




from __future__ import annotations




class 			UpperCAmelCase_      :




							'''simple docstring'''



							def __init__(					self       :	Optional[int]       ,     a       :	int = 0			)			->					str:
										SCREAMING_SNAKE_CASE           =					key





							def    _UpperCAmelCase     (					self       :	Tuple       ,     a       :	str       ,     a       :	int			)			->					list[str]:
										assert isinstance(a       ,     a			) and isinstance(a       ,     a			)

										SCREAMING_SNAKE_CASE           =					key or self.__key or 1

										# make sure key is an appropriate size
										key %= 255

										return [chr(ord(a			) ^ key			) for ch in content]





							def    _UpperCAmelCase     (					self       :	Union[str, Any]       ,     a       :	str       ,     a       :	int			)			->					list[str]:
										assert isinstance(a       ,     a			) and isinstance(a       ,     a			)

										SCREAMING_SNAKE_CASE           =					key or self.__key or 1

										# make sure key is an appropriate size
										key %= 255

										return [chr(ord(a			) ^ key			) for ch in content]





							def    _UpperCAmelCase     (					self       :	Union[str, Any]       ,     a       :	str       ,     a       :	int = 0			)			->					str:
										assert isinstance(a       ,     a			) and isinstance(a       ,     a			)

										SCREAMING_SNAKE_CASE           =					key or self.__key or 1

										# make sure key can be any size
										while key > 255:
													key -= 255

										# This will be returned
										SCREAMING_SNAKE_CASE           =					""""""

										for ch in content:
													ans += chr(ord(a			) ^ key			)

										return ans





							def    _UpperCAmelCase     (					self       :	Dict       ,     a       :	str       ,     a       :	int = 0			)			->					str:
										assert isinstance(a       ,     a			) and isinstance(a       ,     a			)

										SCREAMING_SNAKE_CASE           =					key or self.__key or 1

										# make sure key can be any size
										while key > 255:
													key -= 255

										# This will be returned
										SCREAMING_SNAKE_CASE           =					""""""

										for ch in content:
													ans += chr(ord(a			) ^ key			)

										return ans





							def    _UpperCAmelCase     (					self       :	Optional[int]       ,     a       :	str       ,     a       :	int = 0			)			->					bool:
										assert isinstance(a       ,     a			) and isinstance(a       ,     a			)

										try:
													with open(a			) as fin, open("""encrypt.out"""       ,     """w+"""			) as fout:
																# actual encrypt-process
																for line in fin:
																			fout.write(self.encrypt_string(a       ,     a			)			)

										except OSError:
													return False

										return True







							def    _UpperCAmelCase     (					self       :	Dict       ,     a       :	str       ,     a       :	int			)			->					bool:
										assert isinstance(a       ,     a			) and isinstance(a       ,     a			)

										try:
													with open(a			) as fin, open("""decrypt.out"""       ,     """w+"""			) as fout:
																# actual encrypt-process
																for line in fin:
																			fout.write(self.decrypt_string(a       ,     a			)			)

										except OSError:
													return False

										return True


# Tests
# crypt = XORCipher()
# key = 67

# # test encrypt
# print(crypt.encrypt("hallo welt",key))
# # test decrypt
# print(crypt.decrypt(crypt.encrypt("hallo welt",key), key))

# # test encrypt_string
# print(crypt.encrypt_string("hallo welt",key))

# # test decrypt_string
# print(crypt.decrypt_string(crypt.encrypt_string("hallo welt",key),key))

# if (crypt.encrypt_file("test.txt",key)):
#       print("encrypt successful")
# else:
#       print("encrypt unsuccessful")

# if (crypt.decrypt_file("encrypt.out",key)):
#       print("decrypt successful")
# else:
#       print("decrypt unsuccessful")












import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
		from transformers import AutoModelForSeqaSeqLM, AutoTokenizer




@require_torch
@require_sentencepiece
@require_tokenizers
class 			UpperCAmelCase_      (   unittest.TestCase       ):




							'''simple docstring'''



							@slow
							def    _UpperCAmelCase     (					self       :	Optional[int]			)			->					Tuple:
										SCREAMING_SNAKE_CASE           =					AutoModelForSeqaSeqLM.from_pretrained("""google/mt5-small"""       ,     return_dict=a			).to(a			)
										SCREAMING_SNAKE_CASE           =					AutoTokenizer.from_pretrained("""google/mt5-small"""			)

										SCREAMING_SNAKE_CASE           =					tokenizer("""Hello there"""       ,     return_tensors="""pt"""			).input_ids
										SCREAMING_SNAKE_CASE           =					tokenizer("""Hi I am"""       ,     return_tensors="""pt"""			).input_ids

										SCREAMING_SNAKE_CASE           =					model(input_ids.to(a			)       ,     labels=labels.to(a			)			).loss
										SCREAMING_SNAKE_CASE           =					-(labels.shape[-1] * loss.item())

										SCREAMING_SNAKE_CASE           =					-84.9127
										self.assertTrue(abs(mtf_score - EXPECTED_SCORE			) < 1E-4			)






