
import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs







class  UpperCamelCase__		(    _a   ):







	'''simple docstring'''





	def __init__(			self				,       UpperCamelCase__				,       UpperCamelCase__=None				,       UpperCamelCase__=True				,       UpperCamelCase__=None				,       **UpperCamelCase__		):
					A__  :	Tuple         =							parent
					A__  :	Optional[Any]         =							config_class
					A__  :	Any         =							has_text_modality
					A__  :	Dict         =							kwargs
					A__  :	Optional[int]         =							common_properties





	def   __snake_case				(			self		):
					A__  :	Optional[Any]         =							self.config_class(**self.inputs_dict		)
					A__  :	Tuple         =							(
					    ['''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(_A				,       _A		)				,       msg=F"`{prop}` does not exist"		)

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





	def   __snake_case				(			self		):
					A__  :	str         =							self.config_class(**self.inputs_dict		)

					with tempfile.TemporaryDirectory() as tmpdirname:
									A__  :	List[str]         =							os.path.join(_A				,       '''config.json'''		)
									config_first.to_json_file(_A		)
									A__  :	Dict         =							self.config_class.from_json_file(_A		)

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





	def   __snake_case				(			self		):
					A__  :	Optional[Any]         =							self.config_class(**self.inputs_dict		)

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

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





	def   __snake_case				(			self		):
					A__  :	List[Any]         =							self.config_class(**self.inputs_dict		)

					A__  :	List[str]         =							'''test'''
					with tempfile.TemporaryDirectory() as tmpdirname:
									A__  :	List[Any]         =							os.path.join(_A				,       _A		)
									config_first.save_pretrained(_A		)
									A__  :	Optional[int]         =							self.config_class.from_pretrained(_A				,       subfolder=_A		)

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





	def   __snake_case				(			self		):
					A__  :	List[Any]         =							self.config_class(**self.inputs_dict				,       num_labels=5		)
					self.parent.assertEqual(len(config.idalabel		)				,       5		)
					self.parent.assertEqual(len(config.labelaid		)				,       5		)

					A__  :	Optional[int]         =							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
					A__  :	int         =							self.config_class()
					self.parent.assertIsNotNone(_A		)





	def   __snake_case				(			self		):
					A__  :	List[str]         =							copy.deepcopy(_A		)
					A__  :	List[str]         =							self.config_class(**_A		)
					A__  :	Dict         =							[]
					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(_A				,       _A		) != value:
													wrong_values.append((key, getattr(_A				,       _A		), value)		)

					if len(_A		) > 0:
									A__  :	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   __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()

from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
					if not (is_transformers_available() and is_torch_available()):
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					from ...utils.dummy_torch_and_transformers_objects import KandinskyPipeline, KandinskyPriorPipeline
else:
					from .pipeline_kandinsky import KandinskyPipeline
					from .pipeline_kandinsky_imgaimg import KandinskyImgaImgPipeline
					from .pipeline_kandinsky_inpaint import KandinskyInpaintPipeline
					from .pipeline_kandinsky_prior import KandinskyPriorPipeline, KandinskyPriorPipelineOutput
					from .text_encoder import MultilingualCLIP