




'''simple docstring'''


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


_snake_case				:				int       							=		logging.get_logger(__name__)

_snake_case				:				Tuple       							=		{
    'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json',
    # See all CANINE models at https://huggingface.co/models?filter=canine
}

class       A   (		_a   ):
							lowercase_          =    'canine'







							def __init__(  self	:  Any							,      lowerCAmelCase_	:  Optional[Any]=7_68							,      lowerCAmelCase_	:  str=12							,      lowerCAmelCase_	:  Optional[Any]=12							,      lowerCAmelCase_	:  Optional[int]=30_72							,      lowerCAmelCase_	:  Optional[int]="gelu"							,      lowerCAmelCase_	:  str=0.1							,      lowerCAmelCase_	:  Union[str, Any]=0.1							,      lowerCAmelCase_	:  Tuple=1_63_84							,      lowerCAmelCase_	:  List[str]=16							,      lowerCAmelCase_	:  List[str]=0.0_2							,      lowerCAmelCase_	:  Any=1e-12							,      lowerCAmelCase_	:  Union[str, Any]=0							,      lowerCAmelCase_	:  int=0XE0_00							,      lowerCAmelCase_	:  Tuple=0XE0_01							,      lowerCAmelCase_	:  Any=4							,      lowerCAmelCase_	:  Any=4							,      lowerCAmelCase_	:  Any=8							,      lowerCAmelCase_	:  Union[str, Any]=1_63_84							,      lowerCAmelCase_	:  Dict=1_28							,      **lowerCAmelCase_	:  List[Any]							,      )      ->							Tuple:


														"""simple docstring"""


														super().__init__(pad_token_id=lowerCAmelCase_							,      bos_token_id=lowerCAmelCase_							,      eos_token_id=lowerCAmelCase_							,      **lowerCAmelCase_ )

														_a     					=    max_position_embeddings
														_a     					=    hidden_size
														_a     					=    num_hidden_layers
														_a     					=    num_attention_heads
														_a     					=    intermediate_size
														_a     					=    hidden_act
														_a     					=    hidden_dropout_prob
														_a     					=    attention_probs_dropout_prob
														_a     					=    initializer_range
														_a     					=    type_vocab_size
														_a     					=    layer_norm_eps

														# Character config:
														_a     					=    downsampling_rate
														_a     					=    upsampling_kernel_size
														_a     					=    num_hash_functions
														_a     					=    num_hash_buckets
														_a     					=    local_transformer_stride







'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_snake_case				:				int       							=		{'configuration_yolos': ['YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YolosConfig', 'YolosOnnxConfig']}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_snake_case				:				List[str]       							=		['YolosFeatureExtractor']
				_snake_case				:				Optional[int]       							=		['YolosImageProcessor']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_snake_case				:				Tuple       							=		[
				    'YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'YolosForObjectDetection',
				    'YolosModel',
				    'YolosPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_yolos import YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP, YolosConfig, YolosOnnxConfig

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_yolos import YolosFeatureExtractor
								from .image_processing_yolos import YolosImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_yolos import (
								    YOLOS_PRETRAINED_MODEL_ARCHIVE_LIST,
								    YolosForObjectDetection,
								    YolosModel,
								    YolosPreTrainedModel,
								)


else:
				import sys

				_snake_case				:				Dict       							=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

