





import tempfile
import unittest

from diffusers import (
    DDIMScheduler,
    DDPMScheduler,
    DPMSolverMultistepScheduler,
    EulerAncestralDiscreteScheduler,
    EulerDiscreteScheduler,
    PNDMScheduler,
    logging,
)
from diffusers.configuration_utils import ConfigMixin, register_to_config
from diffusers.utils.testing_utils import CaptureLogger






class 	UpperCamelCase_     (     snake_case__       ):
     _a			:	str							=				'config.json'



     @register_to_config
     def __init__(		self    :    Dict					,			lowerCamelCase    :    Optional[Any]=2					,			lowerCamelCase    :    Tuple=5					,			lowerCamelCase    :    Union[str, Any]=(2, 5)					,			lowerCamelCase    :    int="for diffusion"					,			lowerCamelCase    :    str=[1, 3]					,			):
       pass






class 	UpperCamelCase_     (     snake_case__       ):
     _a			:	Union[str, Any]							=				'config.json'



     @register_to_config
     def __init__(		self    :    Any					,			lowerCamelCase    :    Dict=2					,			lowerCamelCase    :    Optional[int]=5					,			lowerCamelCase    :    Optional[int]=(2, 5)					,			lowerCamelCase    :    Dict="for diffusion"					,			lowerCamelCase    :    str=[1, 3]					,			):
       pass






class 	UpperCamelCase_     (     snake_case__       ):
     _a			:	Optional[Any]							=				'config.json'



     @register_to_config
     def __init__(		self    :    int					,			lowerCamelCase    :    Optional[Any]=2					,			lowerCamelCase    :    Union[str, Any]=5					,			lowerCamelCase    :    Optional[Any]=(2, 5)					,			lowerCamelCase    :    Union[str, Any]="for diffusion"					,			lowerCamelCase    :    List[Any]=[1, 3]					,			lowerCamelCase    :    List[Any]=[1, 3]					,			):
       pass






class 	UpperCamelCase_     (     snake_case__       ):
     _a			:	Tuple							=				'config.json'



     @register_to_config
     def __init__(		self    :    Optional[int]					,			lowerCamelCase    :    Optional[int]=2					,			lowerCamelCase    :    Optional[int]=5					,			lowerCamelCase    :    str=(2, 5)					,			lowerCamelCase    :    str="for diffusion"					,			lowerCamelCase    :    Union[str, Any]=[1, 5]					,			lowerCamelCase    :    Dict=[5, 4]					,			):
       pass






class 	UpperCamelCase_     (     unittest.TestCase       ):



     def      __a    (		self    :    Tuple	):
       with self.assertRaises(lowerCamelCase	):
         ConfigMixin.load_config('dummy_path'	)



     def      __a    (		self    :    Any	):
       lowerCamelCase_  :    List[Any]   	=			SampleObject()
       lowerCamelCase_  :    Any   	=			obj.config
       assert config["a"] == 2
       assert config["b"] == 5
       assert config["c"] == (2, 5)
       assert config["d"] == "for diffusion"
       assert config["e"] == [1, 3]

       # init ignore private arguments
       lowerCamelCase_  :    Any   	=			SampleObject(_name_or_path='lalala'	)
       lowerCamelCase_  :    int   	=			obj.config
       assert config["a"] == 2
       assert config["b"] == 5
       assert config["c"] == (2, 5)
       assert config["d"] == "for diffusion"
       assert config["e"] == [1, 3]

       # can override default
       lowerCamelCase_  :    Union[str, Any]   	=			SampleObject(c=6	)
       lowerCamelCase_  :    List[Any]   	=			obj.config
       assert config["a"] == 2
       assert config["b"] == 5
       assert config["c"] == 6
       assert config["d"] == "for diffusion"
       assert config["e"] == [1, 3]

