




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       , UpperCAmelCase_       , UpperCAmelCase_=None       , UpperCAmelCase_=True       , UpperCAmelCase_=None       , **UpperCAmelCase_						):
											lowerCAmelCase   =		parent
											lowerCAmelCase   =		config_class
											lowerCAmelCase   =		has_text_modality
											lowerCAmelCase   =		kwargs
											lowerCAmelCase   =		common_properties



				def       __snake_case		( self						):
											lowerCAmelCase   =		self.config_class(**self.inputs_dict						)
											lowerCAmelCase   =		(
											    ['''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(__snake_case       , __snake_case						)       , msg=F"""`{prop}` does not exist"""						)

											# Test that config has the common properties as setter
											for idx, name in enumerate(__snake_case						):
																		try:
																									setattr(__snake_case       , __snake_case       , __snake_case						)
																									self.parent.assertEqual(
																									    getattr(__snake_case       , __snake_case						)       , __snake_case       , msg=F"""`{name} value {idx} expected, but was {getattr(__snake_case       , __snake_case						)}"""						)
																		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(__snake_case						):
																		try:
																									lowerCAmelCase   =		self.config_class(**{name: idx}						)
																									self.parent.assertEqual(
																									    getattr(__snake_case       , __snake_case						)       , __snake_case       , msg=F"""`{name} value {idx} expected, but was {getattr(__snake_case       , __snake_case						)}"""						)
																		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						):
											lowerCAmelCase   =		self.config_class(**self.inputs_dict						)
											lowerCAmelCase   =		json.loads(config.to_json_string()						)
											for key, value in self.inputs_dict.items():
																		self.parent.assertEqual(obj[key]       , __snake_case						)



				def       __snake_case		( self						):
											lowerCAmelCase   =		self.config_class(**self.inputs_dict						)

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

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



				def       __snake_case		( self						):
											lowerCAmelCase   =		self.config_class(**self.inputs_dict						)

											with tempfile.TemporaryDirectory() as tmpdirname:
																		config_first.save_pretrained(__snake_case						)
																		lowerCAmelCase   =		self.config_class.from_pretrained(__snake_case						)

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



				def       __snake_case		( self						):
											lowerCAmelCase   =		self.config_class(**self.inputs_dict						)

											lowerCAmelCase   =		'''test'''
											with tempfile.TemporaryDirectory() as tmpdirname:
																		lowerCAmelCase   =		os.path.join(__snake_case       , __snake_case						)
																		config_first.save_pretrained(__snake_case						)
																		lowerCAmelCase   =		self.config_class.from_pretrained(__snake_case       , subfolder=__snake_case						)

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



				def       __snake_case		( self						):
											lowerCAmelCase   =		self.config_class(**self.inputs_dict       , num_labels=5						)
											self.parent.assertEqual(len(config.idalabel						)       , 5						)
											self.parent.assertEqual(len(config.labelaid						)       , 5						)

											lowerCAmelCase   =		3
											self.parent.assertEqual(len(config.idalabel						)       , 3						)
											self.parent.assertEqual(len(config.labelaid						)       , 3						)



				def       __snake_case		( self						):
											if self.config_class.is_composition:
																		return
											lowerCAmelCase   =		self.config_class()
											self.parent.assertIsNotNone(__snake_case						)



				def       __snake_case		( self						):
											lowerCAmelCase   =		copy.deepcopy(__snake_case						)
											lowerCAmelCase   =		self.config_class(**__snake_case						)
											lowerCAmelCase   =		[]
											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(__snake_case       , __snake_case						) != value:
																									wrong_values.append((key, getattr(__snake_case       , __snake_case						), value)						)

											if len(__snake_case						) > 0:
																		lowerCAmelCase   =		'''\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						):
											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()





import torch

from diffusers import StableDiffusionPipeline


UpperCAmelCase_						="""path-to-your-trained-model"""
UpperCAmelCase_						=StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")

UpperCAmelCase_						="""A photo of sks dog in a bucket"""
UpperCAmelCase_						=pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]

image.save("""dog-bucket.png""")



