

from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_        =      logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_        =      {
    'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}

class 				a  (	UpperCAmelCase				):
						_lowercase    						=			"timesformer"


						def __init__(       self						,					A_=224						,					A_=16						,					A_=3						,					A_=8						,					A_=768						,					A_=12						,					A_=12						,					A_=3072						,					A_="gelu"						,					A_=0.0						,					A_=0.0						,					A_=0.02						,					A_=1e-6						,					A_=True						,					A_="divided_space_time"						,					A_=0						,					**A_						,					):







										'''simple docstring'''


										super().__init__(**A_	)

										_UpperCAmelCase       :		Union[str, Any] 		=    image_size
										_UpperCAmelCase       :		Tuple 		=    patch_size
										_UpperCAmelCase       :		Any 		=    num_channels
										_UpperCAmelCase       :		List[Any] 		=    num_frames

										_UpperCAmelCase       :		str 		=    hidden_size
										_UpperCAmelCase       :		Any 		=    num_hidden_layers
										_UpperCAmelCase       :		Dict 		=    num_attention_heads
										_UpperCAmelCase       :		Optional[int] 		=    intermediate_size
										_UpperCAmelCase       :		Union[str, Any] 		=    hidden_act
										_UpperCAmelCase       :		Optional[Any] 		=    hidden_dropout_prob
										_UpperCAmelCase       :		Tuple 		=    attention_probs_dropout_prob
										_UpperCAmelCase       :		Union[str, Any] 		=    initializer_range
										_UpperCAmelCase       :		Optional[Any] 		=    layer_norm_eps
										_UpperCAmelCase       :		str 		=    qkv_bias

										_UpperCAmelCase       :		Tuple 		=    attention_type
										_UpperCAmelCase       :		List[Any] 		=    drop_path_rate





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE_        =      {
    'configuration_nllb_moe': [
        'NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'NllbMoeConfig',
    ]
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE_        =      [
					    '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

					SCREAMING_SNAKE_CASE_        =      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


