





import unittest

from transformers.image_processing_utils import get_size_dict

class    __A  (    unittest.TestCase     ):


				def _snake_case							(		self				):
								# Test a dict with the wrong keys raises an error
								lowerCamelCase									={"""wrong_key""": 224}
								with self.assertRaises(UpperCAmelCase_				):
												get_size_dict(UpperCAmelCase_				)

								lowerCamelCase									={"""height""": 224}
								with self.assertRaises(UpperCAmelCase_				):
												get_size_dict(UpperCAmelCase_				)

								lowerCamelCase									={"""width""": 224, """shortest_edge""": 224}
								with self.assertRaises(UpperCAmelCase_				):
												get_size_dict(UpperCAmelCase_				)

								# Test a dict with the correct keys is returned as is
								lowerCamelCase									={"""height""": 224, """width""": 224}
								lowerCamelCase									=get_size_dict(UpperCAmelCase_				)
								self.assertEqual(UpperCAmelCase_ ,			UpperCAmelCase_				)

								lowerCamelCase									={"""shortest_edge""": 224}
								lowerCamelCase									=get_size_dict(UpperCAmelCase_				)
								self.assertEqual(UpperCAmelCase_ ,			{"""shortest_edge""": 224}				)

								lowerCamelCase									={"""longest_edge""": 224, """shortest_edge""": 224}
								lowerCamelCase									=get_size_dict(UpperCAmelCase_				)
								self.assertEqual(UpperCAmelCase_ ,			{"""longest_edge""": 224, """shortest_edge""": 224}				)

								# Test a single int value which  represents (size, size)
								lowerCamelCase									=get_size_dict(224				)
								self.assertEqual(UpperCAmelCase_ ,			{"""height""": 224, """width""": 224}				)

								# Test a single int value which represents the shortest edge
								lowerCamelCase									=get_size_dict(224 ,			default_to_square=UpperCAmelCase_				)
								self.assertEqual(UpperCAmelCase_ ,			{"""shortest_edge""": 224}				)

								# Test a tuple of ints which represents (height, width)
								lowerCamelCase									=get_size_dict((150, 200)				)
								self.assertEqual(UpperCAmelCase_ ,			{"""height""": 150, """width""": 200}				)

								# Test a tuple of ints which represents (width, height)
								lowerCamelCase									=get_size_dict((150, 200) ,			height_width_order=UpperCAmelCase_				)
								self.assertEqual(UpperCAmelCase_ ,			{"""height""": 200, """width""": 150}				)

								# Test an int representing the shortest edge and max_size which represents the longest edge
								lowerCamelCase									=get_size_dict(224 ,			max_size=256 ,			default_to_square=UpperCAmelCase_				)
								self.assertEqual(UpperCAmelCase_ ,			{"""shortest_edge""": 224, """longest_edge""": 256}				)

								# Test int with default_to_square=True and max_size fails
								with self.assertRaises(UpperCAmelCase_				):
												get_size_dict(224 ,			max_size=256 ,			default_to_square=UpperCAmelCase_				)












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCAmelCase__    :      Optional[Any]       					={
    '''configuration_donut_swin''': ['''DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DonutSwinConfig'''],
    '''processing_donut''': ['''DonutProcessor'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__    :      Any       					=[
							    '''DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''DonutSwinModel''',
							    '''DonutSwinPreTrainedModel''',
							]

try:
							if not is_vision_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__    :      Tuple       					=['''DonutFeatureExtractor''']
							UpperCAmelCase__    :      List[str]       					=['''DonutImageProcessor''']


if TYPE_CHECKING:
							from .configuration_donut_swin import DONUT_SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, DonutSwinConfig
							from .processing_donut import DonutProcessor

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_donut_swin import (
														    DONUT_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DonutSwinModel,
														    DonutSwinPreTrainedModel,
														)

							try:
														if not is_vision_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .feature_extraction_donut import DonutFeatureExtractor
														from .image_processing_donut import DonutImageProcessor

else:
							import sys

							UpperCAmelCase__    :      int       					=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





