


import time
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device

from ..test_modeling_common import ids_tensor


if is_torch_available():
	import torch

	from transformers.generation import (
	    MaxLengthCriteria,
	    MaxNewTokensCriteria,
	    MaxTimeCriteria,
	    StoppingCriteriaList,
	    validate_stopping_criteria,
	)





@require_torch
class UpperCAmelCase						( unittest.TestCase  ):


				'''simple docstring'''






				def   lowerCAmelCase_       (						self		,     lowercase ):



						"""simple docstring"""





						A_		:    Union[str, Any]         =				3
						A_		:    Optional[Any]         =				2_5_0

						A_		:    str         =				ids_tensor((batch_size, length)		,     _lowerCamelCase )
						A_		:    Any         =				torch.ones((batch_size, length)		,     device=_lowerCamelCase		,     dtype=torch.float ) / length
						return input_ids, scores
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_       ,      A_		:    int         =				self._get_tensors(5 )

						A_		:    str         =				StoppingCriteriaList(
						    [
						        MaxLengthCriteria(max_length=1_0 ),
						        MaxTimeCriteria(max_time=0.1 ),
						    ] )

						self.assertFalse(criteria(_lowerCamelCase		,     _lowerCamelCase ) )

						A_       ,      A_		:    Optional[Any]         =				self._get_tensors(9 )
						self.assertFalse(criteria(_lowerCamelCase		,     _lowerCamelCase ) )

						A_       ,      A_		:    Dict         =				self._get_tensors(1_0 )
						self.assertTrue(criteria(_lowerCamelCase		,     _lowerCamelCase ) )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    Optional[int]         =				MaxLengthCriteria(max_length=1_0 )

						A_       ,      A_		:    Optional[int]         =				self._get_tensors(5 )
						self.assertFalse(criteria(_lowerCamelCase		,     _lowerCamelCase ) )

						A_       ,      A_		:    List[Any]         =				self._get_tensors(9 )
						self.assertFalse(criteria(_lowerCamelCase		,     _lowerCamelCase ) )

						A_       ,      A_		:    str         =				self._get_tensors(1_0 )
						self.assertTrue(criteria(_lowerCamelCase		,     _lowerCamelCase ) )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_		:    int         =				MaxNewTokensCriteria(start_length=5		,     max_new_tokens=5 )

						A_       ,      A_		:    Tuple         =				self._get_tensors(5 )
						self.assertFalse(criteria(_lowerCamelCase		,     _lowerCamelCase ) )

						A_       ,      A_		:    List[Any]         =				self._get_tensors(9 )
						self.assertFalse(criteria(_lowerCamelCase		,     _lowerCamelCase ) )

						A_       ,      A_		:    Optional[Any]         =				self._get_tensors(1_0 )
						self.assertTrue(criteria(_lowerCamelCase		,     _lowerCamelCase ) )

						A_		:    Optional[int]         =				StoppingCriteriaList([criteria] )
						self.assertEqual(criteria_list.max_length		,     1_0 )
				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						A_       ,      A_		:    List[Any]         =				self._get_tensors(5 )

						A_		:    Dict         =				MaxTimeCriteria(max_time=0.1 )
						self.assertFalse(criteria(_lowerCamelCase		,     _lowerCamelCase ) )

						A_		:    Any         =				MaxTimeCriteria(max_time=0.1		,     initial_timestamp=time.time() - 0.2 )
						self.assertTrue(criteria(_lowerCamelCase		,     _lowerCamelCase ) )







				def   lowerCAmelCase_       (						self ):



						"""simple docstring"""





						validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(1_0 )] )		,     1_0 )

						with self.assertWarns(_lowerCamelCase ):
								validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(1_0 )] )		,     1_1 )

						A_		:    Optional[int]         =				validate_stopping_criteria(StoppingCriteriaList()		,     1_1 )

						self.assertEqual(len(_lowerCamelCase )		,     1 )







_UpperCAmelCase            =		"""ABCDEFGHIJKLMNOPQRSTUVWXYZ"""




def     UpperCamelCase						(	):
		'''simple docstring'''




		A_		:    Tuple         =				input('Enter message: '     )
		A_		:    int         =				input('Enter key [alphanumeric]: '     )
		A_		:    Optional[Any]         =				input('Encrypt/Decrypt [e/d]: '     )

		if mode.lower().startswith('e'     ):
				A_		:    List[Any]         =				'encrypt'
				A_		:    int         =				encrypt_message(__lowercase						,__lowercase     )
		elif mode.lower().startswith('d'     ):
				A_		:    Optional[Any]         =				'decrypt'
				A_		:    Dict         =				decrypt_message(__lowercase						,__lowercase     )

		print(f'''\n{mode.title()}ed message:'''     )
		print(__lowercase     )




def     UpperCamelCase						(	__lowercase						:			str						,__lowercase						:			str     ):
		'''simple docstring'''




		return translate_message(__lowercase						,__lowercase						,'encrypt'     )




def     UpperCamelCase						(	__lowercase						:			str						,__lowercase						:			str     ):
		'''simple docstring'''




		return translate_message(__lowercase						,__lowercase						,'decrypt'     )




def     UpperCamelCase						(	__lowercase						:			str						,__lowercase						:			str						,__lowercase						:			str     ):
		'''simple docstring'''




		A_		:    Tuple         =				[]
		A_		:    str         =				0
		A_		:    Optional[int]         =				key.upper()

		for symbol in message:
				A_		:    Optional[Any]         =				LETTERS.find(symbol.upper()     )
				if num != -1:
						if mode == "encrypt":
								num += LETTERS.find(key[key_index]     )
						elif mode == "decrypt":
								num -= LETTERS.find(key[key_index]     )

						num %= len(__lowercase     )

						if symbol.isupper():
								translated.append(LETTERS[num]     )
						elif symbol.islower():
								translated.append(LETTERS[num].lower()     )

						key_index += 1
						if key_index == len(__lowercase     ):
								A_		:    str         =				0
				else:
						translated.append(__lowercase     )
		return "".join(__lowercase     )


if __name__ == "__main__":
	main()






