'''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  __magic_name__  (		unittest.TestCase    ):





   """simple docstring"""




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



    """simple docstring"""



    _UpperCamelCase:     str							= 3
    _UpperCamelCase:     int							= 250

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



   def   lowerCAmelCase						(	self					:  Optional[Any]							):



    """simple docstring"""



    _UpperCamelCase:     Optional[int]							= self._get_tensors(5							)

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

    self.assertFalse(criteria(_lowercase		,  _lowercase							)							)

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

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



   def   lowerCAmelCase						(	self					:  List[str]							):



    """simple docstring"""



    _UpperCamelCase:     List[Any]							= MaxLengthCriteria(max_length=10							)

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

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

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



   def   lowerCAmelCase						(	self					:  Optional[int]							):



    """simple docstring"""



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

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

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

    _UpperCamelCase:     Optional[int]							= self._get_tensors(10							)
    self.assertTrue(criteria(_lowercase		,  _lowercase							)							)

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



   def   lowerCAmelCase						(	self					:  Optional[int]							):



    """simple docstring"""



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

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

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



   def   lowerCAmelCase						(	self					:  Any							):



    """simple docstring"""



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

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

    _UpperCamelCase:     int							= validate_stopping_criteria(StoppingCriteriaList()		,  11							)

    self.assertEqual(len(_lowercase							)		,  1							)
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

UpperCAmelCase_			    =							'''2.13.1'''

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse('''3.7'''):
  raise ImportWarning(
      '''To use `datasets`, Python>=3.7 is required, and the current version of Python doesn\'t match this condition.'''
  )

if version.parse(pyarrow.__version__).major < 8:
  raise ImportWarning(
      '''To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn\'t match this condition.\n'''
      '''If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`.'''
  )

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

UpperCAmelCase_			    =							concatenate_datasets
UpperCAmelCase_			    =							DownloadConfig
UpperCAmelCase_			    =							DownloadManager
UpperCAmelCase_			    =							DownloadMode
UpperCAmelCase_			    =							DownloadConfig
UpperCAmelCase_			    =							DownloadMode
UpperCAmelCase_			    =							DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager