


"""simple docstring"""
import unittest

import numpy as np

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available

from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs


if is_torch_available():
			import torch

if is_vision_available():
			from PIL import Image

			from transformers import DeiTImageProcessor



class      _UpperCAmelCase					(				unittest.TestCase							):






		'''simple docstring'''

		def __init__(self							,			a_							,			a_=7							,			a_=3							,			a_=18							,			a_=30							,			a_=4_00							,			a_=True							,			a_=None							,			a_=True							,			a_=None							,			a_=True							,			a_=[0.5, 0.5, 0.5]							,			a_=[0.5, 0.5, 0.5]							,			):





			'''simple docstring'''

			__snake_case      :		Tuple         =							size if size is not None else {'''height''': 20, '''width''': 20}
			__snake_case      :		Optional[Any]         =							crop_size if crop_size is not None else {'''height''': 18, '''width''': 18}

			__snake_case      :		int         =							parent
			__snake_case      :		Union[str, Any]         =							batch_size
			__snake_case      :		Optional[int]         =							num_channels
			__snake_case      :		Union[str, Any]         =							image_size
			__snake_case      :		Dict         =							min_resolution
			__snake_case      :		int         =							max_resolution
			__snake_case      :		str         =							do_resize
			__snake_case      :		Optional[int]         =							size
			__snake_case      :		int         =							do_center_crop
			__snake_case      :		Union[str, Any]         =							crop_size
			__snake_case      :		List[str]         =							do_normalize
			__snake_case      :		str         =							image_mean
			__snake_case      :		Optional[int]         =							image_std



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			return {
			    "do_resize": self.do_resize,
			    "size": self.size,
			    "do_center_crop": self.do_center_crop,
			    "crop_size": self.crop_size,
			    "do_normalize": self.do_normalize,
			    "image_mean": self.image_mean,
			    "image_std": self.image_std,
			}



@require_torch
@require_vision
class      _UpperCAmelCase					(				__snake_case,							unittest.TestCase							):






		'''simple docstring'''

		lowerCamelCase__           =DeiTImageProcessor if is_vision_available() else None
		lowerCamelCase__           =True



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Optional[Any]         =							DeiTImageProcessingTester(self   )



		@property
		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			return self.image_processor_tester.prepare_image_processor_dict()



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		List[Any]         =							self.image_processing_class(**self.image_processor_dict   )
			self.assertTrue(hasattr(a_							,			'''do_resize'''   )   )
			self.assertTrue(hasattr(a_							,			'''size'''   )   )
			self.assertTrue(hasattr(a_							,			'''do_center_crop'''   )   )
			self.assertTrue(hasattr(a_							,			'''center_crop'''   )   )
			self.assertTrue(hasattr(a_							,			'''do_normalize'''   )   )
			self.assertTrue(hasattr(a_							,			'''image_mean'''   )   )
			self.assertTrue(hasattr(a_							,			'''image_std'''   )   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Tuple         =							self.image_processing_class.from_dict(self.image_processor_dict   )
			self.assertEqual(image_processor.size							,			{'''height''': 20, '''width''': 20}   )
			self.assertEqual(image_processor.crop_size							,			{'''height''': 18, '''width''': 18}   )

			__snake_case      :		List[str]         =							self.image_processing_class.from_dict(self.image_processor_dict							,			size=42							,			crop_size=84   )
			self.assertEqual(image_processor.size							,			{'''height''': 42, '''width''': 42}   )
			self.assertEqual(image_processor.crop_size							,			{'''height''': 84, '''width''': 84}   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			pass



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		str         =							self.image_processing_class(**self.image_processor_dict   )
			# create random PIL images
			__snake_case      :		int         =							prepare_image_inputs(self.image_processor_tester							,			equal_resolution=a_   )
			for image in image_inputs:
				self.assertIsInstance(a_							,			Image.Image   )

			# Test not batched input
			__snake_case      :		List[str]         =							image_processing(image_inputs[0]							,			return_tensors='''pt'''   ).pixel_values
			self.assertEqual(
			    encoded_images.shape							,			(
			        1,
			        self.image_processor_tester.num_channels,
			        self.image_processor_tester.crop_size['''height'''],
			        self.image_processor_tester.crop_size['''width'''],
			    )							,			)

