



"""simple docstring"""






import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs

class 	__SCREAMING_SNAKE_CASE     (				lowerCAmelCase_       ):


					'''simple docstring'''





					def __init__(	self							:  str,  lowerCamelCase							:  Union[str, Any],  lowerCamelCase							:  Dict=None,  lowerCamelCase							:  int=True,  lowerCamelCase							:  Optional[Any]=None,  **lowerCamelCase							:  Optional[Any]					)-> Optional[int]:
								lowerCamelCase__		:		Tuple		     =parent
								lowerCamelCase__		:		Union[str, Any]		     =config_class
								lowerCamelCase__		:		str		     =has_text_modality
								lowerCamelCase__		:		Any		     =kwargs
								lowerCamelCase__		:		List[str]		     =common_properties



					def 		snake_case	(	self							:  Dict					)-> str:
								lowerCamelCase__		:		int		     =self.config_class(**self.inputs_dict					)
								lowerCamelCase__		:		str		     =(
								    ['''hidden_size''', '''num_attention_heads''', '''num_hidden_layers''']
								    if self.common_properties is None
								    else self.common_properties
								)

								# Add common fields for text models
								if self.has_text_modality:
											common_properties.extend(['''vocab_size''']					)

								# Test that config has the common properties as getters
								for prop in common_properties:
											self.parent.assertTrue(hasattr(lowerCamelCase,  lowerCamelCase					),  msg=F'''`{prop}` does not exist'''					)

								# Test that config has the common properties as setter
								for idx, name in enumerate(lowerCamelCase					):
											try:
														setattr(lowerCamelCase,  lowerCamelCase,  lowerCamelCase					)
														self.parent.assertEqual(
														    getattr(lowerCamelCase,  lowerCamelCase					),  lowerCamelCase,  msg=F'''`{name} value {idx} expected, but was {getattr(lowerCamelCase,  lowerCamelCase					)}'''					)
											except NotImplementedError:
														# Some models might not be able to implement setters for common_properties
														# In that case, a NotImplementedError is raised
														pass

        # Test if config class can be called with Config(prop_name=..)
								for idx, name in enumerate(lowerCamelCase					):
											try:
														lowerCamelCase__		:		Tuple		     =self.config_class(**{name: idx}					)
														self.parent.assertEqual(
														    getattr(lowerCamelCase,  lowerCamelCase					),  lowerCamelCase,  msg=F'''`{name} value {idx} expected, but was {getattr(lowerCamelCase,  lowerCamelCase					)}'''					)
											except NotImplementedError:
														# Some models might not be able to implement setters for common_properties
														# In that case, a NotImplementedError is raised
														pass



					def 		snake_case	(	self							:  str					)-> Union[str, Any]:
								lowerCamelCase__		:		Dict		     =self.config_class(**self.inputs_dict					)
								lowerCamelCase__		:		Optional[int]		     =json.loads(config.to_json_string()					)
								for key, value in self.inputs_dict.items():
											self.parent.assertEqual(obj[key],  lowerCamelCase					)



					def 		snake_case	(	self							:  Tuple					)-> Union[str, Any]:
								lowerCamelCase__		:		Optional[int]		     =self.config_class(**self.inputs_dict					)

								with tempfile.TemporaryDirectory() as tmpdirname:
											lowerCamelCase__		:		Tuple		     =os.path.join(lowerCamelCase,  '''config.json'''					)
											config_first.to_json_file(lowerCamelCase					)
											lowerCamelCase__		:		Tuple		     =self.config_class.from_json_file(lowerCamelCase					)

								self.parent.assertEqual(config_second.to_dict(),  config_first.to_dict()					)



					def 		snake_case	(	self							:  Optional[int]					)-> List[Any]:
								lowerCamelCase__		:		Optional[int]		     =self.config_class(**self.inputs_dict					)

								with tempfile.TemporaryDirectory() as tmpdirname:
											config_first.save_pretrained(lowerCamelCase					)
											lowerCamelCase__		:		Tuple		     =self.config_class.from_pretrained(lowerCamelCase					)

								self.parent.assertEqual(config_second.to_dict(),  config_first.to_dict()					)



					def 		snake_case	(	self							:  Union[str, Any]					)-> Any:
								lowerCamelCase__		:		Dict		     =self.config_class(**self.inputs_dict					)

