"""simple docstring"""



import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE__:int			=	"""▁"""

SCREAMING_SNAKE_CASE__:str			=	get_tests_dir("""fixtures/test_sentencepiece.model""")






@require_sentencepiece
class 				snake_case__     (   snake_case_,		unittest.TestCase   ):
 _snake_case   :			str           =		BertGenerationTokenizer
 _snake_case   :			List[str]           =		False
 _snake_case   :			str           =		True


 def 		a__ (				self		):
        super().setUp()

        __a     				=  BertGenerationTokenizer(lowerCamelCase  ,						keep_accents=lowerCamelCase		)
        tokenizer.save_pretrained(self.tmpdirname		)


 def 		a__ (				self		):
        __a     				=  "<s>"
        __a     				=  1

        self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCamelCase		)  ,						lowerCamelCase		)
        self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCamelCase		)  ,						lowerCamelCase		)


 def 		a__ (				self		):
        __a     				=  list(self.get_tokenizer().get_vocab().keys()		)

        self.assertEqual(vocab_keys[0]  ,						"<unk>"		)
        self.assertEqual(vocab_keys[1]  ,						"<s>"		)
        self.assertEqual(vocab_keys[-1]  ,						"<pad>"		)
        self.assertEqual(len(lowerCamelCase		)  ,						1002		)


 def 		a__ (				self		):
        self.assertEqual(self.get_tokenizer().vocab_size  ,						1000		)


 def 		a__ (				self		):
        __a     				=  BertGenerationTokenizer(lowerCamelCase  ,						keep_accents=lowerCamelCase		)

        __a     				=  tokenizer.tokenize("This is a test"		)
        self.assertListEqual(lowerCamelCase  ,						["▁This", "▁is", "▁a", "▁t", "est"]		)

        self.assertListEqual(
            tokenizer.convert_tokens_to_ids(lowerCamelCase		)  ,						[285, 46, 10, 170, 382]  ,						)

        __a     				=  tokenizer.tokenize("I was born in 92000, and this is falsé."		)
        self.assertListEqual(
            lowerCamelCase  ,						[
                SPIECE_UNDERLINE + "I",
                SPIECE_UNDERLINE + "was",
                SPIECE_UNDERLINE + "b",
                "or",
                "n",
                SPIECE_UNDERLINE + "in",
                SPIECE_UNDERLINE + "",
                "9",
                "2",
                "0",
                "0",
                "0",
                ",",
                SPIECE_UNDERLINE + "and",
                SPIECE_UNDERLINE + "this",
                SPIECE_UNDERLINE + "is",
                SPIECE_UNDERLINE + "f",
                "al",
                "s",
                "é",
                ".",
            ]  ,						)
        __a     				=  tokenizer.convert_tokens_to_ids(lowerCamelCase		)
        self.assertListEqual(
            lowerCamelCase  ,						[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]  ,						)

        __a     				=  tokenizer.convert_ids_to_tokens(lowerCamelCase		)
        self.assertListEqual(
            lowerCamelCase  ,						[
                SPIECE_UNDERLINE + "I",
                SPIECE_UNDERLINE + "was",
                SPIECE_UNDERLINE + "b",
                "or",
                "n",
                SPIECE_UNDERLINE + "in",
                SPIECE_UNDERLINE + "",
                "<unk>",
                "2",
                "0",
                "0",
                "0",
                ",",
                SPIECE_UNDERLINE + "and",
                SPIECE_UNDERLINE + "this",
                SPIECE_UNDERLINE + "is",
                SPIECE_UNDERLINE + "f",
                "al",
                "s",
                "<unk>",
                ".",
            ]  ,						)


 @cached_property
 def 		a__ (				self		):
        return BertGenerationTokenizer.from_pretrained("google/bert_for_seq_generation_L-24_bbc_encoder"		)


 @slow
 def 		a__ (				self		):
        __a     				=  "Hello World!"
        __a     				=  [18536, 2260, 101]

        self.assertListEqual(lowerCamelCase  ,						self.big_tokenizer.encode(lowerCamelCase		)		)


 @slow
 def 		a__ (				self		):
        __a     				=  (
            "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
            " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
        )
        __a     				=  [
            871,
            419,
            358,
            946,
            991,
            2521,
            452,
            358,
            1357,
            387,
            7751,
            3536,
            112,
            985,
            456,
            126,
            865,
            938,
            5400,
            5734,
            458,
            1368,
            467,
            786,
            2462,
            5246,
            1159,
            633,
            865,
            4519,
            457,
            582,
            852,
            2557,
            427,
            916,
            508,
            405,
            34324,
            497,
            391,
            408,
            11342,
            1244,
            385,
            100,
            938,
            985,
            456,
            574,
            362,
            12597,
            3200,
            3129,
            1172,
        ]

        self.assertListEqual(lowerCamelCase  ,						self.big_tokenizer.encode(lowerCamelCase		)		)


