





import unittest

from transformers.image_processing_utils import get_size_dict







class 	_UpperCamelCase	(							unittest.TestCase	):







					'''simple docstring'''

					def 							SCREAMING_SNAKE_CASE				(    self     :	Optional[Any]		):






						'''simple docstring'''







						UpperCAmelCase_		    =  {"""wrong_key""": 2_24}
						with self.assertRaises(__lowercase		):
							get_size_dict(__lowercase		)

						UpperCAmelCase_		    =  {"""height""": 2_24}
						with self.assertRaises(__lowercase		):
							get_size_dict(__lowercase		)

						UpperCAmelCase_		    =  {"""width""": 2_24, """shortest_edge""": 2_24}
						with self.assertRaises(__lowercase		):
							get_size_dict(__lowercase		)

						# Test a dict with the correct keys is returned as is
						UpperCAmelCase_		    =  {"""height""": 2_24, """width""": 2_24}
						UpperCAmelCase_		    =  get_size_dict(__lowercase		)
						self.assertEqual(__lowercase			,       __lowercase		)

						UpperCAmelCase_		    =  {"""shortest_edge""": 2_24}
						UpperCAmelCase_		    =  get_size_dict(__lowercase		)
						self.assertEqual(__lowercase			,       {"""shortest_edge""": 2_24}		)

						UpperCAmelCase_		    =  {"""longest_edge""": 2_24, """shortest_edge""": 2_24}
						UpperCAmelCase_		    =  get_size_dict(__lowercase		)
						self.assertEqual(__lowercase			,       {"""longest_edge""": 2_24, """shortest_edge""": 2_24}		)

						# Test a single int value which  represents (size, size)
						UpperCAmelCase_		    =  get_size_dict(2_24		)
						self.assertEqual(__lowercase			,       {"""height""": 2_24, """width""": 2_24}		)

						# Test a single int value which represents the shortest edge
						UpperCAmelCase_		    =  get_size_dict(2_24			,       default_to_square=__lowercase		)
						self.assertEqual(__lowercase			,       {"""shortest_edge""": 2_24}		)

						# Test a tuple of ints which represents (height, width)
						UpperCAmelCase_		    =  get_size_dict((1_50, 2_00)		)
						self.assertEqual(__lowercase			,       {"""height""": 1_50, """width""": 2_00}		)

						# Test a tuple of ints which represents (width, height)
						UpperCAmelCase_		    =  get_size_dict((1_50, 2_00)			,       height_width_order=__lowercase		)
						self.assertEqual(__lowercase			,       {"""height""": 2_00, """width""": 1_50}		)

						# Test an int representing the shortest edge and max_size which represents the longest edge
						UpperCAmelCase_		    =  get_size_dict(2_24			,       max_size=2_56			,       default_to_square=__lowercase		)
						self.assertEqual(__lowercase			,       {"""shortest_edge""": 2_24, """longest_edge""": 2_56}		)

						# Test int with default_to_square=True and max_size fails
						with self.assertRaises(__lowercase		):
							get_size_dict(2_24			,       max_size=2_56			,       default_to_square=__lowercase		)









from typing import TYPE_CHECKING

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


UpperCamelCase__ :			Any       	=			{
    """configuration_splinter""": ["""SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SplinterConfig"""],
    """tokenization_splinter""": ["""SplinterTokenizer"""],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase__ :			Any       	=			["""SplinterTokenizerFast"""]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase__ :			Union[str, Any]       	=			[
				    """SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """SplinterForQuestionAnswering""",
				    """SplinterForPreTraining""",
				    """SplinterLayer""",
				    """SplinterModel""",
				    """SplinterPreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
				from .tokenization_splinter import SplinterTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_splinter_fast import SplinterTokenizerFast

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_splinter import (
								    SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    SplinterForPreTraining,
								    SplinterForQuestionAnswering,
								    SplinterLayer,
								    SplinterModel,
								    SplinterPreTrainedModel,
								)


else:
				import sys

				UpperCamelCase__ :			List[str]       	=			_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