			# Test batched
			__snake_case      :		Dict         =							image_processing(a_							,			return_tensors='''pt'''   ).pixel_values
			self.assertEqual(
			    encoded_images.shape							,			(
			        self.image_processor_tester.batch_size,
			        self.image_processor_tester.num_channels,
			        self.image_processor_tester.crop_size['''height'''],
			        self.image_processor_tester.crop_size['''width'''],
			    )							,			)



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		List[Any]         =							self.image_processing_class(**self.image_processor_dict   )
			# create random numpy tensors
			__snake_case      :		List[str]         =							prepare_image_inputs(self.image_processor_tester							,			equal_resolution=a_							,			numpify=a_   )
			for image in image_inputs:
				self.assertIsInstance(a_							,			np.ndarray   )

			# Test not batched input
			__snake_case      :		Any         =							image_processing(image_inputs[0]							,			return_tensors='''pt'''   ).pixel_values
			self.assertEqual(
			    encoded_images.shape							,			(
			        1,
			        self.image_processor_tester.num_channels,
			        self.image_processor_tester.crop_size['''height'''],
			        self.image_processor_tester.crop_size['''width'''],
			    )							,			)

			# Test batched
			__snake_case      :		Dict         =							image_processing(a_							,			return_tensors='''pt'''   ).pixel_values
			self.assertEqual(
			    encoded_images.shape							,			(
			        self.image_processor_tester.batch_size,
			        self.image_processor_tester.num_channels,
			        self.image_processor_tester.crop_size['''height'''],
			        self.image_processor_tester.crop_size['''width'''],
			    )							,			)



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Tuple         =							self.image_processing_class(**self.image_processor_dict   )
			# create random PyTorch tensors
			__snake_case      :		List[str]         =							prepare_image_inputs(self.image_processor_tester							,			equal_resolution=a_							,			torchify=a_   )
			for image in image_inputs:
				self.assertIsInstance(a_							,			torch.Tensor   )

			# Test not batched input
			__snake_case      :		Tuple         =							image_processing(image_inputs[0]							,			return_tensors='''pt'''   ).pixel_values
			self.assertEqual(
			    encoded_images.shape							,			(
			        1,
			        self.image_processor_tester.num_channels,
			        self.image_processor_tester.crop_size['''height'''],
			        self.image_processor_tester.crop_size['''width'''],
			    )							,			)

			# Test batched
			__snake_case      :		Tuple         =							image_processing(a_							,			return_tensors='''pt'''   ).pixel_values
			self.assertEqual(
			    encoded_images.shape							,			(
			        self.image_processor_tester.batch_size,
			        self.image_processor_tester.num_channels,
			        self.image_processor_tester.crop_size['''height'''],
			        self.image_processor_tester.crop_size['''width'''],
			    )							,			)









"""simple docstring"""
import unittest

from diffusers import __version__
from diffusers.utils import deprecate



class      _UpperCAmelCase					(				unittest.TestCase							):






		'''simple docstring'''

		lowerCamelCase__           ='.'.join([str(int(__version__.split('.'							)[0]							) + 1							)] + __version__.split('.'							)[1:]							)
		lowerCamelCase__           ='0.0.1'



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		int         =							{'''deprecated_arg''': 4}

			with self.assertWarns(a_   ) as warning:
				__snake_case      :		Union[str, Any]         =							deprecate('''deprecated_arg'''							,			self.higher_version							,			'''message'''							,			take_from=a_   )

			assert output == 4
			assert (
			    str(warning.warning   )
			    == f"""The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}."""
			    " message"
			)



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Tuple         =							{'''deprecated_arg''': 4}

			with self.assertWarns(a_   ) as warning:
				__snake_case      :		Dict         =							deprecate(('''deprecated_arg''', self.higher_version, '''message''')							,			take_from=a_   )

			assert output == 4
			assert (
			    str(warning.warning   )
			    == f"""The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}."""
			    " message"
			)



