

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 	_A						(					__magic_name__):
  SCREAMING_SNAKE_CASE      : Tuple    =					'''config.json'''

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





        """simple docstring"""







        pass

class 	_A						(					__magic_name__):
  SCREAMING_SNAKE_CASE      : Tuple    =					'''config.json'''

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





        """simple docstring"""







        pass

class 	_A						(					__magic_name__):
  SCREAMING_SNAKE_CASE      : Optional[Any]    =					'''config.json'''

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





        """simple docstring"""







        pass

class 	_A						(					__magic_name__):
  SCREAMING_SNAKE_CASE      : List[Any]    =					'''config.json'''

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





        """simple docstring"""







        pass

class 	_A						(					unittest.TestCase):

  def 	UpperCAmelCase      (			self   ):





        """simple docstring"""







        with self.assertRaises(_SCREAMING_SNAKE_CASE   ):
              ConfigMixin.load_config('dummy_path'   )

  def 	UpperCAmelCase      (			self   ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_			:					List[Any]          =       SampleObject()
        SCREAMING_SNAKE_CASE_			:					Optional[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
        SCREAMING_SNAKE_CASE_			:					Optional[Any]          =       SampleObject(_name_or_path='lalala'   )
        SCREAMING_SNAKE_CASE_			:					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]

        # can override default
        SCREAMING_SNAKE_CASE_			:					Dict          =       SampleObject(c=6   )
        SCREAMING_SNAKE_CASE_			:					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.
        SCREAMING_SNAKE_CASE_			:					int          =       SampleObject(1	,   c=6   )
        SCREAMING_SNAKE_CASE_			:					int          =       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 	UpperCAmelCase      (			self   ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_			:					Optional[Any]          =       SampleObject()
        SCREAMING_SNAKE_CASE_			:					Tuple          =       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(_SCREAMING_SNAKE_CASE   )
              SCREAMING_SNAKE_CASE_			:					int          =       SampleObject.from_config(SampleObject.load_config(_SCREAMING_SNAKE_CASE   )   )
              SCREAMING_SNAKE_CASE_			:					Optional[int]          =       new_obj.config

        # unfreeze configs
        SCREAMING_SNAKE_CASE_			:					Union[str, Any]          =       dict(_SCREAMING_SNAKE_CASE   )
        SCREAMING_SNAKE_CASE_			:					Union[str, Any]          =       dict(_SCREAMING_SNAKE_CASE   )

        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 	UpperCAmelCase      (			self   ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_			:					Optional[int]          =       logging.get_logger('diffusers.configuration_utils'   )
        # 30 for warning
        logger.setLevel(30   )

        with CaptureLogger(_SCREAMING_SNAKE_CASE   ) as cap_logger:
              SCREAMING_SNAKE_CASE_			:					Dict          =       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 	UpperCAmelCase      (			self   ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_			:					Dict          =       logging.get_logger('diffusers.configuration_utils'   )
        # 30 for warning
        logger.setLevel(30   )

        with CaptureLogger(_SCREAMING_SNAKE_CASE   ) as cap_logger:
              SCREAMING_SNAKE_CASE_			:					Optional[Any]          =       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 	UpperCAmelCase      (			self   ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_			:					int          =       logging.get_logger('diffusers.configuration_utils'   )
        # 30 for warning
        logger.setLevel(30   )

        with CaptureLogger(_SCREAMING_SNAKE_CASE   ) as cap_logger:
              SCREAMING_SNAKE_CASE_			:					Optional[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 	UpperCAmelCase      (			self   ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_			:					List[str]          =       logging.get_logger('diffusers.configuration_utils'   )
        # 30 for warning
        logger.setLevel(30   )

        with CaptureLogger(_SCREAMING_SNAKE_CASE   ) as cap_logger:
              SCREAMING_SNAKE_CASE_			:					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 	UpperCAmelCase      (			self   ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_			:					Dict          =       logging.get_logger('diffusers.configuration_utils'   )
        # 30 for warning
        logger.setLevel(30   )

        with CaptureLogger(_SCREAMING_SNAKE_CASE   ) as cap_logger:
              SCREAMING_SNAKE_CASE_			:					Dict          =       DDPMScheduler.from_pretrained(
                  'hf-internal-testing/tiny-stable-diffusion-torch'	,   subfolder='scheduler'	,   prediction_type='sample'	,   beta_end=8	,   )

        with CaptureLogger(_SCREAMING_SNAKE_CASE   ) as cap_logger_a:
              SCREAMING_SNAKE_CASE_			:					List[Any]          =       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 	UpperCAmelCase      (			self   ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_			:					List[Any]          =       logging.get_logger('diffusers.configuration_utils'   )
        # 30 for warning
        logger.setLevel(30   )

        with CaptureLogger(_SCREAMING_SNAKE_CASE   ) as cap_logger:
              SCREAMING_SNAKE_CASE_			:					List[str]          =       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 	UpperCAmelCase      (			self   ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_			:					List[Any]          =       SampleObject()

        SCREAMING_SNAKE_CASE_			:					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(_SCREAMING_SNAKE_CASE   )

              # now loading it with SampleObject2 should put f into `_use_default_values`
              SCREAMING_SNAKE_CASE_			:					Any          =       SampleObjecta.from_config(_SCREAMING_SNAKE_CASE   )

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

        config.config._use_default_values.pop()
        SCREAMING_SNAKE_CASE_			:					Tuple          =       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]









from typing import TYPE_CHECKING

from ...utils import _LazyModule


lowerCAmelCase       :				Tuple         =					{'tokenization_phobert': ['PhobertTokenizer']}


if TYPE_CHECKING:
    from .tokenization_phobert import PhobertTokenizer

else:
    import sys

    lowerCAmelCase       :				Optional[int]         =					_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






