEB06A53ED9027D831"
            + "179727B0865A8918DA3EDBEBCF9B14ED44CE6CBACED4BB1B"
            + "DB7F1447E6CC254B332051512BD7AF426FB8F401378CD2BF"
            + "5983CA01C64B92ECF032EA15D1721D03F482D7CE6E74FEF6"
            + "D55E702F46980C82B5A84031900B1C9E59E7C97FBEC7E8F3"
            + "23A97A7E36CC88BE0F1D45B7FF585AC54BD407B22B4154AA"
            + "CC8F6D7EBF48E1D814CC5ED20F8037E0A79715EEF29BE328"
            + "06A1D58BB7C5DA76F550AA3D8A1FBFF0EB19CCB1A313D55C"
            + "DA56C9EC2EF29632387FE8D76E3C0468043E8F663F4860EE"
            + "12BF2D5B0B7474D6E694F91E6DBE115974A3926F12FEE5E4"
            + "38777CB6A932DF8CD8BEC4D073B931BA3BC832B68D9DD300"
            + "741FA7BF8AFC47ED2576F6936BA424663AAB639C5AE4F568"
            + "3423B4742BF1C978238F16CBE39D652DE3FDB8BEFC848AD9"
            + "22222E04A4037C0713EB57A81A23F0C73473FC646CEA306B"
            + "4BCBC8862F8385DDFA9D4B7FA2C087E879683303ED5BDD3A"
            + "062B3CF5B3A278A66D2A13F83F44F82DDF310EE074AB6A36"
            + "4597E899A0255DC164F31CC50846851DF9AB48195DED7EA1"
            + "B1D510BD7EE74D73FAF36BC31ECFA268359046F4EB879F92"
            + "4009438B481C6CD7889A002ED5EE382BC9190DA6FC026E47"
            + "9558E4475677E9AA9E3050E2765694DFC81F56E880B96E71"
            + "60C980DD98EDD3DFFFFFFFFFFFFFFFFF",
            base=16,
        ),
        "generator": 2,
    },
}






class __A     :



 '''simple docstring'''







 def __init__(self					,  A = 14			)       ->	None:


      """simple docstring"""



      if group not in primes:
           raise ValueError('''Unsupported Group'''			)
      _a           =    primes[group]['''prime''']
      _a           =    primes[group]['''generator''']

      _a           =    int(hexlify(urandom(32			)			)					,  base=16			)



 def    a__    (self			)       ->	str:


      """simple docstring"""



      return hex(self.__private_key			)[2:]



 def    a__    (self			)       ->	str:


      """simple docstring"""



      _a           =    pow(self.generator					,  self.__private_key					,  self.prime			)
      return hex(A			)[2:]



 def    a__    (self					,  A			)       ->	bool:


      """simple docstring"""



      return (
          2 <= key <= self.prime - 2
          and pow(A					,  (self.prime - 1) // 2					,  self.prime			) == 1
      )



 def    a__    (self					,  A			)       ->	str:


      """simple docstring"""



      _a           =    int(A					,  base=16			)
      if not self.is_valid_public_key(A			):
           raise ValueError('''Invalid public key'''			)
      _a           =    pow(A					,  self.__private_key					,  self.prime			)
      return shaaaa(str(A			).encode()			).hexdigest()



 @staticmethod
 def    a__    (A					,  A			)       ->	bool:


      """simple docstring"""



      return (
          2 <= remote_public_key_str <= prime - 2
          and pow(A					,  (prime - 1) // 2					,  A			) == 1
      )



 @staticmethod
 def    a__    (A					,  A					,  A = 14			)       ->	str:


      """simple docstring"""



      _a           =    int(A					,  base=16			)
      _a           =    int(A					,  base=16			)
      _a           =    primes[group]['''prime''']
      if not DiffieHellman.is_valid_public_key_static(A					,  A			):
           raise ValueError('''Invalid public key'''			)
      _a           =    pow(A					,  A					,  A			)
      return shaaaa(str(A			).encode()			).hexdigest()


if __name__ == "__main__":
  import doctest

  doctest.testmod()



