
from typing import TYPE_CHECKING

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


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

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

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case				:   Optional[int]     =				[
						    '''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				:   Optional[int]     =				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

'''simple docstring'''







from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_snake_case				:   List[Any]     =				logging.get_logger(__name__)

_snake_case				:   int     =				{
    """YituTech/conv-bert-base""": """https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json""",
    """YituTech/conv-bert-medium-small""": (
        """https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json"""
    ),
    """YituTech/conv-bert-small""": """https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json""",
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}


class 			lowerCAmelCase (				__UpperCAmelCase			):
		a							:					Tuple       =					"""convbert"""




		def __init__(				self					,						UpperCamelCase=30_522					,						UpperCamelCase=768					,						UpperCamelCase=12					,						UpperCamelCase=12					,						UpperCamelCase=3_072					,						UpperCamelCase="gelu"					,						UpperCamelCase=0.1					,						UpperCamelCase=0.1					,						UpperCamelCase=512					,						UpperCamelCase=2					,						UpperCamelCase=0.02					,						UpperCamelCase=1e-12					,						UpperCamelCase=1					,						UpperCamelCase=0					,						UpperCamelCase=2					,						UpperCamelCase=768					,						UpperCamelCase=2					,						UpperCamelCase=9					,						UpperCamelCase=1					,						UpperCamelCase=None					,						**UpperCamelCase					,						):
								super().__init__(
								    pad_token_id=UpperCamelCase					,						bos_token_id=UpperCamelCase					,						eos_token_id=UpperCamelCase					,						**UpperCamelCase					,						)

								_SCREAMING_SNAKE_CASE				= vocab_size
								_SCREAMING_SNAKE_CASE				= hidden_size
								_SCREAMING_SNAKE_CASE				= num_hidden_layers
								_SCREAMING_SNAKE_CASE				= num_attention_heads
								_SCREAMING_SNAKE_CASE				= intermediate_size
								_SCREAMING_SNAKE_CASE				= hidden_act
								_SCREAMING_SNAKE_CASE				= hidden_dropout_prob
								_SCREAMING_SNAKE_CASE				= attention_probs_dropout_prob
								_SCREAMING_SNAKE_CASE				= max_position_embeddings
								_SCREAMING_SNAKE_CASE				= type_vocab_size
								_SCREAMING_SNAKE_CASE				= initializer_range
								_SCREAMING_SNAKE_CASE				= layer_norm_eps
								_SCREAMING_SNAKE_CASE				= embedding_size
								_SCREAMING_SNAKE_CASE				= head_ratio
								_SCREAMING_SNAKE_CASE				= conv_kernel_size
								_SCREAMING_SNAKE_CASE				= num_groups
								_SCREAMING_SNAKE_CASE				= classifier_dropout


class 			lowerCAmelCase (				__UpperCAmelCase			):




		@property
		def     lowercase       (				self      ):
								if self.task == "multiple-choice":
														_SCREAMING_SNAKE_CASE				= {0: "batch", 1: "choice", 2: "sequence"}
								else:
														_SCREAMING_SNAKE_CASE				= {0: "batch", 1: "sequence"}
								return OrderedDict(
								    [
								        ("input_ids", dynamic_axis),
								        ("attention_mask", dynamic_axis),
								        ("token_type_ids", dynamic_axis),
								    ]      )