'''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 				UpperCAmelCase (       _SCREAMING_SNAKE_CASE ):




				'''simple docstring'''







				def __init__(       self    ,							lowercase__    ,							lowercase__=None    ,							lowercase__=True    ,							lowercase__=None    ,							**lowercase__ )							-> Optional[Any]:
									SCREAMING_SNAKE_CASE					:			int    	=       parent
									SCREAMING_SNAKE_CASE					:			str    	=       config_class
									SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       has_text_modality
									SCREAMING_SNAKE_CASE					:			Any    	=       kwargs
									SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       common_properties






				def       _UpperCamelCase    (       self )							-> Union[str, Any]:
									SCREAMING_SNAKE_CASE					:			Optional[int]    	=       self.config_class(**self.inputs_dict )
									SCREAMING_SNAKE_CASE					:			int    	=       (
									    ['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(lowercase__    ,							lowercase__ )    ,							msg=F"""`{prop}` does not exist""" )

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






				def       _UpperCamelCase    (       self )							-> List[str]:
									SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       self.config_class(**self.inputs_dict )
									SCREAMING_SNAKE_CASE					:			Any    	=       json.loads(config.to_json_string() )
									for key, value in self.inputs_dict.items():
														self.parent.assertEqual(obj[key]    ,							lowercase__ )






				def       _UpperCamelCase    (       self )							-> Optional[int]:
									SCREAMING_SNAKE_CASE					:			Tuple    	=       self.config_class(**self.inputs_dict )

									with tempfile.TemporaryDirectory() as tmpdirname:
														SCREAMING_SNAKE_CASE					:			List[str]    	=       os.path.join(lowercase__    ,							'config.json' )
														config_first.to_json_file(lowercase__ )
														SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       self.config_class.from_json_file(lowercase__ )

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






				def       _UpperCamelCase    (       self )							-> Dict:
									SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       self.config_class(**self.inputs_dict )

									with tempfile.TemporaryDirectory() as tmpdirname:
														config_first.save_pretrained(lowercase__ )
														SCREAMING_SNAKE_CASE					:			Optional[int]    	=       self.config_class.from_pretrained(lowercase__ )

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






				def       _UpperCamelCase    (       self )							-> int:
									SCREAMING_SNAKE_CASE					:			List[Any]    	=       self.config_class(**self.inputs_dict )

									SCREAMING_SNAKE_CASE					:			Optional[int]    	=       'test'
									with tempfile.TemporaryDirectory() as tmpdirname:
														SCREAMING_SNAKE_CASE					:			Tuple    	=       os.path.join(lowercase__    ,							lowercase__ )
														config_first.save_pretrained(lowercase__ )
														SCREAMING_SNAKE_CASE					:			Dict    	=       self.config_class.from_pretrained(lowercase__    ,							subfolder=lowercase__ )

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






				def       _UpperCamelCase    (       self )							-> List[Any]:
									SCREAMING_SNAKE_CASE					:			Dict    	=       self.config_class(**self.inputs_dict    ,							num_labels=5 )
									self.parent.assertEqual(len(config.idalabel )    ,							5 )
									self.parent.assertEqual(len(config.labelaid )    ,							5 )

									SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       3
									self.parent.assertEqual(len(config.idalabel )    ,							3 )
									self.parent.assertEqual(len(config.labelaid )    ,							3 )






				def       _UpperCamelCase    (       self )							-> Dict:
									if self.config_class.is_composition:
														return
									SCREAMING_SNAKE_CASE					:			int    	=       self.config_class()
									self.parent.assertIsNotNone(lowercase__ )






				def       _UpperCamelCase    (       self )							-> Tuple:
									SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       copy.deepcopy(lowercase__ )
									SCREAMING_SNAKE_CASE					:			Any    	=       self.config_class(**lowercase__ )
									SCREAMING_SNAKE_CASE					:			str    	=       []
									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(lowercase__    ,							lowercase__ ) != value:
																			wrong_values.append((key, getattr(lowercase__    ,							lowercase__ ), value) )

									if len(lowercase__ ) > 0:
														SCREAMING_SNAKE_CASE					:			List[Any]    	=       '\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       _UpperCamelCase    (       self )							-> Optional[int]:
									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 gc
import tempfile
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device


_lowerCAmelCase  :List[Any]  				=    False






class 				UpperCAmelCase (       unittest.TestCase ):




    '''simple docstring'''







    pass






@nightly
@require_torch_gpu
class 				UpperCAmelCase (       unittest.TestCase ):




    '''simple docstring'''







    def       _UpperCamelCase    (       self )							-> Any:
         # clean up the VRAM after each test
         super().tearDown()
         gc.collect()
         torch.cuda.empty_cache()






    def       _UpperCamelCase    (       self )							-> Tuple:
         SCREAMING_SNAKE_CASE					:			Dict    	=       VersatileDiffusionTextToImagePipeline.from_pretrained('shi-labs/versatile-diffusion' )
         # remove text_unet
         pipe.remove_unused_weights()
         pipe.to(lowercase__ )
         pipe.set_progress_bar_config(disable=lowercase__ )

         SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       'A painting of a squirrel eating a burger '
         SCREAMING_SNAKE_CASE					:			List[Any]    	=       torch.manual_seed(0 )
         SCREAMING_SNAKE_CASE					:			Union[str, Any]    	=       pipe(
             prompt=lowercase__    ,							generator=lowercase__    ,							guidance_scale=7.5    ,							num_inference_steps=2    ,							output_type='numpy' ).images

         with tempfile.TemporaryDirectory() as tmpdirname:
              pipe.save_pretrained(lowercase__ )
              SCREAMING_SNAKE_CASE					:			int    	=       VersatileDiffusionTextToImagePipeline.from_pretrained(lowercase__ )
         pipe.to(lowercase__ )
         pipe.set_progress_bar_config(disable=lowercase__ )

         SCREAMING_SNAKE_CASE					:			List[str]    	=       generator.manual_seed(0 )
         SCREAMING_SNAKE_CASE					:			List[str]    	=       pipe(
             prompt=lowercase__    ,							generator=lowercase__    ,							guidance_scale=7.5    ,							num_inference_steps=2    ,							output_type='numpy' ).images

         assert np.abs(image - new_image ).sum() < 1E-5, "Models don't have the same forward pass"






    def       _UpperCamelCase    (       self )							-> Any:
         SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       VersatileDiffusionTextToImagePipeline.from_pretrained(
             'shi-labs/versatile-diffusion'    ,							torch_dtype=torch.floataa )
         pipe.to(lowercase__ )
         pipe.set_progress_bar_config(disable=lowercase__ )

         SCREAMING_SNAKE_CASE					:			int    	=       'A painting of a squirrel eating a burger '
         SCREAMING_SNAKE_CASE					:			Tuple    	=       torch.manual_seed(0 )
         SCREAMING_SNAKE_CASE					:			Tuple    	=       pipe(
             prompt=lowercase__    ,							generator=lowercase__    ,							guidance_scale=7.5    ,							num_inference_steps=50    ,							output_type='numpy' ).images

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

         assert image.shape == (1, 512, 512, 3)
         SCREAMING_SNAKE_CASE					:			Optional[Any]    	=       np.array([0.3_3_6_7, 0.3_1_6_9, 0.2_6_5_6, 0.3_8_7_0, 0.4_7_9_0, 0.3_7_9_6, 0.4_0_0_9, 0.4_8_7_8, 0.4_7_7_8] )

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



