

"""simple docstring"""






from typing import Tuple, Union

from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig


if is_timm_available():
	import timm


if is_torch_available():
	from torch import Tensor







class       snake_case__  ( lowerCAmelCase_					,  lowerCAmelCase_     ):
			SCREAMING_SNAKE_CASE__     				=						'''pixel_values'''
			SCREAMING_SNAKE_CASE__     				=						False
			SCREAMING_SNAKE_CASE__     				=						TimmBackboneConfig







			def __init__(			self			: Optional[int]			,  lowercase			: Optional[Any]			,  **lowercase			: List[str]  ):





								'''simple docstring'''



								requires_backends(self			,  "timm"  )
								super().__init__(lowercase  )
								UpperCAmelCase			:   Optional[int]      =				config

								if config.backbone is None:
													raise ValueError("backbone is not set in the config. Please set it to a timm model name."  )

								if config.backbone not in timm.list_models():
													raise ValueError(f"""backbone {config.backbone} is not supported by timm."""  )

								if hasattr(lowercase			,  "out_features"  ) and config.out_features is not None:
													raise ValueError("out_features is not supported by TimmBackbone. Please use out_indices instead."  )

								UpperCAmelCase			:   Dict      =				getattr(lowercase			,  "use_pretrained_backbone"			,  lowercase  )
								if pretrained is None:
													raise ValueError("use_pretrained_backbone is not set in the config. Please set it to True or False."  )

								# We just take the final layer by default. This matches the default for the transformers models.
								UpperCAmelCase			:   Optional[Any]      =				config.out_indices if getattr(lowercase			,  "out_indices"			,  lowercase  ) is not None else (-1,)

								UpperCAmelCase			:   Any      =				timm.create_model(
								    config.backbone			,  pretrained=lowercase			,  features_only=config.features_only			,  in_chans=config.num_channels			,  out_indices=lowercase			,  **lowercase			,  )
								# These are used to control the output of the model when called. If output_hidden_states is True, then
								# return_layers is modified to include all layers.
								UpperCAmelCase			:   Optional[int]      =				self._backbone.return_layers
								UpperCAmelCase			:   str      =				{layer["module"]: str(lowercase  ) for i, layer in enumerate(self._backbone.feature_info.info  )}
								super()._init_backbone(lowercase  )







			@classmethod
			def 			__lowerCAmelCase				(			cls			: Dict			,  lowercase			: Optional[int]			,  *lowercase			: Any			,  **lowercase			: Optional[Any]  ):





								'''simple docstring'''



								requires_backends(cls			,  ["vision", "timm"]  )
								from ...models.timm_backbone import TimmBackboneConfig

								UpperCAmelCase			:   Union[str, Any]      =				kwargs.pop("config"			,  TimmBackboneConfig()  )

								UpperCAmelCase			:   Tuple      =				kwargs.pop("use_timm_backbone"			,  lowercase  )
								if not use_timm:
													raise ValueError("use_timm_backbone must be True for timm backbones"  )

								UpperCAmelCase			:   Tuple      =				kwargs.pop("num_channels"			,  config.num_channels  )
								UpperCAmelCase			:   List[Any]      =				kwargs.pop("features_only"			,  config.features_only  )
								UpperCAmelCase			:   str      =				kwargs.pop("use_pretrained_backbone"			,  config.use_pretrained_backbone  )
								UpperCAmelCase			:   int      =				kwargs.pop("out_indices"			,  config.out_indices  )
								UpperCAmelCase			:   Union[str, Any]      =				TimmBackboneConfig(
								    backbone=lowercase			,  num_channels=lowercase			,  features_only=lowercase			,  use_pretrained_backbone=lowercase			,  out_indices=lowercase			,  )
								return super()._from_config(lowercase			,  **lowercase  )







			def 			__lowerCAmelCase				(			self			: Any			,  lowercase			: Dict  ):





								'''simple docstring'''



								pass







			def 			__lowerCAmelCase				(			self			: Any			,  lowercase			: List[Any]			,  lowercase			: Any=None			,  lowercase			: Union[str, Any]=None			,  lowercase			: str=None			,  **lowercase			: Union[str, Any]  ):





								'''simple docstring'''



								UpperCAmelCase			:   str      =				return_dict if return_dict is not None else self.config.use_return_dict
								UpperCAmelCase			:   Optional[int]      =				(
								    output_hidden_states if output_hidden_states is not None else self.config.output_hidden_states
								)
								UpperCAmelCase			:   str      =				output_attentions if output_attentions is not None else self.config.output_attentions

								if output_attentions:
													raise ValueError("Cannot output attentions for timm backbones at the moment"  )

								if output_hidden_states:
													# We modify the return layers to include all the stages of the backbone
													UpperCAmelCase			:   int      =				self._all_layers
													UpperCAmelCase			:   Optional[int]      =				self._backbone(lowercase			,  **lowercase  )
													UpperCAmelCase			:   Any      =				self._return_layers
													UpperCAmelCase			:   str      =				tuple(hidden_states[i] for i in self.out_indices  )
								else:
													UpperCAmelCase			:   List[Any]      =				self._backbone(lowercase			,  **lowercase  )
													UpperCAmelCase			:   Any      =				None

								UpperCAmelCase			:   List[str]      =				tuple(lowercase  )
								UpperCAmelCase			:   List[Any]      =				tuple(lowercase  ) if hidden_states is not None else None

								if not return_dict:
													UpperCAmelCase			:   Optional[int]      =				(feature_maps,)
													if output_hidden_states:
																		UpperCAmelCase			:   Dict      =				output + (hidden_states,)
													return output

								return BackboneOutput(feature_maps=lowercase			,  hidden_states=lowercase			,  attentions=lowercase  )





"""simple docstring"""






snake_case_   :   List[str]        =       6_5_5_2_1



def   lowercase_	(    _lowercase       :		str	):




					'''simple docstring'''






					UpperCAmelCase			:   Dict      =				1
					UpperCAmelCase			:   Optional[int]      =				0
					for plain_chr in plain_text:
										UpperCAmelCase			:   int      =				(a + ord(_lowercase	)) % MOD_ADLER
										UpperCAmelCase			:   str      =				(b + a) % MOD_ADLER
					return (b << 16) | a


