






"""simple docstring"""
import functools
from typing import Any





def 				lowercase__		(					lowerCamelCase,						lowerCamelCase       ):

				# Validation
				if not isinstance(lowerCamelCase,						lowerCamelCase       ) or len(lowerCamelCase       ) == 0:
								raise ValueError('the string should be not empty string'       )

				if not isinstance(lowerCamelCase,						lowerCamelCase       ) or not all(
				    isinstance(lowerCamelCase,						lowerCamelCase       ) and len(lowerCamelCase       ) > 0 for item in words       ):
								raise ValueError('the words should be a list of non-empty strings'       )

				# Build trie
				_SCREAMING_SNAKE_CASE   :		dict[str, Any]       		=    {}
				_SCREAMING_SNAKE_CASE   :		List[str]       		=    'WORD_KEEPER'

				for word in words:
								_SCREAMING_SNAKE_CASE   :		int       		=    trie
								for c in word:
												if c not in trie_node:
																_SCREAMING_SNAKE_CASE   :		int       		=    {}

												_SCREAMING_SNAKE_CASE   :		List[Any]       		=    trie_node[c]

								_SCREAMING_SNAKE_CASE   :		str       		=    True

				_SCREAMING_SNAKE_CASE   :		Dict       		=    len(lowerCamelCase       )

				# Dynamic programming method
				@functools.cache
				def is_breakable(lowerCamelCase       ) -> bool:
								if index == len_string:
												return True

								_SCREAMING_SNAKE_CASE   :		int       		=    trie
								for i in range(lowerCamelCase,						lowerCamelCase       ):
												_SCREAMING_SNAKE_CASE   :		Optional[int]       		=    trie_node.get(string[i],						lowerCamelCase       )

												if trie_node is None:
																return False

												if trie_node.get(lowerCamelCase,						lowerCamelCase       ) and is_breakable(i + 1       ):
																return True

								return False

				return is_breakable(0       )


if __name__ == "__main__":
			import doctest

			doctest.testmod()









"""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 _lowerCAmelCase						(    __UpperCAmelCase       ):
						SCREAMING_SNAKE_CASE_:					Any 					=				'swin2sr'

						SCREAMING_SNAKE_CASE_:					Dict 					=				{
						    'hidden_size': 'embed_dim',
						    'num_attention_heads': 'num_heads',
						    'num_hidden_layers': 'num_layers',
						}







						def __init__(    self   ,				lowerCAmelCase_=6_4   ,				lowerCAmelCase_=1   ,				lowerCAmelCase_=3   ,				lowerCAmelCase_=1_8_0   ,				lowerCAmelCase_=[6, 6, 6, 6, 6, 6]   ,				lowerCAmelCase_=[6, 6, 6, 6, 6, 6]   ,				lowerCAmelCase_=8   ,				lowerCAmelCase_=2.0   ,				lowerCAmelCase_=True   ,				lowerCAmelCase_=0.0   ,				lowerCAmelCase_=0.0   ,				lowerCAmelCase_=0.1   ,				lowerCAmelCase_="gelu"   ,				lowerCAmelCase_=False   ,				lowerCAmelCase_=0.02   ,				lowerCAmelCase_=1e-5   ,				lowerCAmelCase_=2   ,				lowerCAmelCase_=1.0   ,				lowerCAmelCase_="1conv"   ,				lowerCAmelCase_="pixelshuffle"   ,				**lowerCAmelCase_   ,				)		->							Dict:
										super().__init__(**lowerCAmelCase_							)

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