								lowerCamelCase__		:		int		     ='''test'''
								with tempfile.TemporaryDirectory() as tmpdirname:
											lowerCamelCase__		:		Union[str, Any]		     =os.path.join(lowerCamelCase,  lowerCamelCase					)
											config_first.save_pretrained(lowerCamelCase					)
											lowerCamelCase__		:		int		     =self.config_class.from_pretrained(lowerCamelCase,  subfolder=lowerCamelCase					)

								self.parent.assertEqual(config_second.to_dict(),  config_first.to_dict()					)



					def 		snake_case	(	self							:  str					)-> Tuple:
								lowerCamelCase__		:		int		     =self.config_class(**self.inputs_dict,  num_labels=5					)
								self.parent.assertEqual(len(config.idalabel					),  5					)
								self.parent.assertEqual(len(config.labelaid					),  5					)

								lowerCamelCase__		:		List[Any]		     =3
								self.parent.assertEqual(len(config.idalabel					),  3					)
								self.parent.assertEqual(len(config.labelaid					),  3					)



					def 		snake_case	(	self							:  Optional[int]					)-> int:
								if self.config_class.is_composition:
											return
								lowerCamelCase__		:		Union[str, Any]		     =self.config_class()
								self.parent.assertIsNotNone(lowerCamelCase					)



					def 		snake_case	(	self							:  Optional[int]					)-> str:
								lowerCamelCase__		:		Optional[Any]		     =copy.deepcopy(lowerCamelCase					)
								lowerCamelCase__		:		List[Any]		     =self.config_class(**lowerCamelCase					)
								lowerCamelCase__		:		Tuple		     =[]
								for key, value in config_common_kwargs.items():
											if key == "torch_dtype":
														if not is_torch_available():
																	continue
														else:
																	import torch

																	if config.torch_dtype != torch.floataa:
																				wrong_values.append(('''torch_dtype''', config.torch_dtype, torch.floataa)					)
											elif getattr(lowerCamelCase,  lowerCamelCase					) != value:
														wrong_values.append((key, getattr(lowerCamelCase,  lowerCamelCase					), value)					)

								if len(lowerCamelCase					) > 0:
											lowerCamelCase__		:		Optional[int]		     ='''\n'''.join([F'''- {v[0]}: got {v[1]} instead of {v[2]}''' for v in wrong_values]					)
											raise ValueError(F'''The following keys were not properly set in the config:\n{errors}'''					)




					def 		snake_case	(	self							:  List[Any]					)-> str:
								self.create_and_test_config_common_properties()
								self.create_and_test_config_to_json_string()
								self.create_and_test_config_to_json_file()
								self.create_and_test_config_from_and_save_pretrained()
								self.create_and_test_config_from_and_save_pretrained_subfolder()
								self.create_and_test_config_with_num_labels()
								self.check_config_can_be_init_without_params()
								self.check_config_arguments_init()









"""simple docstring"""






import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


_lowercase			:			Tuple										=						False

class 	__SCREAMING_SNAKE_CASE     (				unittest.TestCase       ):


					'''simple docstring'''





					pass





@slow
@require_torch_gpu
class 	__SCREAMING_SNAKE_CASE     (				unittest.TestCase       ):


					'''simple docstring'''





					def 		snake_case	(	self							:  List[Any]					)-> Dict:
								lowerCamelCase__		:		str		     =VersatileDiffusionImageVariationPipeline.from_pretrained('''shi-labs/versatile-diffusion'''					)
								pipe.to(lowerCamelCase					)
								pipe.set_progress_bar_config(disable=lowerCamelCase					)

								lowerCamelCase__		:		int		     =load_image(
								    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg'''					)
								lowerCamelCase__		:		Dict		     =torch.manual_seed(0					)
								lowerCamelCase__		:		str		     =pipe(
								    image=lowerCamelCase,  generator=lowerCamelCase,  guidance_scale=7.5,  num_inference_steps=50,  output_type='''numpy''',  ).images

								lowerCamelCase__		:		Dict		     =image[0, 253:256, 253:256, -1]

								assert image.shape == (1, 512, 512, 3)
								lowerCamelCase__		:		List[Any]		     =np.array([0.0_441, 0.0_469, 0.0_507, 0.0_575, 0.0_632, 0.0_650, 0.0_865, 0.0_909, 0.0_945]					)

								assert np.abs(image_slice.flatten() - expected_slice					).max() < 1E-2




