






"""simple docstring"""







import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


__a       :	str             = pytest.mark.integration





@pytest.mark.parametrize('''path''' ,     ['''paws''', '''csv'''])
def        SCREAMING_SNAKE_CASE       (      lowerCamelCase_ ,     lowerCamelCase_):
					inspect_dataset(lowerCamelCase_ ,     lowerCamelCase_)
					a__          =  path + '''.py'''
					assert script_name in os.listdir(lowerCamelCase_)
					assert "__pycache__" not in os.listdir(lowerCamelCase_)





@pytest.mark.filterwarnings('''ignore:inspect_metric is deprecated:FutureWarning''')
@pytest.mark.filterwarnings('''ignore:metric_module_factory is deprecated:FutureWarning''')
@pytest.mark.parametrize('''path''' ,     ['''accuracy'''])
def        SCREAMING_SNAKE_CASE       (      lowerCamelCase_ ,     lowerCamelCase_):
					inspect_metric(lowerCamelCase_ ,     lowerCamelCase_)
					a__          =  path + '''.py'''
					assert script_name in os.listdir(lowerCamelCase_)
					assert "__pycache__" not in os.listdir(lowerCamelCase_)





@pytest.mark.parametrize(
    '''path, config_name, expected_splits''' ,     [
        ('''squad''', '''plain_text''', ['''train''', '''validation''']),
        ('''dalle-mini/wit''', '''dalle-mini--wit''', ['''train''']),
        ('''paws''', '''labeled_final''', ['''train''', '''test''', '''validation''']),
    ] ,     )
def        SCREAMING_SNAKE_CASE       (      lowerCamelCase_ ,     lowerCamelCase_ ,     lowerCamelCase_):
					a__          =  get_dataset_config_info(lowerCamelCase_ ,     config_name=lowerCamelCase_)
					assert info.config_name == config_name
					assert list(info.splits.keys()) == expected_splits





@pytest.mark.parametrize(
    '''path, config_name, expected_exception''' ,     [
        ('''paws''', None, ValueError),
    ] ,     )
def        SCREAMING_SNAKE_CASE       (      lowerCamelCase_ ,     lowerCamelCase_ ,     lowerCamelCase_):
					with pytest.raises(lowerCamelCase_):
										get_dataset_config_info(lowerCamelCase_ ,     config_name=lowerCamelCase_)





@pytest.mark.parametrize(
    '''path, expected''' ,     [
        ('''squad''', '''plain_text'''),
        ('''acronym_identification''', '''default'''),
        ('''lhoestq/squad''', '''plain_text'''),
        ('''lhoestq/test''', '''default'''),
        ('''lhoestq/demo1''', '''lhoestq--demo1'''),
        ('''dalle-mini/wit''', '''dalle-mini--wit'''),
    ] ,     )
def        SCREAMING_SNAKE_CASE       (      lowerCamelCase_ ,     lowerCamelCase_):
					a__          =  get_dataset_config_names(lowerCamelCase_)
					assert expected in config_names





@pytest.mark.parametrize(
    '''path, expected_configs, expected_splits_in_first_config''' ,     [
        ('''squad''', ['''plain_text'''], ['''train''', '''validation''']),
        ('''dalle-mini/wit''', ['''dalle-mini--wit'''], ['''train''']),
        ('''paws''', ['''labeled_final''', '''labeled_swap''', '''unlabeled_final'''], ['''train''', '''test''', '''validation''']),
    ] ,     )
def        SCREAMING_SNAKE_CASE       (      lowerCamelCase_ ,     lowerCamelCase_ ,     lowerCamelCase_):
					a__          =  get_dataset_infos(lowerCamelCase_)
					assert list(infos.keys()) == expected_configs
					a__          =  expected_configs[0]
					assert expected_config in infos
					a__          =  infos[expected_config]
					assert info.config_name == expected_config
					assert list(info.splits.keys()) == expected_splits_in_first_config





@pytest.mark.parametrize(
    '''path, expected_config, expected_splits''' ,     [
        ('''squad''', '''plain_text''', ['''train''', '''validation''']),
        ('''dalle-mini/wit''', '''dalle-mini--wit''', ['''train''']),
        ('''paws''', '''labeled_final''', ['''train''', '''test''', '''validation''']),
    ] ,     )
def        SCREAMING_SNAKE_CASE       (      lowerCamelCase_ ,     lowerCamelCase_ ,     lowerCamelCase_):
					a__          =  get_dataset_infos(lowerCamelCase_)
					assert expected_config in infos
					a__          =  infos[expected_config]
					assert info.config_name == expected_config
					assert list(info.splits.keys()) == expected_splits





@pytest.mark.parametrize(
    '''path, config_name, expected_exception''' ,     [
        ('''paws''', None, ValueError),
    ] ,     )
def        SCREAMING_SNAKE_CASE       (      lowerCamelCase_ ,     lowerCamelCase_ ,     lowerCamelCase_):
					with pytest.raises(lowerCamelCase_):
										get_dataset_split_names(lowerCamelCase_ ,     config_name=lowerCamelCase_)










"""simple docstring"""







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


__a       :	Any             = logging.get_logger(__name__)

__a       :	Union[str, Any]             = {
    'caidas/swin2sr-classicalsr-x2-64': (
        'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json'
    ),
}







class        _SCREAMING_SNAKE_CASE						(  __snake_case							):





							"""simple docstring"""





							_SCREAMING_SNAKE_CASE    ='swin2sr'

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




							def __init__(   self:     Union[str, Any]				,		__A:     List[Any]=64				,		__A:     int=1				,		__A:     Dict=3				,		__A:     List[Any]=180				,		__A:     int=[6, 6, 6, 6, 6, 6]				,		__A:     Tuple=[6, 6, 6, 6, 6, 6]				,		__A:     int=8				,		__A:     Optional[int]=2.0				,		__A:     Optional[int]=True				,		__A:     int=0.0				,		__A:     Any=0.0				,		__A:     Optional[Any]=0.1				,		__A:     Optional[Any]="gelu"				,		__A:     Dict=False				,		__A:     List[Any]=0.0_2				,		__A:     List[Any]=1e-5				,		__A:     List[str]=2				,		__A:     int=1.0				,		__A:     Dict="1conv"				,		__A:     Optional[Any]="pixelshuffle"				,		**__A:     Dict				,		):

												'''simple docstring'''

												super().__init__(**__A    )

												a__          =  image_size
												a__          =  patch_size
												a__          =  num_channels
												a__          =  embed_dim
												a__          =  depths
												a__          =  len(__A    )
												a__          =  num_heads
												a__          =  window_size
												a__          =  mlp_ratio
												a__          =  qkv_bias
												a__          =  hidden_dropout_prob
												a__          =  attention_probs_dropout_prob
												a__          =  drop_path_rate
												a__          =  hidden_act
												a__          =  use_absolute_embeddings
												a__          =  layer_norm_eps
												a__          =  initializer_range
												a__          =  upscale
												a__          =  img_range
												a__          =  resi_connection
												a__          =  upsampler


