



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


_snake_case		=  logging.get_logger(__name__)

_snake_case		=  {
    "microsoft/swinv2-tiny-patch4-window8-256": (
        "https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"
    ),
}



class   UpperCAmelCase_    (       a):
							lowerCamelCase__   			=		'swinv2'

							lowerCamelCase__   			=		{
							    'num_attention_heads': 'num_heads',
							    'num_hidden_layers': 'num_layers',
							}







							def __init__(   self,			__a=224,			__a=4,			__a=3,			__a=96,			__a=[2, 2, 6, 2],			__a=[3, 6, 12, 24],			__a=7,			__a=4.0,			__a=True,			__a=0.0,			__a=0.0,			__a=0.1,			__a="gelu",			__a=False,			__a=0.02,			__a=1E-5,			__a=32,			**__a,			):

														'''simple docstring'''

														super().__init__(**__a)

														_lowerCAmelCase     :							Union[str, Any]    =    image_size
														_lowerCAmelCase     :							Any    =    patch_size
														_lowerCAmelCase     :							Any    =    num_channels
														_lowerCAmelCase     :							Union[str, Any]    =    embed_dim
														_lowerCAmelCase     :							Union[str, Any]    =    depths
														_lowerCAmelCase     :							Tuple    =    len(__a)
														_lowerCAmelCase     :							Union[str, Any]    =    num_heads
														_lowerCAmelCase     :							Tuple    =    window_size
														_lowerCAmelCase     :							str    =    mlp_ratio
														_lowerCAmelCase     :							Optional[Any]    =    qkv_bias
														_lowerCAmelCase     :							Union[str, Any]    =    hidden_dropout_prob
														_lowerCAmelCase     :							str    =    attention_probs_dropout_prob
														_lowerCAmelCase     :							Optional[Any]    =    drop_path_rate
														_lowerCAmelCase     :							Tuple    =    hidden_act
														_lowerCAmelCase     :							Union[str, Any]    =    use_absolute_embeddings
														_lowerCAmelCase     :							int    =    layer_norm_eps
														_lowerCAmelCase     :							Tuple    =    initializer_range
														_lowerCAmelCase     :							Optional[Any]    =    encoder_stride
														# we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
														# this indicates the channel dimension after the last stage of the model
														_lowerCAmelCase     :							Tuple    =    int(embed_dim * 2 ** (len(__a) - 1))
														_lowerCAmelCase     :							Optional[int]    =    (0, 0, 0, 0)





import pytest

from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs






@pytest.mark.parametrize(
    "kwargs, expected"				, [
        ({"num_shards": 0, "max_num_jobs": 1}, []),
        ({"num_shards": 10, "max_num_jobs": 1}, [range(10  )]),
        ({"num_shards": 10, "max_num_jobs": 10}, [range(_lowerCamelCase				, i + 1  ) for i in range(10  )]),
        ({"num_shards": 1, "max_num_jobs": 10}, [range(1  )]),
        ({"num_shards": 10, "max_num_jobs": 3}, [range(0				, 4  ), range(4				, 7  ), range(7				, 10  )]),
        ({"num_shards": 3, "max_num_jobs": 10}, [range(0				, 1  ), range(1				, 2  ), range(2				, 3  )]),
    ]				, )
def 				A				(					_lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							_lowerCAmelCase     :							List[Any]    =    _distribute_shards(**_lowerCamelCase  )
							assert out == expected






@pytest.mark.parametrize(
    "gen_kwargs, max_num_jobs, expected"				, [
        ({"foo": 0}, 10, [{"foo": 0}]),
        ({"shards": [0, 1, 2, 3]}, 1, [{"shards": [0, 1, 2, 3]}]),
        ({"shards": [0, 1, 2, 3]}, 4, [{"shards": [0]}, {"shards": [1]}, {"shards": [2]}, {"shards": [3]}]),
        ({"shards": [0, 1]}, 4, [{"shards": [0]}, {"shards": [1]}]),
        ({"shards": [0, 1, 2, 3]}, 2, [{"shards": [0, 1]}, {"shards": [2, 3]}]),
    ]				, )
def 				A				(					_lowerCamelCase				, _lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							_lowerCAmelCase     :							Optional[int]    =    _split_gen_kwargs(_lowerCamelCase				, _lowerCamelCase  )
							assert out == expected






@pytest.mark.parametrize(
    "gen_kwargs, expected"				, [
        ({"foo": 0}, 1),
        ({"shards": [0]}, 1),
        ({"shards": [0, 1, 2, 3]}, 4),
        ({"shards": [0, 1, 2, 3], "foo": 0}, 4),
        ({"shards": [0, 1, 2, 3], "other": (0, 1)}, 4),
        ({"shards": [0, 1, 2, 3], "shards2": [0, 1]}, RuntimeError),
    ]				, )
def 				A				(					_lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							if expected is RuntimeError:
														with pytest.raises(_lowerCamelCase  ):
																					_number_of_shards_in_gen_kwargs(_lowerCamelCase  )
							else:
														_lowerCAmelCase     :							Optional[int]    =    _number_of_shards_in_gen_kwargs(_lowerCamelCase  )
														assert out == expected
