



'''simple docstring'''

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


__lowerCAmelCase									=   logging.get_logger(__name__)

__lowerCAmelCase									=   {
    '''caidas/swin2sr-classicalsr-x2-64''': (
        '''https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json'''
    ),
}

class 	__magic_name__						(    _UpperCamelCase   ):
							lowerCAmelCase       :    List[str]   				=					'swin2sr'

							lowerCAmelCase       :    str   				=					{
							    'hidden_size': 'embed_dim',
							    'num_attention_heads': 'num_heads',
							    'num_hidden_layers': 'num_layers',
							}







							def __init__(							self					:       Union[str, Any]	,_UpperCAmelCase					:       Tuple=64	,_UpperCAmelCase					:       str=1	,_UpperCAmelCase					:       List[Any]=3	,_UpperCAmelCase					:       Any=180	,_UpperCAmelCase					:       Optional[Any]=[6, 6, 6, 6, 6, 6]	,_UpperCAmelCase					:       Any=[6, 6, 6, 6, 6, 6]	,_UpperCAmelCase					:       int=8	,_UpperCAmelCase					:       Any=2.0	,_UpperCAmelCase					:       Optional[Any]=True	,_UpperCAmelCase					:       Tuple=0.0	,_UpperCAmelCase					:       Optional[int]=0.0	,_UpperCAmelCase					:       Tuple=0.1	,_UpperCAmelCase					:       List[str]="gelu"	,_UpperCAmelCase					:       Tuple=False	,_UpperCAmelCase					:       Optional[int]=0.02	,_UpperCAmelCase					:       Union[str, Any]=1E-5	,_UpperCAmelCase					:       int=2	,_UpperCAmelCase					:       Tuple=1.0	,_UpperCAmelCase					:       Union[str, Any]="1conv"	,_UpperCAmelCase					:       Tuple="pixelshuffle"	,**_UpperCAmelCase					:       List[str]	,):
									super().__init__(**_UpperCAmelCase		)

									_a     :      List[str]        =							image_size
									_a     :      Dict        =							patch_size
									_a     :      Optional[int]        =							num_channels
									_a     :      Optional[int]        =							embed_dim
									_a     :      Union[str, Any]        =							depths
									_a     :      Optional[int]        =							len(_UpperCAmelCase		)
									_a     :      Optional[Any]        =							num_heads
									_a     :      str        =							window_size
									_a     :      Optional[Any]        =							mlp_ratio
									_a     :      Optional[int]        =							qkv_bias
									_a     :      Tuple        =							hidden_dropout_prob
									_a     :      List[Any]        =							attention_probs_dropout_prob
									_a     :      Any        =							drop_path_rate
									_a     :      str        =							hidden_act
									_a     :      Tuple        =							use_absolute_embeddings
									_a     :      Dict        =							layer_norm_eps
									_a     :      Any        =							initializer_range
									_a     :      Optional[Any]        =							upscale
									_a     :      int        =							img_range
									_a     :      Union[str, Any]        =							resi_connection
									_a     :      int        =							upsampler








"""simple docstring"""




from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import pyarrow as pa


if TYPE_CHECKING:
				from .features import FeatureType
@dataclass
class 					__lowerCAmelCase					:


		'''simple docstring'''



		__UpperCAmelCase		:			List[str]
		__UpperCAmelCase		:			Optional[str]										=				None
		# Automatically constructed
		__UpperCAmelCase		:			ClassVar[str]										=				"dict"
		__UpperCAmelCase		:			ClassVar[Any]										=				None
		__UpperCAmelCase		:			str										=				field(default='Translation'     ,			init=__SCREAMING_SNAKE_CASE     ,			repr=__SCREAMING_SNAKE_CASE       )

		def __call__(  self      ):
				return pa.struct({lang: pa.string() for lang in sorted(self.languages      )}      )





		def 			__UpperCAmelCase       (  self      ):
				from .features import Value

				return {k: Value('''string'''      ) for k in sorted(self.languages      )}







@dataclass
class 					__lowerCAmelCase					:


		'''simple docstring'''



		__UpperCAmelCase		:			Optional[List]										=				None
		__UpperCAmelCase		:			Optional[int]										=				None
		__UpperCAmelCase		:			Optional[str]										=				None
		# Automatically constructed
		__UpperCAmelCase		:			ClassVar[str]										=				"dict"
		__UpperCAmelCase		:			ClassVar[Any]										=				None
		__UpperCAmelCase		:			str										=				field(default='TranslationVariableLanguages'     ,			init=__SCREAMING_SNAKE_CASE     ,			repr=__SCREAMING_SNAKE_CASE       )

		def 			__UpperCAmelCase       (  self      ):
				__a           =			sorted(set(self.languages      )      ) if self.languages else None
				__a           =			len(self.languages      ) if self.languages else None

		def __call__(  self      ):
				return pa.struct({'''language''': pa.list_(pa.string()      ), '''translation''': pa.list_(pa.string()      )}      )

		def 			__UpperCAmelCase       (  self							, _a      ):
				__a           =			set(self.languages      )
				if self.languages and set(_a      ) - lang_set:
						raise ValueError(
						    f'''Some languages in example ({', '.join(sorted(set(_a      ) - lang_set      )      )}) are not in valid set ({', '.join(_a      )}).'''      )

				# Convert dictionary into tuples, splitting out cases where there are
				# multiple translations for a single language.
				__a           =			[]
				for lang, text in translation_dict.items():
						if isinstance(_a							, _a      ):
								translation_tuples.append((lang, text)      )
						else:
								translation_tuples.extend([(lang, el) for el in text]      )

        # Ensure translations are in ascending order by language code.
				__a      ,     __a           =			zip(*sorted(_a      )      )

				return {"language": languages, "translation": translations}





		def 			__UpperCAmelCase       (  self      ):
				from .features import Sequence, Value

				return {
				    "language": Sequence(Value('''string'''      )      ),
				    "translation": Sequence(Value('''string'''      )      ),
				}