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		Union[str, Any]         =							{'''deprecated_arg_1''': 4, '''deprecated_arg_2''': 8}
			with self.assertWarns(a_   ) as warning:
				__snake_case      ,				__snake_case      :		List[Any]         =							deprecate(
				    ('''deprecated_arg_1''', self.higher_version, '''Hey''')							,			('''deprecated_arg_2''', self.higher_version, '''Hey''')							,			take_from=a_							,			)
			assert output_a == 4
			assert output_a == 8
			assert (
			    str(warning.warnings[0].message   )
			    == "The `deprecated_arg_1` argument is deprecated and will be removed in version"
			    f""" {self.higher_version}. Hey"""
			)
			assert (
			    str(warning.warnings[1].message   )
			    == "The `deprecated_arg_2` argument is deprecated and will be removed in version"
			    f""" {self.higher_version}. Hey"""
			)



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		int         =							{'''deprecated_arg''': 4}

			with self.assertRaises(a_   ) as error:
				deprecate(('''wrong_arg''', self.higher_version, '''message''')							,			take_from=a_   )

			assert "test_deprecate_function_incorrect_arg in" in str(error.exception   )
			assert "line" in str(error.exception   )
			assert "got an unexpected keyword argument `deprecated_arg`" in str(error.exception   )



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			with self.assertWarns(a_   ) as warning:
				deprecate(('''deprecated_arg''', self.higher_version, '''message''')   )

			assert (
			    str(warning.warning   )
			    == f"""`deprecated_arg` is deprecated and will be removed in version {self.higher_version}. message"""
			)



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			with self.assertWarns(a_   ) as warning:
				deprecate(
				    ('''deprecated_arg_1''', self.higher_version, '''Hey''')							,			('''deprecated_arg_2''', self.higher_version, '''Hey''')							,			)
			assert (
			    str(warning.warnings[0].message   )
			    == f"""`deprecated_arg_1` is deprecated and will be removed in version {self.higher_version}. Hey"""
			)
			assert (
			    str(warning.warnings[1].message   )
			    == f"""`deprecated_arg_2` is deprecated and will be removed in version {self.higher_version}. Hey"""
			)



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			class      _UpperCAmelCase					:






					'''simple docstring'''

					lowerCamelCase__           =5

			with self.assertWarns(a_   ) as warning:
				__snake_case      :		List[Any]         =							deprecate(('''arg''', self.higher_version, '''message''')							,			take_from=Args()   )

			assert arg == 5
			assert (
			    str(warning.warning   )
			    == f"""The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message"""
			)



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			class      _UpperCAmelCase					:






					'''simple docstring'''

					lowerCamelCase__           =5
					lowerCamelCase__           =7

			with self.assertWarns(a_   ) as warning:
				__snake_case      ,				__snake_case      :		List[str]         =							deprecate(
				    ('''arg''', self.higher_version, '''message''')							,			('''foo''', self.higher_version, '''message''')							,			('''does not exist''', self.higher_version, '''message''')							,			take_from=Args()							,			)

			assert arg_a == 5
			assert arg_a == 7
			assert (
			    str(warning.warning   )
			    == f"""The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message"""
			)
			assert (
			    str(warning.warnings[0].message   )
			    == f"""The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message"""
			)
			assert (
			    str(warning.warnings[1].message   )
			    == f"""The `foo` attribute is deprecated and will be removed in version {self.higher_version}. message"""
			)



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			__snake_case      :		str         =							{'''deprecated_arg''': 4}

			with self.assertRaises(a_   ) as error:
				deprecate(('''wrong_arg''', self.lower_version, '''message''')							,			take_from=a_   )

			assert (
			    str(error.exception   )
			    == "The deprecation tuple ('wrong_arg', '0.0.1', 'message') should be removed since diffusers' version"
			    f""" {__version__} is >= {self.lower_version}"""
			)



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			with self.assertWarns(a_   ) as warning:
				deprecate(('''deprecated_arg''', self.higher_version, '''This message is better!!!''')							,			standard_warn=a_   )

			assert str(warning.warning   ) == "This message is better!!!"



		def 							SCREAMING_SNAKE_CASE    (self   ):





			'''simple docstring'''

			with self.assertWarns(a_   ) as warning:
				deprecate(('''deprecated_arg''', self.higher_version, '''This message is better!!!''')							,			standard_warn=a_   )
			assert str(warning.warning   ) == "This message is better!!!"
			assert "diffusers/tests/others/test_utils.py" in warning.filename





