


'''simple docstring'''

# limitations under the License.


from typing import Optional, Tuple, Union

import torch

from diffusers import DiffusionPipeline, ImagePipelineOutput


class       a__				( __A      ):







				"""simple docstring"""



				def __init__(self       ,			__lowercase       ,			__lowercase		):
										super().__init__()
										self.register_modules(unet=__lowercase       ,			scheduler=__lowercase		)




				@torch.no_grad()
				def __call__(self       ,			__lowercase = 1       ,			__lowercase = None       ,			__lowercase = 50       ,			__lowercase = "pil"       ,			__lowercase = True       ,			**__lowercase       ,			):
										__lowerCAmelCase							       =				torch.randn(
										    (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)       ,			generator=__lowercase       ,			)
										__lowerCAmelCase							       =				image.to(self.device		)

										# set step values
										self.scheduler.set_timesteps(__lowercase		)

										for t in self.progress_bar(self.scheduler.timesteps		):
																# 1. predict noise model_output
																__lowerCAmelCase							       =				self.unet(__lowercase       ,			__lowercase		).sample

																# 2. predict previous mean of image x_t-1 and add variance depending on eta
																# eta corresponds to η in paper and should be between [0, 1]
																# do x_t -> x_t-1
																__lowerCAmelCase							       =				self.scheduler.step(__lowercase       ,			__lowercase       ,			__lowercase		).prev_sample

										__lowerCAmelCase							       =				(image / 2 + 0.5).clamp(0       ,			1		)
										__lowerCAmelCase							       =				image.cpu().permute(0       ,			2       ,			3       ,			1		).numpy()
										if output_type == "pil":
																__lowerCAmelCase							       =				self.numpy_to_pil(__lowercase		)

										if not return_dict:
																return (image,), "This is a local test"

										return ImagePipelineOutput(images=__lowercase		), "This is a local test"





'''simple docstring'''

import sys

from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core


# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers

_UpperCAmelCase				: Tuple							    =				"""python tqdm regex requests packaging filelock numpy tokenizers""".split()
if sys.version_info < (3, 7):
	pkgs_to_check_at_runtime.append("""dataclasses""")
if sys.version_info < (3, 8):
	pkgs_to_check_at_runtime.append("""importlib_metadata""")

for pkg in pkgs_to_check_at_runtime:
	if pkg in deps:
		if pkg == "tokenizers":
			# must be loaded here, or else tqdm check may fail
			from .utils import is_tokenizers_available

			if not is_tokenizers_available():
				continue  # not required, check version only if installed

		require_version_core(deps[pkg])
	else:
		raise ValueError(f"""can't find {pkg} in {deps.keys()}, check dependency_versions_table.py""")

def 							__magic_name__(						lowerCamelCase,				lowerCamelCase=None):
						require_version(deps[pkg],				lowerCamelCase)

