import importlib.metadata
import operator
import re
import sys
from typing import Optional

from packaging import version


SCREAMING_SNAKE_CASE		:     List[str]         =	{
    "<": operator.lt,
    "<=": operator.le,
    "==": operator.eq,
    "!=": operator.ne,
    ">=": operator.ge,
    ">": operator.gt,
}






def     lowerCAmelCase_			(   _SCREAMING_SNAKE_CASE     :				Union[str, Any]		, _SCREAMING_SNAKE_CASE     :				Any		, _SCREAMING_SNAKE_CASE     :				Optional[Any]		, _SCREAMING_SNAKE_CASE     :				int		, _SCREAMING_SNAKE_CASE     :				Any		, _SCREAMING_SNAKE_CASE     :				str			):
						if got_ver is None or want_ver is None:
												raise ValueError(
												    f'''Unable to compare versions for {requirement}: need={want_ver} found={got_ver}. This is unusual. Consider'''
												    f''' reinstalling {pkg}.'''			)
						if not ops[op](version.parse(_SCREAMING_SNAKE_CASE			)		, version.parse(_SCREAMING_SNAKE_CASE			)			):
												raise ImportError(
												    f'''{requirement} is required for a normal functioning of this module, but found {pkg}=={got_ver}.{hint}'''			)






def     lowerCAmelCase_			(   _SCREAMING_SNAKE_CASE     :				str		, _SCREAMING_SNAKE_CASE     :				Optional[str] = None			):
						UpperCamelCase_		:							Optional[int]  =		f'''\n{hint}''' if hint is not None else """"""

						# non-versioned check
						if re.match(R"""^[\w_\-\d]+$"""		, _SCREAMING_SNAKE_CASE			):
												UpperCamelCase_,UpperCamelCase_,UpperCamelCase_		:							List[str]  =		requirement, None, None
						else:
												UpperCamelCase_		:							Tuple  =		re.findall(R"""^([^!=<>\s]+)([\s!=<>]{1,2}.+)"""		, _SCREAMING_SNAKE_CASE			)
												if not match:
																		raise ValueError(
																		    """requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23, but"""
																		    f''' got {requirement}'''			)
												UpperCamelCase_,UpperCamelCase_		:							str  =		match[0]
												UpperCamelCase_		:							Tuple  =		want_full.split(""","""			)  # there could be multiple requirements
												UpperCamelCase_		:							Union[str, Any]  =		{}
												for w in want_range:
																		UpperCamelCase_		:							Optional[int]  =		re.findall(R"""^([\s!=<>]{1,2})(.+)"""		, _SCREAMING_SNAKE_CASE			)
																		if not match:
																								raise ValueError(
																								    """requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23,"""
																								    f''' but got {requirement}'''			)
																		UpperCamelCase_,UpperCamelCase_		:							str  =		match[0]
																		UpperCamelCase_		:							List[str]  =		want_ver
																		if op not in ops:
																								raise ValueError(f'''{requirement}: need one of {list(ops.keys()			)}, but got {op}'''			)

    # special case
						if pkg == "python":
												UpperCamelCase_		:							Any  =		""".""".join([str(_SCREAMING_SNAKE_CASE			) for x in sys.version_info[:3]]			)
												for op, want_ver in wanted.items():
																		_compare_versions(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE			)
												return

						# check if any version is installed
						try:
												UpperCamelCase_		:							List[str]  =		importlib.metadata.version(_SCREAMING_SNAKE_CASE			)
						except importlib.metadata.PackageNotFoundError:
												raise importlib.metadata.PackageNotFoundError(
												    f'''The \'{requirement}\' distribution was not found and is required by this application. {hint}'''			)