       # can use positional arguments.
       lowerCamelCase_  :    Tuple   	=			SampleObject(1					,			c=6	)
       lowerCamelCase_  :    Union[str, Any]   	=			obj.config
       assert config["a"] == 1
       assert config["b"] == 5
       assert config["c"] == 6
       assert config["d"] == "for diffusion"
       assert config["e"] == [1, 3]



     def      __a    (		self    :    List[str]	):
       lowerCamelCase_  :    int   	=			SampleObject()
       lowerCamelCase_  :    str   	=			obj.config

       assert config["a"] == 2
       assert config["b"] == 5
       assert config["c"] == (2, 5)
       assert config["d"] == "for diffusion"
       assert config["e"] == [1, 3]

       with tempfile.TemporaryDirectory() as tmpdirname:
         obj.save_config(lowerCamelCase	)
         lowerCamelCase_  :    str   	=			SampleObject.from_config(SampleObject.load_config(lowerCamelCase	)	)
         lowerCamelCase_  :    Optional[Any]   	=			new_obj.config

       # unfreeze configs
       lowerCamelCase_  :    int   	=			dict(lowerCamelCase	)
       lowerCamelCase_  :    str   	=			dict(lowerCamelCase	)

       assert config.pop('c'	) == (2, 5)  # instantiated as tuple
       assert new_config.pop('c'	) == [2, 5]  # saved & loaded as list because of json
       config.pop('_use_default_values'	)
       assert config == new_config



     def      __a    (		self    :    Optional[int]	):
       lowerCamelCase_  :    List[str]   	=			logging.get_logger('diffusers.configuration_utils'	)
       # 30 for warning
       logger.setLevel(30	)

       with CaptureLogger(lowerCamelCase	) as cap_logger:
         lowerCamelCase_  :    List[str]   	=			DDIMScheduler.from_pretrained(
             'hf-internal-testing/tiny-stable-diffusion-torch'					,			subfolder='scheduler'	)

       assert ddim.__class__ == DDIMScheduler
       # no warning should be thrown
       assert cap_logger.out == ""



     def      __a    (		self    :    List[str]	):
       lowerCamelCase_  :    Optional[Any]   	=			logging.get_logger('diffusers.configuration_utils'	)
       # 30 for warning
       logger.setLevel(30	)

       with CaptureLogger(lowerCamelCase	) as cap_logger:
         lowerCamelCase_  :    List[str]   	=			EulerDiscreteScheduler.from_pretrained(
             'hf-internal-testing/tiny-stable-diffusion-torch'					,			subfolder='scheduler'	)

       assert euler.__class__ == EulerDiscreteScheduler
       # no warning should be thrown
       assert cap_logger.out == ""



     def      __a    (		self    :    int	):
       lowerCamelCase_  :    str   	=			logging.get_logger('diffusers.configuration_utils'	)
       # 30 for warning
       logger.setLevel(30	)

       with CaptureLogger(lowerCamelCase	) as cap_logger:
         lowerCamelCase_  :    List[Any]   	=			EulerAncestralDiscreteScheduler.from_pretrained(
             'hf-internal-testing/tiny-stable-diffusion-torch'					,			subfolder='scheduler'	)

       assert euler.__class__ == EulerAncestralDiscreteScheduler
       # no warning should be thrown
       assert cap_logger.out == ""



     def      __a    (		self    :    List[str]	):
       lowerCamelCase_  :    Optional[int]   	=			logging.get_logger('diffusers.configuration_utils'	)
       # 30 for warning
       logger.setLevel(30	)

       with CaptureLogger(lowerCamelCase	) as cap_logger:
         lowerCamelCase_  :    List[Any]   	=			PNDMScheduler.from_pretrained(
             'hf-internal-testing/tiny-stable-diffusion-torch'					,			subfolder='scheduler'	)

       assert pndm.__class__ == PNDMScheduler
       # no warning should be thrown
       assert cap_logger.out == ""



     def      __a    (		self    :    List[str]	):
       lowerCamelCase_  :    Tuple   	=			logging.get_logger('diffusers.configuration_utils'	)
       # 30 for warning
       logger.setLevel(30	)

       with CaptureLogger(lowerCamelCase	) as cap_logger:
         lowerCamelCase_  :    Optional[Any]   	=			DDPMScheduler.from_pretrained(
             'hf-internal-testing/tiny-stable-diffusion-torch'					,			subfolder='scheduler'					,			prediction_type='sample'					,			beta_end=8					,			)

       with CaptureLogger(lowerCamelCase	) as cap_logger_a:
         lowerCamelCase_  :    Tuple   	=			DDPMScheduler.from_pretrained('google/ddpm-celebahq-256'					,			beta_start=88	)

       assert ddpm.__class__ == DDPMScheduler
       assert ddpm.config.prediction_type == "sample"
       assert ddpm.config.beta_end == 8
       assert ddpm_a.config.beta_start == 88

