




import unittest

from transformers.image_processing_utils import get_size_dict






class 	A	(						unittest.TestCase						):
     """simple docstring"""

     def        __snake_case      (			self     :      List[Any]	) ->				Union[str, Any]:
           lowerCamelCase__					     = {'wrong_key': 2_2_4}
           with self.assertRaises(_UpperCamelCase	):
                 get_size_dict(_UpperCamelCase	)

           lowerCamelCase__					     = {'height': 2_2_4}
           with self.assertRaises(_UpperCamelCase	):
                 get_size_dict(_UpperCamelCase	)

           lowerCamelCase__					     = {'width': 2_2_4, 'shortest_edge': 2_2_4}
           with self.assertRaises(_UpperCamelCase	):
                 get_size_dict(_UpperCamelCase	)

           # Test a dict with the correct keys is returned as is
           lowerCamelCase__					     = {'height': 2_2_4, 'width': 2_2_4}
           lowerCamelCase__					     = get_size_dict(_UpperCamelCase	)
           self.assertEqual(_UpperCamelCase		,     _UpperCamelCase	)

           lowerCamelCase__					     = {'shortest_edge': 2_2_4}
           lowerCamelCase__					     = get_size_dict(_UpperCamelCase	)
           self.assertEqual(_UpperCamelCase		,     {'shortest_edge': 2_2_4}	)

           lowerCamelCase__					     = {'longest_edge': 2_2_4, 'shortest_edge': 2_2_4}
           lowerCamelCase__					     = get_size_dict(_UpperCamelCase	)
           self.assertEqual(_UpperCamelCase		,     {'longest_edge': 2_2_4, 'shortest_edge': 2_2_4}	)

           # Test a single int value which  represents (size, size)
           lowerCamelCase__					     = get_size_dict(2_2_4	)
           self.assertEqual(_UpperCamelCase		,     {'height': 2_2_4, 'width': 2_2_4}	)

           # Test a single int value which represents the shortest edge
           lowerCamelCase__					     = get_size_dict(2_2_4		,     default_to_square=_UpperCamelCase	)
           self.assertEqual(_UpperCamelCase		,     {'shortest_edge': 2_2_4}	)

           # Test a tuple of ints which represents (height, width)
           lowerCamelCase__					     = get_size_dict((1_5_0, 2_0_0)	)
           self.assertEqual(_UpperCamelCase		,     {'height': 1_5_0, 'width': 2_0_0}	)

           # Test a tuple of ints which represents (width, height)
           lowerCamelCase__					     = get_size_dict((1_5_0, 2_0_0)		,     height_width_order=_UpperCamelCase	)
           self.assertEqual(_UpperCamelCase		,     {'height': 2_0_0, 'width': 1_5_0}	)

           # Test an int representing the shortest edge and max_size which represents the longest edge
           lowerCamelCase__					     = get_size_dict(2_2_4		,     max_size=2_5_6		,     default_to_square=_UpperCamelCase	)
           self.assertEqual(_UpperCamelCase		,     {'shortest_edge': 2_2_4, 'longest_edge': 2_5_6}	)

           # Test int with default_to_square=True and max_size fails
           with self.assertRaises(_UpperCamelCase	):
                 get_size_dict(2_2_4		,     max_size=2_5_6		,     default_to_square=_UpperCamelCase	)







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__snake_case			:			Optional[int]			   =   {"""configuration_sew_d""": ["""SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWDConfig"""]}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__snake_case			:			List[Any]			   =   [
					    """SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """SEWDForCTC""",
					    """SEWDForSequenceClassification""",
					    """SEWDModel""",
					    """SEWDPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_sew_d import SEW_D_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWDConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_sew_d import (
										    SEW_D_PRETRAINED_MODEL_ARCHIVE_LIST,
										    SEWDForCTC,
										    SEWDForSequenceClassification,
										    SEWDModel,
										    SEWDPreTrainedModel,
										)


else:
					import sys

					__snake_case			:			Dict			   =   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





