



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 			__snake_case   ( SCREAMING_SNAKE_CASE):







							'''simple docstring'''






							UpperCamelCase__					:   List[str]       =       """config.json"""


							@register_to_config
							def __init__(				self	,	a_=2	,	a_=5	,	a_=(2, 5)	,	a_="for diffusion"	,	a_=[1, 3]	,	):
											pass




class 			__snake_case   ( SCREAMING_SNAKE_CASE):







							'''simple docstring'''






							UpperCamelCase__					:   List[Any]       =       """config.json"""


							@register_to_config
							def __init__(				self	,	a_=2	,	a_=5	,	a_=(2, 5)	,	a_="for diffusion"	,	a_=[1, 3]	,	):
											pass




class 			__snake_case   ( SCREAMING_SNAKE_CASE):







							'''simple docstring'''






							UpperCamelCase__					:   List[Any]       =       """config.json"""


							@register_to_config
							def __init__(				self	,	a_=2	,	a_=5	,	a_=(2, 5)	,	a_="for diffusion"	,	a_=[1, 3]	,	a_=[1, 3]	,	):
											pass




class 			__snake_case   ( SCREAMING_SNAKE_CASE):







							'''simple docstring'''






							UpperCamelCase__					:   Tuple       =       """config.json"""


							@register_to_config
							def __init__(				self	,	a_=2	,	a_=5	,	a_=(2, 5)	,	a_="for diffusion"	,	a_=[1, 5]	,	a_=[5, 4]	,	):
											pass




class 			__snake_case   ( unittest.TestCase):







							'''simple docstring'''






							def _a   (				self		):




											with self.assertRaises(a_		):
															ConfigMixin.load_config("""dummy_path"""		)


							def _a   (				self		):
											a__					   =		SampleObject()
											a__					   =		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
											a__					   =		SampleObject(_name_or_path="""lalala"""		)
											a__					   =		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
											a__					   =		SampleObject(c=6		)
											a__					   =		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.
											a__					   =		SampleObject(1	,	c=6		)
											a__					   =		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		):
											a__					   =		SampleObject()
											a__					   =		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(a_		)
															a__					   =		SampleObject.from_config(SampleObject.load_config(a_		)		)
															a__					   =		new_obj.config

											# unfreeze configs
											a__					   =		dict(a_		)
											a__					   =		dict(a_		)

											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		):
											a__					   =		logging.get_logger("""diffusers.configuration_utils"""		)
											# 30 for warning
											logger.setLevel(30		)

											with CaptureLogger(a_		) as cap_logger:
															a__					   =		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		):
											a__					   =		logging.get_logger("""diffusers.configuration_utils"""		)
											# 30 for warning
											logger.setLevel(30		)

											with CaptureLogger(a_		) as cap_logger:
															a__					   =		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		):
											a__					   =		logging.get_logger("""diffusers.configuration_utils"""		)
											# 30 for warning
											logger.setLevel(30		)

											with CaptureLogger(a_		) as cap_logger:
															a__					   =		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		):
											a__					   =		logging.get_logger("""diffusers.configuration_utils"""		)
											# 30 for warning
											logger.setLevel(30		)

											with CaptureLogger(a_		) as cap_logger:
															a__					   =		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		):
											a__					   =		logging.get_logger("""diffusers.configuration_utils"""		)
											# 30 for warning
											logger.setLevel(30		)

											with CaptureLogger(a_		) as cap_logger:
															a__					   =		DDPMScheduler.from_pretrained(
															    """hf-internal-testing/tiny-stable-diffusion-torch"""	,	subfolder="""scheduler"""	,	prediction_type="""sample"""	,	beta_end=8	,	)

											with CaptureLogger(a_		) as cap_logger_a:
															a__					   =		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		):
											a__					   =		logging.get_logger("""diffusers.configuration_utils"""		)
											# 30 for warning
											logger.setLevel(30		)

											with CaptureLogger(a_		) as cap_logger:
															a__					   =		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		):
											a__					   =		SampleObject()

											a__					   =		{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(a_		)

															# now loading it with SampleObject2 should put f into `_use_default_values`
															a__					   =		SampleObjecta.from_config(a_		)

															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`
											a__					   =		SampleObjecta.from_config(config.config		)
											assert new_config.f == [5, 4]

											config.config._use_default_values.pop()
											a__					   =		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]









"""simple docstring"""


import json

import requests

from .fetch_github_info import AUTHENTICATED_USER_ENDPOINT, fetch_github_info




def      snake_case    (A_ :Union[str, Any] ):







  '''simple docstring'''

  class 		snake_case    :





      def __init__(				self      :   Tuple							,						A      :   Dict     ):


        '''simple docstring'''




        assert isinstance(A							,						(bytes, str)     )
        a	:     Union[str, Any]							=  content





      def 							lowerCamelCase__ (				self      :   str     ):


        '''simple docstring'''




        return json.loads(self.content     )

  def mock_response(*A_ :Union[str, Any]      ,     **A_ :Tuple ):
    assert args[0] == AUTHENTICATED_USER_ENDPOINT
    assert "Authorization" in kwargs["headers"]
    assert kwargs["headers"]["Authorization"].startswith('token ' )
    assert "Accept" in kwargs["headers"]
    return FakeResponse(B'{"login":"test","id":1}' )

  monkeypatch.setattr(A_      ,     'get'      ,     A_ )
  a	:     List[str]							=  fetch_github_info('token' )
  assert result["login"] == "test"
  assert result["id"] == 1




