



'''simple docstring'''




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 UpperCamelCase__					(							self     : int							,     lowerCAmelCase__     : Union[str, Any]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		str           =		3
					__SCREAMING_SNAKE_CASE       :		Tuple           =		2_5_0

					__SCREAMING_SNAKE_CASE       :		Tuple           =		ids_tensor((batch_size, length)							,     lowerCAmelCase__						)
					__SCREAMING_SNAKE_CASE       :		str           =		torch.ones((batch_size, length)							,     device=lowerCAmelCase__							,     dtype=torch.float						) / length
					return input_ids, scores

			def UpperCamelCase__					(							self     : Union[str, Any]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		Optional[Any]           =		self._get_tensors(5						)

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

					self.assertFalse(criteria(lowerCAmelCase__							,     lowerCAmelCase__						)						)

					__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		List[Any]           =		self._get_tensors(9						)
					self.assertFalse(criteria(lowerCAmelCase__							,     lowerCAmelCase__						)						)

					__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		str           =		self._get_tensors(1_0						)
					self.assertTrue(criteria(lowerCAmelCase__							,     lowerCAmelCase__						)						)

			def UpperCamelCase__					(							self     : str						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Dict           =		MaxLengthCriteria(max_length=1_0						)

					__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		List[Any]           =		self._get_tensors(5						)
					self.assertFalse(criteria(lowerCAmelCase__							,     lowerCAmelCase__						)						)

					__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		Union[str, Any]           =		self._get_tensors(9						)
					self.assertFalse(criteria(lowerCAmelCase__							,     lowerCAmelCase__						)						)

					__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		Union[str, Any]           =		self._get_tensors(1_0						)
					self.assertTrue(criteria(lowerCAmelCase__							,     lowerCAmelCase__						)						)

			def UpperCamelCase__					(							self     : List[Any]						):





					"""simple docstring"""






					__SCREAMING_SNAKE_CASE       :		Any           =		MaxNewTokensCriteria(start_length=5							,     max_new_tokens=5						)

					__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		int           =		self._get_tensors(5						)
					self.assertFalse(criteria(lowerCAmelCase__							,     lowerCAmelCase__						)						)

					__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		Tuple           =		self._get_tensors(9						)
					self.assertFalse(criteria(lowerCAmelCase__							,     lowerCAmelCase__						)						)

					__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		int           =		self._get_tensors(1_0						)
					self.assertTrue(criteria(lowerCAmelCase__							,     lowerCAmelCase__						)						)

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

			def UpperCamelCase__					(							self     : Dict						):





					"""simple docstring"""






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

					__SCREAMING_SNAKE_CASE       :		List[str]           =		MaxTimeCriteria(max_time=0.1						)
					self.assertFalse(criteria(lowerCAmelCase__							,     lowerCAmelCase__						)						)

					__SCREAMING_SNAKE_CASE       :		Optional[int]           =		MaxTimeCriteria(max_time=0.1							,     initial_timestamp=time.time() - 0.2						)
					self.assertTrue(criteria(lowerCAmelCase__							,     lowerCAmelCase__						)						)



			def UpperCamelCase__					(							self     : List[Any]						):





					"""simple docstring"""






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

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

					__SCREAMING_SNAKE_CASE       :		Any           =		validate_stopping_criteria(StoppingCriteriaList()							,     1_1						)

					self.assertEqual(len(lowerCAmelCase__						)							,     1						)




'''simple docstring'''




def 				lowerCAmelCase_   (	_lowerCamelCase:   int					):
		__SCREAMING_SNAKE_CASE       :		str           =		int(_lowerCamelCase					)
		if n_element < 1:
				__SCREAMING_SNAKE_CASE       :		List[str]           =		ValueError("""a should be a positive number"""					)
				raise my_error

		__SCREAMING_SNAKE_CASE       :		List[Any]           =		[1]
		__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       ,						__SCREAMING_SNAKE_CASE       :		Optional[int]           =		(0, 0, 0)
		__SCREAMING_SNAKE_CASE       :		List[str]           =		1
		while index < n_element:
				while hamming_list[i] * 2 <= hamming_list[-1]:
						i += 1
				while hamming_list[j] * 3 <= hamming_list[-1]:
						j += 1
				while hamming_list[k] * 5 <= hamming_list[-1]:
						k += 1
				hamming_list.append(
				    min(hamming_list[i] * 2       ,      hamming_list[j] * 3       ,      hamming_list[k] * 5					)					)
				index += 1
		return hamming_list


if __name__ == "__main__":
						UpperCamelCase__       :	Optional[Any]    = input('''Enter the last number (nth term) of the Hamming Number Series: ''')
						print('''Formula of Hamming Number Series => 2^i * 3^j * 5^k''')
						UpperCamelCase__       :	List[str]    = hamming(int(n))
						print('''-----------------------------------------------------''')
						print(f"The list with nth numbers is: {hamming_numbers}")
						print('''-----------------------------------------------------''')