


import warnings

from ..trainer import Trainer
from ..utils import logging


lowercase  :							Optional[Any]			  =    logging.get_logger(__name__)




class 		UpperCAmelCase_						(	_UpperCAmelCase					):


						'''simple docstring'''




						def __init__(	self		,				_SCREAMING_SNAKE_CASE=None		,				**_SCREAMING_SNAKE_CASE				) ->				Dict:
								warnings.warn(
								    "`SageMakerTrainer` is deprecated and will be removed in v5 of Transformers. You can use `Trainer` "
								    "instead."		,				A_		,				)
								super().__init__(args=A_		,				**A_				)








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase  :							Optional[int]			  =    {
    '''configuration_nllb_moe''': [
        '''NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''NllbMoeConfig''',
    ]
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase  :							Optional[Any]			  =    [
							    '''NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''NllbMoeForConditionalGeneration''',
							    '''NllbMoeModel''',
							    '''NllbMoePreTrainedModel''',
							    '''NllbMoeTop2Router''',
							    '''NllbMoeSparseMLP''',
							]


if TYPE_CHECKING:
							from .configuration_nllb_moe import (
							    NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    NllbMoeConfig,
							)

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_nllb_moe import (
														    NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    NllbMoeForConditionalGeneration,
														    NllbMoeModel,
														    NllbMoePreTrainedModel,
														    NllbMoeSparseMLP,
														    NllbMoeTopaRouter,
														)


else:
							import sys

							lowercase  :							Tuple			  =    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
