




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        SCREAMING_SNAKE_CASE							(			self      :	Any					, UpperCAmelCase__      :	List[Any])						->Union[str, Any]:





           '''simple docstring'''

           A__       =    3
           A__       =    250

           A__       =    ids_tensor((batch_size, length)					, UpperCAmelCase__)
           A__       =    torch.ones((batch_size, length)					, device=UpperCAmelCase__					, dtype=torch.float) / length
           return input_ids, scores


    def        SCREAMING_SNAKE_CASE							(			self      :	Union[str, Any])						->Dict:





           '''simple docstring'''

           A__ ,							A__       =    self._get_tensors(5)

           A__       =    StoppingCriteriaList(
               [
                   MaxLengthCriteria(max_length=10),
                   MaxTimeCriteria(max_time=0.1),
               ])

           self.assertFalse(criteria(UpperCAmelCase__					, UpperCAmelCase__))

           A__ ,							A__       =    self._get_tensors(9)
           self.assertFalse(criteria(UpperCAmelCase__					, UpperCAmelCase__))

           A__ ,							A__       =    self._get_tensors(10)
           self.assertTrue(criteria(UpperCAmelCase__					, UpperCAmelCase__))


    def        SCREAMING_SNAKE_CASE							(			self      :	Dict)						->int:





           '''simple docstring'''

           A__       =    MaxLengthCriteria(max_length=10)

           A__ ,							A__       =    self._get_tensors(5)
           self.assertFalse(criteria(UpperCAmelCase__					, UpperCAmelCase__))

           A__ ,							A__       =    self._get_tensors(9)
           self.assertFalse(criteria(UpperCAmelCase__					, UpperCAmelCase__))

           A__ ,							A__       =    self._get_tensors(10)
           self.assertTrue(criteria(UpperCAmelCase__					, UpperCAmelCase__))


    def        SCREAMING_SNAKE_CASE							(			self      :	Any)						->Union[str, Any]:





           '''simple docstring'''

           A__       =    MaxNewTokensCriteria(start_length=5					, max_new_tokens=5)

           A__ ,							A__       =    self._get_tensors(5)
           self.assertFalse(criteria(UpperCAmelCase__					, UpperCAmelCase__))

           A__ ,							A__       =    self._get_tensors(9)
           self.assertFalse(criteria(UpperCAmelCase__					, UpperCAmelCase__))

           A__ ,							A__       =    self._get_tensors(10)
           self.assertTrue(criteria(UpperCAmelCase__					, UpperCAmelCase__))

           A__       =    StoppingCriteriaList([criteria])
           self.assertEqual(criteria_list.max_length					, 10)


    def        SCREAMING_SNAKE_CASE							(			self      :	str)						->Optional[int]:





           '''simple docstring'''

           A__ ,							A__       =    self._get_tensors(5)

           A__       =    MaxTimeCriteria(max_time=0.1)
           self.assertFalse(criteria(UpperCAmelCase__					, UpperCAmelCase__))

           A__       =    MaxTimeCriteria(max_time=0.1					, initial_timestamp=time.time() - 0.2)
           self.assertTrue(criteria(UpperCAmelCase__					, UpperCAmelCase__))





    def        SCREAMING_SNAKE_CASE							(			self      :	Any)						->Dict:





           '''simple docstring'''

           validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10)])					, 10)

           with self.assertWarns(UpperCAmelCase__):
                  validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10)])					, 11)

           A__       =    validate_stopping_criteria(StoppingCriteriaList()					, 11)

           self.assertEqual(len(UpperCAmelCase__)					, 1)








def SCREAMING_SNAKE_CASE				(       lowercase_						)   ->       "list[int]":



       """simple docstring"""

       if upper_limit < 0:
              raise ValueError('''Limit for the Catalan sequence must be ≥ 0'''						)

       A__       =    [0] * (upper_limit + 1)

       # Base case: C(0) = C(1) = 1
       A__       =    1
       if upper_limit > 0:
              A__       =    1

       # Recurrence relation: C(i) = sum(C(j).C(i-j-1)), from j = 0 to i
       for i in range(2 ,				upper_limit + 1						):
              for j in range(lowercase_						):
                     catalan_list[i] += catalan_list[j] * catalan_list[i - j - 1]

       return catalan_list


if __name__ == "__main__":
  print("""\n********* Catalan Numbers Using Dynamic Programming ************\n""")
  print("""\n*** Enter -1 at any time to quit ***""")
  print("""\nEnter the upper limit (≥ 0) for the Catalan number sequence: """, end="""""")
  try:
    while True:
      _lowerCamelCase	:		List[Any]							       =   int(input().strip())
      if N < 0:
        print("""\n********* Goodbye!! ************""")
        break
      else:
        print(F'''The Catalan numbers from 0 through {N} are:''')
        print(catalan_numbers(N))
        print("""Try another upper limit for the sequence: """, end="""""")
  except (NameError, ValueError):
    print("""\n********* Invalid input, goodbye! ************\n""")

  import doctest

  doctest.testmod()