 @require_torch
 @slow
 def 		a__ (				self		):
        import torch

        from transformers import BertGenerationConfig, BertGenerationEncoder

        # Build sequence
        __a     				=  list(self.big_tokenizer.get_vocab().keys()		)[:10]
        __a     				=  " ".join(lowerCamelCase		)
        __a     				=  self.big_tokenizer.encode_plus(lowerCamelCase  ,						return_tensors="pt"  ,						return_token_type_ids=lowerCamelCase		)
        __a     				=  self.big_tokenizer.batch_encode_plus(
            [sequence + " " + sequence]  ,						return_tensors="pt"  ,						return_token_type_ids=lowerCamelCase		)

        __a     				=  BertGenerationConfig()
        __a     				=  BertGenerationEncoder(lowerCamelCase		)

        assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

        with torch.no_grad():
               model(**lowerCamelCase		)
               model(**lowerCamelCase		)






 @slow
 def 		a__ (				self		):
        # fmt: off
        __a     				=  {"input_ids": [[39286, 458, 36335, 2001, 456, 13073, 13266, 455, 113, 7746, 1741, 11157, 391, 13073, 13266, 455, 113, 3967, 35412, 113, 4936, 109, 3870, 2377, 113, 30084, 45720, 458, 134, 17496, 112, 503, 11672, 113, 118, 112, 5665, 13347, 38687, 112, 1496, 31389, 112, 3268, 47264, 134, 962, 112, 16377, 8035, 23130, 430, 12169, 15518, 28592, 458, 146, 41697, 109, 391, 12169, 15518, 16689, 458, 146, 41358, 109, 452, 726, 4034, 111, 763, 35412, 5082, 388, 1903, 111, 9051, 391, 2870, 48918, 1900, 1123, 550, 998, 112, 9586, 15985, 455, 391, 410, 22955, 37636, 114], [448, 17496, 419, 3663, 385, 763, 113, 27533, 2870, 3283, 13043, 1639, 24713, 523, 656, 24013, 18550, 2521, 517, 27014, 21244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 11786, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [484, 2169, 7687, 21932, 18146, 726, 363, 17032, 3391, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
        # fmt: on

        self.tokenizer_integration_test_util(
            expected_encoding=lowerCamelCase  ,						model_name="google/bert_for_seq_generation_L-24_bbc_encoder"  ,						revision="c817d1fd1be2ffa69431227a1fe320544943d4db"  ,						)

"""simple docstring"""



import os
import random
import sys

from . import cryptomath_module as cryptomath
from . import rabin_miller

SCREAMING_SNAKE_CASE__:List[str]			=	3



def 					_lowerCamelCase(					a							):
       print("Generating primitive root of p"							)
       while True:
              __a     				=  random.randrange(3 ,  a							)
              if pow(a ,  2 ,  a							) == 1:
                     continue
              if pow(a ,  a ,  a							) == 1:
                     continue
              return g



def 					_lowerCamelCase(					a							):
       print("Generating prime p..."							)
       __a     				=  rabin_miller.generate_large_prime(a							)  # select large prime number.
       __a     				=  primitive_root(a							)  # one primitive root on modulo p.
       __a     				=  random.randrange(3 ,  a							)  # private_key -> have to be greater than 2 for safety.
       __a     				=  cryptomath.find_mod_inverse(pow(a ,  a ,  a							) ,  a							)

       __a     				=  (key_size, e_a, e_a, p)
       __a     				=  (key_size, d)

       return public_key, private_key



def 					_lowerCamelCase(					a ,  a							):
       if os.path.exists(F"{name}_pubkey.txt"							) or os.path.exists(F"{name}_privkey.txt"							):
              print("\nWARNING:"							)
              print(
                  F"\"{name}_pubkey.txt\" or \"{name}_privkey.txt\" already exists. \n"
                  "Use a different name or delete these files and re-run this program."							)
              sys.exit()

       __a				, __a     				=  generate_key(a							)
       print(F"\nWriting public key to file {name}_pubkey.txt..."							)
       with open(F"{name}_pubkey.txt" ,  "w"							) as fo:
              fo.write(F"{public_key[0]},{public_key[1]},{public_key[2]},{public_key[3]}"							)

       print(F"Writing private key to file {name}_privkey.txt..."							)
       with open(F"{name}_privkey.txt" ,  "w"							) as fo:
              fo.write(F"{private_key[0]},{private_key[1]}"							)



def 					_lowerCamelCase(					):
       print("Making key files..."							)
       make_key_files("elgamal" ,  2_0_4_8							)
       print("Key files generation successful"							)


if __name__ == "__main__":
   main()