       # no warning should be thrown
       assert cap_logger.out == ""
       assert cap_logger_a.out == ""



     def      __a    (		self    :    int	):
       lowerCamelCase_  :    Optional[Any]   	=			logging.get_logger('diffusers.configuration_utils'	)
       # 30 for warning
       logger.setLevel(30	)

       with CaptureLogger(lowerCamelCase	) as cap_logger:
         lowerCamelCase_  :    Optional[Any]   	=			DPMSolverMultistepScheduler.from_pretrained(
             'hf-internal-testing/tiny-stable-diffusion-torch'					,			subfolder='scheduler'	)

       assert dpm.__class__ == DPMSolverMultistepScheduler
       # no warning should be thrown
       assert cap_logger.out == ""





     def      __a    (		self    :    Dict	):
       # let's first save a config that should be in the form
       #    a=2,
       #    b=5,
       #    c=(2, 5),
       #    d="for diffusion",
       #    e=[1, 3],

       lowerCamelCase_  :    Optional[Any]   	=			SampleObject()

       lowerCamelCase_  :    str   	=			{k: v for k, v in config.config.items() if not k.startswith('_'	)}

       # make sure that default config has all keys in `_use_default_values`
       assert set(config_dict.keys()	) == set(config.config._use_default_values	)

       with tempfile.TemporaryDirectory() as tmpdirname:
         config.save_config(lowerCamelCase	)

         # now loading it with SampleObject2 should put f into `_use_default_values`
         lowerCamelCase_  :    Optional[Any]   	=			SampleObjecta.from_config(lowerCamelCase	)

         assert "f" in config._use_default_values
         assert config.f == [1, 3]

       # now loading the config, should **NOT** use [1, 3] for `f`, but the default [1, 4] value
       # **BECAUSE** it is part of `config._use_default_values`
       lowerCamelCase_  :    Union[str, Any]   	=			SampleObjecta.from_config(config.config	)
       assert new_config.f == [5, 4]

       config.config._use_default_values.pop()
       lowerCamelCase_  :    Optional[Any]   	=			SampleObjecta.from_config(config.config	)
       assert new_config_a.f == [1, 3]

       # Nevertheless "e" should still be correctly loaded to [1, 3] from SampleObject2 instead of defaulting to [1, 5]
       assert new_config_a.e == [1, 3]







import os
import unittest

import pytest
from parameterized import parameterized

from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device


# skipping in unittest tests

_lowercase		:     Optional[Any] 					=[(1,)]


def 		_SCREAMING_SNAKE_CASE    (   ):
		lowerCamelCase_  :    Union[str, Any]   	=			bool(os.getenv('RUN_SLOW'       ,0	)	)
		if run_slow:
				assert True
		else:
				assert False, "should have been skipped"


def 		_SCREAMING_SNAKE_CASE    (   ):
		lowerCamelCase_  :    List[str]   	=			bool(os.getenv('RUN_SLOW'       ,0	)	)
		if run_slow and torch_device == "cuda":
				assert True
		else:
				assert False, "should have been skipped"






@require_torch
class 	UpperCamelCase_     (     unittest.TestCase       ):



					@slow
					@require_torch_gpu
					def      __a    (		self    :    Tuple	):
							check_slow_torch_cuda()



					@require_torch_gpu
					@slow
					def      __a    (		self    :    Optional[int]	):
							check_slow_torch_cuda()





					@parameterized.expand(lowerCamelCase	)
					@slow
					def      __a    (		self    :    List[str]					,			lowerCamelCase    :    Optional[Any]=None	):
							check_slow()


@slow
@require_torch_gpu
def 		_SCREAMING_SNAKE_CASE    (   ):
		check_slow_torch_cuda()


@require_torch_gpu
@slow
def 		_SCREAMING_SNAKE_CASE    (   ):
		check_slow_torch_cuda()


@slow
@pytest.mark.parametrize('param'       ,[1]	)
def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
		check_slow()





@pytest.mark.parametrize('param'       ,[1]	)
@slow
def 		_SCREAMING_SNAKE_CASE    (   lowerCAmelCase__	):
		check_slow()
