




from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments







def SCREAMING_SNAKE_CASE    (	)       ->	Optional[int]:



       """simple docstring"""

       A__							=   HfArgumentParser(lowercase_						)
       A__							=   parser.parse_args_into_dataclasses()[0]
       A__							=   TensorFlowBenchmark(args=lowercase_						)
       try:
              A__							=   parser.parse_args_into_dataclasses()[0]
       except ValueError as e:
              A__							=   '''Arg --no_{0} is no longer used, please use --no-{0} instead.'''
              A__							=   ''' '''.join(str(lowercase_						).split(''' '''						)[:-1]						)
              A__							=   ''''''
              A__							=   eval(str(lowercase_						).split(''' '''						)[-1]						)
              A__							=   []
              for arg in depreciated_args:
                     # arg[2:] removes '--'
                     if arg[2:] in TensorFlowBenchmark.deprecated_args:
                            # arg[5:] removes '--no_'
                            full_error_msg += arg_error_msg.format(arg[5:]						)
                     else:
                            wrong_args.append(lowercase_						)
              if len(lowercase_						) > 0:
                     A__							=   full_error_msg + begin_error_msg + str(lowercase_						)
              raise ValueError(lowercase_						)
       benchmark.run()


if __name__ == "__main__":
  main()








import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
  import torch

  from transformers.generation import DisjunctiveConstraint


@require_torch
class     UpperCamelCase_   (			unittest.TestCase					):

    '''simple docstring'''






    def 	SCREAMING_SNAKE_CASE							(      self				:     Dict)						->Tuple:





           '''simple docstring'''

           A__							=   [[1, 2, 4], [1, 2, 3, 4]]
           A__							=   DisjunctiveConstraint(UpperCAmelCase__)
           self.assertTrue(isinstance(dc.token_ids ,			UpperCAmelCase__))

           with self.assertRaises(UpperCAmelCase__):
                  DisjunctiveConstraint(torch.LongTensor([[1, 2, 4], [1, 2, 3]]))

           with self.assertRaises(UpperCAmelCase__):
                  DisjunctiveConstraint([torch.LongTensor([1, 2, 4]), torch.LongTensor([1, 2, 3, 4, 5])])


    def 	SCREAMING_SNAKE_CASE							(      self				:     int)						->str:





           '''simple docstring'''

           A__							=   [[1, 2], [1, 2, 3, 4]]

           with self.assertRaises(UpperCAmelCase__):
                  DisjunctiveConstraint(UpperCAmelCase__)  # fails here


    def 	SCREAMING_SNAKE_CASE							(      self				:     Any)						->str:





           '''simple docstring'''

           A__							=   [[1, 2, 3], [1, 2, 4]]

           A__							=   DisjunctiveConstraint(UpperCAmelCase__)

           A__			,							A__			,							A__							=   dc.update(1)
           A__							=   stepped is True and completed is False and reset is False
           self.assertTrue(UpperCAmelCase__)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.current_seq == [1])

           A__			,							A__			,							A__							=   dc.update(2)
           A__							=   stepped is True and completed is False and reset is False
           self.assertTrue(UpperCAmelCase__)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.current_seq == [1, 2])

           A__			,							A__			,							A__							=   dc.update(3)
           A__							=   stepped is True and completed is True and reset is False
           self.assertTrue(UpperCAmelCase__)
           self.assertTrue(dc.completed)  # Completed!
           self.assertTrue(dc.current_seq == [1, 2, 3])





    def 	SCREAMING_SNAKE_CASE							(      self				:     Optional[Any])						->Tuple:





           '''simple docstring'''

           A__							=   [[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

           A__							=   DisjunctiveConstraint(UpperCAmelCase__)

           A__			,							A__			,							A__							=   dc.update(1)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.current_seq == [1])

           A__			,							A__			,							A__							=   dc.update(2)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.current_seq == [1, 2])

           A__			,							A__			,							A__							=   dc.update(4)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.current_seq == [1, 2, 4])

           A__			,							A__			,							A__							=   dc.update(5)
           self.assertTrue(dc.completed)  # Completed!
           self.assertTrue(dc.current_seq == [1, 2, 4, 5])

           dc.reset()

           A__			,							A__			,							A__							=   dc.update(1)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.remaining() == 3)
           self.assertTrue(dc.current_seq == [1])

           A__			,							A__			,							A__							=   dc.update(2)
           self.assertTrue(not dc.completed)
           self.assertTrue(dc.remaining() == 2)
           self.assertTrue(dc.current_seq == [1, 2])

           A__			,							A__			,							A__							=   dc.update(5)
           self.assertTrue(dc.completed)  # Completed!
           self.assertTrue(dc.remaining() == 0)
           self.assertTrue(dc.current_seq == [1, 2, 5])


