
"""simple docstring"""


from typing import List, Optional, TypeVar

from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interleave_iterable_datasets
from .splits import NamedSplit
from .utils import logging
from .utils.py_utils import Literal


_lowercase							   =				logging.get_logger(__name__)


_lowercase							   =				TypeVar('''DatasetType''', Dataset, IterableDataset)






def       _snake_case				(		snake_case__   :     List[DatasetType]	,      snake_case__   :     Optional[List[float]] = None	,      snake_case__   :     Optional[int] = None	,      snake_case__   :     Optional[DatasetInfo] = None	,      snake_case__   :     Optional[NamedSplit] = None	,      snake_case__   :     Literal["first_exhausted", "all_exhausted"] = "first_exhausted"	,      ):
	from .arrow_dataset import Dataset
	from .iterable_dataset import IterableDataset

	if not datasets:
		raise ValueError('Unable to interleave an empty list of datasets.'     )
	for i, dataset in enumerate(snake_case__     ):
		if not isinstance(snake_case__	,      (Dataset, IterableDataset)     ):
			if isinstance(snake_case__	,      (DatasetDict, IterableDatasetDict)     ):
				if not dataset:
					raise ValueError(
					    F'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} '
					    'is an empty dataset dictionary.'     )
				raise ValueError(
				    F'Dataset at position {i} has at least one split: {list(snake_case__     )}\n'
				    F'Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(snake_case__     )     )}\']'     )
			raise ValueError(
			    F'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(snake_case__     ).__name__}.'     )
		if i == 0:
			A   ,      A						   =   (
			    (Dataset, IterableDataset) if isinstance(snake_case__	,      snake_case__     ) else (IterableDataset, Dataset)
			)
		elif not isinstance(snake_case__	,      snake_case__     ):
			raise ValueError(
			    F'Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects.'     )
	if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
		raise ValueError(F'{stopping_strategy} is not supported. Please enter a valid stopping_strategy.'     )
	if dataset_type is Dataset:
		return _interleave_map_style_datasets(
		    snake_case__	,      snake_case__	,      snake_case__	,      info=snake_case__	,      split=snake_case__	,      stopping_strategy=snake_case__     )
	else:
		return _interleave_iterable_datasets(
		    snake_case__	,      snake_case__	,      snake_case__	,      info=snake_case__	,      split=snake_case__	,      stopping_strategy=snake_case__     )






def       _snake_case				(		snake_case__   :     List[DatasetType]	,      snake_case__   :     Optional[DatasetInfo] = None	,      snake_case__   :     Optional[NamedSplit] = None	,      snake_case__   :     int = 0	,      ):

	if not dsets:
		raise ValueError('Unable to concatenate an empty list of datasets.'     )
	for i, dataset in enumerate(snake_case__     ):
		if not isinstance(snake_case__	,      (Dataset, IterableDataset)     ):
			if isinstance(snake_case__	,      (DatasetDict, IterableDatasetDict)     ):
				if not dataset:
					raise ValueError(
					    F'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} '
					    'is an empty dataset dictionary.'     )
				raise ValueError(
				    F'Dataset at position {i} has at least one split: {list(snake_case__     )}\n'
				    F'Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(snake_case__     )     )}\']'     )
			raise ValueError(
			    F'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(snake_case__     ).__name__}.'     )
		if i == 0:
			A   ,      A						   =   (
			    (Dataset, IterableDataset) if isinstance(snake_case__	,      snake_case__     ) else (IterableDataset, Dataset)
			)
		elif not isinstance(snake_case__	,      snake_case__     ):
			raise ValueError(
			    F'Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects.'     )
	if dataset_type is Dataset:
		return _concatenate_map_style_datasets(snake_case__	,      info=snake_case__	,      split=snake_case__	,      axis=snake_case__     )
	else:
		return _concatenate_iterable_datasets(snake_case__	,      info=snake_case__	,      split=snake_case__	,      axis=snake_case__     )

"""simple docstring"""


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


_lowercase							   =				logging.get_logger(__name__)

_lowercase							   =				{
    '''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_				(      _lowercase    ):



						'''simple docstring'''


						_lowerCamelCase:    List[str]      =    '''yolos'''


						def __init__( self     :      Dict  ,A_     :      Optional[Any]=768  ,A_     :      int=12  ,A_     :      List[str]=12  ,A_     :      str=3072  ,A_     :      Tuple="gelu"  ,A_     :      Dict=0.0  ,A_     :      List[Any]=0.0  ,A_     :      Any=0.02  ,A_     :      str=1e-12  ,A_     :      List[Any]=[512, 864]  ,A_     :      Union[str, Any]=16  ,A_     :      List[str]=3  ,A_     :      Optional[int]=True  ,A_     :      Tuple=100  ,A_     :      str=True  ,A_     :      Optional[Any]=False  ,A_     :      Any=1  ,A_     :      Optional[Any]=5  ,A_     :      Optional[Any]=2  ,A_     :      Optional[int]=5  ,A_     :      List[Any]=2  ,A_     :      Union[str, Any]=0.1  ,**A_     :      Tuple  ,)     ->   Any:
							super().__init__(**A_      )

							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						   =   layer_norm_eps
							A						   =   image_size
							A						   =   patch_size
							A						   =   num_channels
							A						   =   qkv_bias
							A						   =   num_detection_tokens
							A						   =   use_mid_position_embeddings
							A						   =   auxiliary_loss
							# Hungarian matcher
							A						   =   class_cost
							A						   =   bbox_cost
							A						   =   giou_cost
							# Loss coefficients
							A						   =   bbox_loss_coefficient
							A						   =   giou_loss_coefficient
							A						   =   eos_coefficient







class 				lowerCAmelCase_				(      _lowercase    ):



						'''simple docstring'''


						_lowerCamelCase:    Any      =    version.parse('''1.11'''    )


						@property
						def 						_SCREAMING_SNAKE_CASE      ( self     :      Optional[int]      )     ->   Mapping[str, Mapping[int, str]]:
							return OrderedDict(
							    [
							        ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
							    ]      )


						@property
						def 						_SCREAMING_SNAKE_CASE      ( self     :      Any      )     ->   float:
							return 1e-4




						@property
						def 						_SCREAMING_SNAKE_CASE      ( self     :      Tuple      )     ->   int:
							return 12