

"""simple docstring"""

import enum
import inspect
import warnings
from functools import wraps
from typing import Callable, Optional

from .logging import get_logger


_UpperCamelCase		    =						set()
_UpperCamelCase		    =						get_logger(__name__)



def 			SCREAMING_SNAKE_CASE       (   lowercase__ = None      ) ->	Optional[Any]:

	def decorator(lowercase__      ):
		global _emitted_deprecation_warnings

		if inspect.isclass(_UpperCAmelCase      ):
			lowerCAmelCase__      :							Union[str, Any]    =							deprecated_class_or_function.__init__
			lowerCAmelCase__      :							str    =							deprecated_class_or_function.__name__
		else:
			lowerCAmelCase__      :							Optional[Any]    =							deprecated_class_or_function
			lowerCAmelCase__      :							Any    =							deprecated_function.__name__
			# Support deprecating __init__ class method: class name instead
			lowerCAmelCase__      :							List[str]    =							name if name != "__init__" else deprecated_function.__qualname__.split("."      )[-2]

		lowerCAmelCase__      :							Union[str, Any]    =							(
		    F"""{name} is deprecated and will be removed in the next major version of datasets.""" + F""" {help_message}"""
		    if help_message
		    else ""
		)

		@wraps(_UpperCAmelCase      )
		def wrapper(*lowercase__				,				**lowercase__      ):
			lowerCAmelCase__      :							str    =							hash(_UpperCAmelCase      )
			if func_hash not in _emitted_deprecation_warnings:
				warnings.warn(_UpperCAmelCase				,				category=_UpperCAmelCase				,				stacklevel=2      )
				_emitted_deprecation_warnings.add(_UpperCAmelCase      )
			return deprecated_function(*_UpperCAmelCase				,				**_UpperCAmelCase      )

		lowerCAmelCase__      :							str    =							"deprecated"

		if inspect.isclass(_UpperCAmelCase      ):
			lowerCAmelCase__      :							Union[str, Any]    =							wrapper
			return deprecated_class_or_function
		else:
			return wrapper

	return decorator






class  __a				(	enum.EnumMeta					):





							"""simple docstring"""


							def __getattribute__(      cls ,				snake_case      ):





								"""simple docstring"""

								lowerCAmelCase__      :							Dict    =							super().__getattribute__(SCREAMING_SNAKE_CASE_      )
								if isinstance(SCREAMING_SNAKE_CASE_ ,				enum.Enum      ) and obj._on_access:
									obj._on_access()
								return obj






							def __getitem__(      cls ,				snake_case      ):





								"""simple docstring"""

								lowerCAmelCase__      :							Tuple    =							super().__getitem__(SCREAMING_SNAKE_CASE_      )
								if member._on_access:
									member._on_access()
								return member






							def __call__(      cls ,				snake_case ,				snake_case=None ,				*, snake_case=None ,				snake_case=None ,				snake_case=None ,				snake_case=1      ):





								"""simple docstring"""

								lowerCAmelCase__      :							Union[str, Any]    =							super().__call__(SCREAMING_SNAKE_CASE_ ,				SCREAMING_SNAKE_CASE_ ,				module=SCREAMING_SNAKE_CASE_ ,				qualname=SCREAMING_SNAKE_CASE_ ,				type=SCREAMING_SNAKE_CASE_ ,				start=SCREAMING_SNAKE_CASE_      )
								if isinstance(SCREAMING_SNAKE_CASE_ ,				enum.Enum      ) and obj._on_access:
									obj._on_access()
								return obj






class  __a				(	enum.Enum					,  metaclass=lowerCamelCase__					):





							"""simple docstring"""


							def __new__(      cls ,				snake_case      ):





								"""simple docstring"""

								lowerCAmelCase__      :							List[str]    =							object.__new__(cls      )
								lowerCAmelCase__      :							List[str]    =							value
								lowerCAmelCase__      :							List[str]    =							member.deprecate
								return member






							@property
							def  SCREAMING_SNAKE_CASE_  (      self      ):





								"""simple docstring"""

								return ""






							def  SCREAMING_SNAKE_CASE_  (      self      ):





								"""simple docstring"""

								lowerCAmelCase__      :							Any    =							F""" {self.help_message}""" if self.help_message else ""
								warnings.warn(
								    F"""'{self.__objclass__.__name__}' is deprecated and will be removed in the next major version of datasets."""
								    + help_message ,				SCREAMING_SNAKE_CASE_ ,				stacklevel=3 ,				)









"""simple docstring"""

import torch
import torch.nn.functional as F

from diffusers import VQDiffusionScheduler

from .test_schedulers import SchedulerCommonTest






class  __a				(	__magic_name__					):





       """simple docstring"""


       __UpperCamelCase				:			Optional[int]          =	(VQDiffusionScheduler,)






       def  SCREAMING_SNAKE_CASE_  (      self ,				**snake_case      ):





        """simple docstring"""

        lowerCAmelCase__      :							str    =							{
            "num_vec_classes": 4_097,
            "num_train_timesteps": 100,
        }

        config.update(**snake_case      )
        return config






       def  SCREAMING_SNAKE_CASE_  (      self ,				snake_case      ):





        """simple docstring"""

        lowerCAmelCase__      :							Optional[int]    =							4
        lowerCAmelCase__      :							Optional[Any]    =							8
        lowerCAmelCase__      :							Union[str, Any]    =							8

        lowerCAmelCase__      :							Optional[Any]    =							torch.randint(0 ,				snake_case ,				(batch_size, height * width)      )

        return sample






       @property
       def  SCREAMING_SNAKE_CASE_  (      self      ):





        """simple docstring"""

        assert False






       def  SCREAMING_SNAKE_CASE_  (      self ,				snake_case      ):





        """simple docstring"""

        def model(snake_case ,				snake_case ,				*snake_case      ):
         lowerCAmelCase__ ,	lowerCAmelCase__      :							str    =							sample.shape
         lowerCAmelCase__      :							Dict    =							torch.rand((batch_size, num_vec_classes - 1, num_latent_pixels)      )
         lowerCAmelCase__      :							int    =							F.log_softmax(logits.double() ,				dim=1      ).float()
         return return_value

        return model






       def  SCREAMING_SNAKE_CASE_  (      self      ):





        """simple docstring"""

        for timesteps in [2, 5, 100, 1_000]:
         self.check_over_configs(num_train_timesteps=snake_case      )






       def  SCREAMING_SNAKE_CASE_  (      self      ):





        """simple docstring"""

        for num_vec_classes in [5, 100, 1_000, 4_000]:
         self.check_over_configs(num_vec_classes=snake_case      )






       def  SCREAMING_SNAKE_CASE_  (      self      ):





        """simple docstring"""

        for t in [0, 50, 99]:
         self.check_over_forward(time_step=snake_case      )






       def  SCREAMING_SNAKE_CASE_  (      self      ):





        """simple docstring"""

        pass