						# check that the right version is installed if version number or a range was provided
						if want_ver is not None:
												for op, want_ver in wanted.items():
																		_compare_versions(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE			)







def     lowerCAmelCase_			(   _SCREAMING_SNAKE_CASE     :				Optional[int]			):
						UpperCamelCase_		:							Optional[int]  =		"""Try: pip install transformers -U or pip install -e '.[dev]' if you're working with git main"""
						return require_version(_SCREAMING_SNAKE_CASE		, _SCREAMING_SNAKE_CASE			)







import unittest

import torch

from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow


SCREAMING_SNAKE_CASE		:     List[str]         =	False

class        UpperCamelCase						(				unittest.TestCase				):





						def        A_							(self			,     __UpperCamelCase=32						)				->				Optional[int]:
												set_seed(0						)
												UpperCamelCase_		:							Optional[Any]  =		UNetaDModel(sample_size=__UpperCamelCase			,     in_channels=3			,     out_channels=3						)
												UpperCamelCase_		:							Union[str, Any]  =		torch.optim.SGD(model.parameters()			,     lr=0.0_001						)
												return model, optimizer





						@slow
						def        A_							(self						)				->				str:
												UpperCamelCase_		:							str  =		"""cpu"""  # ensure full determinism without setting the CUBLAS_WORKSPACE_CONFIG env variable
												UpperCamelCase_		:							Tuple  =		DDPMScheduler(
												    num_train_timesteps=1_000			,     beta_start=0.0_001			,     beta_end=0.02			,     beta_schedule="""linear"""			,     clip_sample=__UpperCamelCase			,     )
												UpperCamelCase_		:							List[Any]  =		DDIMScheduler(
												    num_train_timesteps=1_000			,     beta_start=0.0_001			,     beta_end=0.02			,     beta_schedule="""linear"""			,     clip_sample=__UpperCamelCase			,     )

												assert ddpm_scheduler.config.num_train_timesteps == ddim_scheduler.config.num_train_timesteps

												# shared batches for DDPM and DDIM
												set_seed(0						)
												UpperCamelCase_		:							Any  =		[torch.randn((4, 3, 32, 32)						).clip(-1			,     1						).to(__UpperCamelCase						) for _ in range(4						)]
												UpperCamelCase_		:							str  =		[torch.randn((4, 3, 32, 32)						).to(__UpperCamelCase						) for _ in range(4						)]
												UpperCamelCase_		:							Union[str, Any]  =		[torch.randint(0			,     1_000			,     (4,)						).long().to(__UpperCamelCase						) for _ in range(4						)]

												# train with a DDPM scheduler
												UpperCamelCase_,UpperCamelCase_		:							Optional[int]  =		self.get_model_optimizer(resolution=32						)
												model.train().to(__UpperCamelCase						)
												for i in range(4						):
																		optimizer.zero_grad()
																		UpperCamelCase_		:							Optional[Any]  =		ddpm_scheduler.add_noise(clean_images[i]			,     noise[i]			,     timesteps[i]						)
																		UpperCamelCase_		:							List[Any]  =		model(__UpperCamelCase			,     timesteps[i]						).sample
																		UpperCamelCase_		:							Dict  =		torch.nn.functional.mse_loss(__UpperCamelCase			,     noise[i]						)
																		loss.backward()
																		optimizer.step()
												del model, optimizer

												# recreate the model and optimizer, and retry with DDIM
												UpperCamelCase_,UpperCamelCase_		:							Optional[int]  =		self.get_model_optimizer(resolution=32						)
												model.train().to(__UpperCamelCase						)
												for i in range(4						):
																		optimizer.zero_grad()
																		UpperCamelCase_		:							str  =		ddim_scheduler.add_noise(clean_images[i]			,     noise[i]			,     timesteps[i]						)
																		UpperCamelCase_		:							Optional[int]  =		model(__UpperCamelCase			,     timesteps[i]						).sample
																		UpperCamelCase_		:							Union[str, Any]  =		torch.nn.functional.mse_loss(__UpperCamelCase			,     noise[i]						)
																		loss.backward()
																		optimizer.step()
												del model, optimizer

												self.assertTrue(torch.allclose(__UpperCamelCase			,     __UpperCamelCase			,     atol=1E-5						)						)
												self.assertTrue(torch.allclose(__UpperCamelCase			,     __UpperCamelCase			,     atol=1E-5						)						)






