import unittest

from transformers import load_tool

from .test_tools_common import ToolTesterMixin



class  SCREAMING_SNAKE_CASE_ (					unittest.TestCase   ,						lowerCAmelCase_			):
  '''simple docstring'''


  def 		SCREAMING_SNAKE_CASE_		(				self    :					Union[str, Any]     )    ->				Optional[Any]:
         A						:     List[str]         =load_tool('text-classification'     )
         self.tool.setup()
         A						:     Tuple         =load_tool('text-classification'      ,	remote=SCREAMING_SNAKE_CASE__     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[Any]     )    ->				str:
         A						:     Optional[int]         =self.tool('That\'s quite cool'      ,	['positive', 'negative']     )
         self.assertEqual(SCREAMING_SNAKE_CASE__      ,	'positive'     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[str]     )    ->				Optional[Any]:
         A						:     Optional[int]         =self.remote_tool('That\'s quite cool'      ,	['positive', 'negative']     )
         self.assertEqual(SCREAMING_SNAKE_CASE__      ,	'positive'     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[int]     )    ->				Any:
         A						:     Any         =self.tool(text='That\'s quite cool'      ,	labels=['positive', 'negative']     )
         self.assertEqual(SCREAMING_SNAKE_CASE__      ,	'positive'     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Optional[int]     )    ->				Any:
         A						:     Optional[int]         =self.remote_tool(text='That\'s quite cool'      ,	labels=['positive', 'negative']     )
         self.assertEqual(SCREAMING_SNAKE_CASE__      ,	'positive'     )







_lowercase							:      Dict      							='''0.21.0'''

from .accelerator import Accelerator
from .big_modeling import (
    cpu_offload,
    cpu_offload_with_hook,
    disk_offload,
    dispatch_model,
    init_empty_weights,
    init_on_device,
    load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launchers import debug_launcher, notebook_launcher
from .state import PartialState
from .utils import (
    DeepSpeedPlugin,
    DistributedDataParallelKwargs,
    DistributedType,
    FullyShardedDataParallelPlugin,
    GradScalerKwargs,
    InitProcessGroupKwargs,
    find_executable_batch_size,
    infer_auto_device_map,
    is_rich_available,
    load_checkpoint_in_model,
    synchronize_rng_states,
)


if is_rich_available():
    from .utils import rich






