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 			__magic_name__	(		unittest.TestCase     ):





   """simple docstring"""




   def 	lowerCAmelCase    (						self       :	Optional[Any]		,	_lowercase       :	str				):



    """simple docstring"""



    _UpperCamelCase:  str    						=			3
    _UpperCamelCase:  str    						=			250

    _UpperCamelCase:  Optional[int]    						=			ids_tensor((batch_size, length)		,	_lowercase				)
    _UpperCamelCase:  Any    						=			torch.ones((batch_size, length)		,	device=_lowercase		,	dtype=torch.float				) / length
    return input_ids, scores



   def 	lowerCAmelCase    (						self       :	str				):



    """simple docstring"""



    _UpperCamelCase						,				_UpperCamelCase:  Union[str, Any]    						=			self._get_tensors(5				)

    _UpperCamelCase:  Union[str, Any]    						=			StoppingCriteriaList(
        [
            MaxLengthCriteria(max_length=10				),
            MaxTimeCriteria(max_time=0.1				),
        ]				)

    self.assertFalse(criteria(_lowercase		,	_lowercase				)				)

    _UpperCamelCase						,				_UpperCamelCase:  Optional[Any]    						=			self._get_tensors(9				)
    self.assertFalse(criteria(_lowercase		,	_lowercase				)				)

    _UpperCamelCase						,				_UpperCamelCase:  Any    						=			self._get_tensors(10				)
    self.assertTrue(criteria(_lowercase		,	_lowercase				)				)



   def 	lowerCAmelCase    (						self       :	str				):



    """simple docstring"""



    _UpperCamelCase:  Dict    						=			MaxLengthCriteria(max_length=10				)

    _UpperCamelCase						,				_UpperCamelCase:  List[str]    						=			self._get_tensors(5				)
    self.assertFalse(criteria(_lowercase		,	_lowercase				)				)

    _UpperCamelCase						,				_UpperCamelCase:  Dict    						=			self._get_tensors(9				)
    self.assertFalse(criteria(_lowercase		,	_lowercase				)				)

    _UpperCamelCase						,				_UpperCamelCase:  List[str]    						=			self._get_tensors(10				)
    self.assertTrue(criteria(_lowercase		,	_lowercase				)				)



   def 	lowerCAmelCase    (						self       :	Dict				):



    """simple docstring"""



    _UpperCamelCase:  Optional[Any]    						=			MaxNewTokensCriteria(start_length=5		,	max_new_tokens=5				)

    _UpperCamelCase						,				_UpperCamelCase:  List[Any]    						=			self._get_tensors(5				)
    self.assertFalse(criteria(_lowercase		,	_lowercase				)				)

    _UpperCamelCase						,				_UpperCamelCase:  str    						=			self._get_tensors(9				)
    self.assertFalse(criteria(_lowercase		,	_lowercase				)				)

    _UpperCamelCase						,				_UpperCamelCase:  Union[str, Any]    						=			self._get_tensors(10				)
    self.assertTrue(criteria(_lowercase		,	_lowercase				)				)

    _UpperCamelCase:  Dict    						=			StoppingCriteriaList([criteria]				)
    self.assertEqual(criteria_list.max_length		,	10				)



   def 	lowerCAmelCase    (						self       :	List[Any]				):



    """simple docstring"""



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

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

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



   def 	lowerCAmelCase    (						self       :	int				):



    """simple docstring"""



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

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

    _UpperCamelCase:  List[Any]    						=			validate_stopping_criteria(StoppingCriteriaList()		,	11				)

    self.assertEqual(len(_lowercase				)		,	1				)
UpperCAmelCase_           =				'''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

UpperCAmelCase_           =				[{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
UpperCAmelCase_           =				{
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}