



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase__ =						{
    "configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP", "FunnelConfig"],
    "convert_funnel_original_tf_checkpoint_to_pytorch": [],
    "tokenization_funnel": ["FunnelTokenizer"],
}

try:
			if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCamelCase__ =						["FunnelTokenizerFast"]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCamelCase__ =						[
			    "FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "FunnelBaseModel",
			    "FunnelForMaskedLM",
			    "FunnelForMultipleChoice",
			    "FunnelForPreTraining",
			    "FunnelForQuestionAnswering",
			    "FunnelForSequenceClassification",
			    "FunnelForTokenClassification",
			    "FunnelModel",
			    "FunnelPreTrainedModel",
			    "load_tf_weights_in_funnel",
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCamelCase__ =						[
			    "TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "TFFunnelBaseModel",
			    "TFFunnelForMaskedLM",
			    "TFFunnelForMultipleChoice",
			    "TFFunnelForPreTraining",
			    "TFFunnelForQuestionAnswering",
			    "TFFunnelForSequenceClassification",
			    "TFFunnelForTokenClassification",
			    "TFFunnelModel",
			    "TFFunnelPreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_funnel import FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP, FunnelConfig
			from .tokenization_funnel import FunnelTokenizer

			try:
						if not is_tokenizers_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_funnel_fast import FunnelTokenizerFast

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_funnel import (
						    FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
						    FunnelBaseModel,
						    FunnelForMaskedLM,
						    FunnelForMultipleChoice,
						    FunnelForPreTraining,
						    FunnelForQuestionAnswering,
						    FunnelForSequenceClassification,
						    FunnelForTokenClassification,
						    FunnelModel,
						    FunnelPreTrainedModel,
						    load_tf_weights_in_funnel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_funnel import (
						    TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
						    TFFunnelBaseModel,
						    TFFunnelForMaskedLM,
						    TFFunnelForMultipleChoice,
						    TFFunnelForPreTraining,
						    TFFunnelForQuestionAnswering,
						    TFFunnelForSequenceClassification,
						    TFFunnelForTokenClassification,
						    TFFunnelModel,
						    TFFunnelPreTrainedModel,
						)

else:
			import sys

			UpperCamelCase__ =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










from collections import OrderedDict
from typing import Mapping

from packaging import version

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


UpperCamelCase__ =						logging.get_logger(__name__)

UpperCamelCase__ =						{
    "hustvl/yolos-small": "https://huggingface.co/hustvl/yolos-small/resolve/main/config.json",
    # See all YOLOS models at https://huggingface.co/models?filter=yolos
}
class 			_lowerCAmelCase   ( _UpperCAmelCase			):






			"""simple docstring"""





			lowercase__      :  Union[str, Any]      =			"""yolos"""





			def __init__(				self	:       Optional[int]			,     lowercase	:       Any=768			,     lowercase	:       Tuple=12			,     lowercase	:       Tuple=12			,     lowercase	:       str=3_072			,     lowercase	:       Optional[Any]="gelu"			,     lowercase	:       Union[str, Any]=0.0			,     lowercase	:       Dict=0.0			,     lowercase	:       Optional[int]=0.02			,     lowercase	:       Optional[Any]=1E-1_2			,     lowercase	:       Tuple=[512, 864]			,     lowercase	:       Optional[int]=16			,     lowercase	:       Dict=3			,     lowercase	:       Optional[Any]=True			,     lowercase	:       Optional[int]=100			,     lowercase	:       Optional[int]=True			,     lowercase	:       Any=False			,     lowercase	:       Any=1			,     lowercase	:       Any=5			,     lowercase	:       List[str]=2			,     lowercase	:       Union[str, Any]=5			,     lowercase	:       str=2			,     lowercase	:       Tuple=0.1			,     **lowercase	:       str			,     )						->					Optional[Any]:
									"""simple docstring"""







									super().__init__(**lowercase   )

									__lowercase					=				hidden_size
									__lowercase					=				num_hidden_layers
									__lowercase					=				num_attention_heads
									__lowercase					=				intermediate_size
									__lowercase					=				hidden_act
									__lowercase					=				hidden_dropout_prob
									__lowercase					=				attention_probs_dropout_prob
									__lowercase					=				initializer_range
									__lowercase					=				layer_norm_eps
									__lowercase					=				image_size
									__lowercase					=				patch_size
									__lowercase					=				num_channels
									__lowercase					=				qkv_bias
									__lowercase					=				num_detection_tokens
									__lowercase					=				use_mid_position_embeddings
									__lowercase					=				auxiliary_loss
									# Hungarian matcher
									__lowercase					=				class_cost
									__lowercase					=				bbox_cost
									__lowercase					=				giou_cost
									# Loss coefficients
									__lowercase					=				bbox_loss_coefficient
									__lowercase					=				giou_loss_coefficient
									__lowercase					=				eos_coefficient





class 			_lowerCAmelCase   ( _UpperCAmelCase			):






			"""simple docstring"""





			lowercase__      :  Dict      =			version.parse("""1.11"""			)





			@property
			def 		snake_case__			(				self	:       List[str]   )						->					Mapping[str, Mapping[int, str]]:
									"""simple docstring"""







									return OrderedDict(
									    [
									        ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
									    ]   )





			@property
			def 		snake_case__			(				self	:       int   )						->					float:
									"""simple docstring"""







									return 1E-4







			@property
			def 		snake_case__			(				self	:       Optional[Any]   )						->					int:
									"""simple docstring"""







									return 12





