





'''simple docstring'''







from collections import OrderedDict
from dataclasses import fields
from typing import Any, Tuple

import numpy as np

from .import_utils import is_torch_available





def     lowerCamelCase_ (					SCREAMING_SNAKE_CASE__ :     Union[str, Any]				)	->		Optional[Any]:
						if is_torch_available():
												import torch

												if isinstance(SCREAMING_SNAKE_CASE__,     torch.Tensor				):
																		return True

						return isinstance(SCREAMING_SNAKE_CASE__,     np.ndarray				)


class    __a (lowerCamelCase       ):

							def       UpperCAmelCase__		(							self							:       Tuple				)   ->    List[str]:







													"""simple docstring"""
													UpperCAmelCase_     : Dict         =					fields(self				)

													# Safety and consistency checks
													if not len(__magic_name__				):
																			raise ValueError(F"""{self.__class__.__name__} has no fields."""				)

													UpperCAmelCase_     : Dict         =					getattr(self    ,       class_fields[0].name				)
													UpperCAmelCase_     : List[Any]         =					all(getattr(self    ,       field.name				) is None for field in class_fields[1:]				)

													if other_fields_are_none and isinstance(__magic_name__    ,       __magic_name__				):
																			for key, value in first_field.items():
																									UpperCAmelCase_     : List[str]         =					value
													else:
																			for field in class_fields:
																									UpperCAmelCase_     : List[str]         =					getattr(self    ,       field.name				)
																									if v is not None:
																															UpperCAmelCase_     : int         =					v

							def __delitem__(							self							:       str    ,       *__magic_name__							:       Optional[int]    ,       **__magic_name__							:       Union[str, Any]				)   ->    Tuple:







													"""simple docstring"""
													raise Exception(F"""You cannot use ``__delitem__`` on a {self.__class__.__name__} instance."""				)

							def       UpperCAmelCase__		(							self							:       Optional[int]    ,       *__magic_name__							:       Dict    ,       **__magic_name__							:       Union[str, Any]				)   ->    List[str]:







													"""simple docstring"""
													raise Exception(F"""You cannot use ``setdefault`` on a {self.__class__.__name__} instance."""				)

							def       UpperCAmelCase__		(							self							:       Optional[Any]    ,       *__magic_name__							:       Union[str, Any]    ,       **__magic_name__							:       Optional[Any]				)   ->    str:







													"""simple docstring"""
													raise Exception(F"""You cannot use ``pop`` on a {self.__class__.__name__} instance."""				)

							def       UpperCAmelCase__		(							self							:       Tuple    ,       *__magic_name__							:       List[Any]    ,       **__magic_name__							:       Optional[int]				)   ->    Any:







													"""simple docstring"""
													raise Exception(F"""You cannot use ``update`` on a {self.__class__.__name__} instance."""				)

							def __getitem__(							self							:       List[str]    ,       __magic_name__							:       List[str]				)   ->    Dict:







													"""simple docstring"""
													if isinstance(__magic_name__    ,       __magic_name__				):
																			UpperCAmelCase_     : Tuple         =					dict(self.items()				)
																			return inner_dict[k]
													else:
																			return self.to_tuple()[k]

							def __setattr__(							self							:       Any    ,       __magic_name__							:       Union[str, Any]    ,       __magic_name__							:       Union[str, Any]				)   ->    Dict:







													"""simple docstring"""
													if name in self.keys() and value is not None:
																			# Don't call self.__setitem__ to avoid recursion errors
																			super().__setitem__(__magic_name__    ,       __magic_name__				)
													super().__setattr__(__magic_name__    ,       __magic_name__				)

							def __setitem__(							self							:       Any    ,       __magic_name__							:       Tuple    ,       __magic_name__							:       Tuple				)   ->    Union[str, Any]:







													"""simple docstring"""
													# Will raise a KeyException if needed
													super().__setitem__(__magic_name__    ,       __magic_name__				)
													# Don't call self.__setattr__ to avoid recursion errors
													super().__setattr__(__magic_name__    ,       __magic_name__				)



							def       UpperCAmelCase__		(							self							:       Tuple				)   ->    Tuple[Any]:







													"""simple docstring"""
													return tuple(self[k] for k in self.keys()				)












'''simple docstring'''







from typing import List, Optional, Tuple, Union

import torch

from ...models import UNetaDModel
from ...schedulers import PNDMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput


class    __a (lowerCamelCase       ):
							__a   :				UNetaDModel
							__a   :				PNDMScheduler

							def __init__(							self							:       Optional[Any]    ,       __magic_name__							:       UNetaDModel    ,       __magic_name__							:       PNDMScheduler				)   ->    Tuple:







													"""simple docstring"""
													super().__init__()

													UpperCAmelCase_     : Optional[int]         =					PNDMScheduler.from_config(scheduler.config				)

													self.register_modules(unet=__magic_name__    ,       scheduler=__magic_name__				)



							@torch.no_grad()
							def __call__(							self							:       Union[str, Any]    ,       __magic_name__							:       int = 1    ,       __magic_name__							:       int = 50    ,       __magic_name__							:       Optional[Union[torch.Generator, List[torch.Generator]]] = None    ,       __magic_name__							:       Optional[str] = "pil"    ,       __magic_name__							:       bool = True    ,       **__magic_name__							:       Dict    ,       )   ->    Union[ImagePipelineOutput, Tuple]:







													"""simple docstring"""
													UpperCAmelCase_     : Dict         =					randn_tensor(
													    (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)    ,       generator=__magic_name__    ,       device=self.device    ,       )

													self.scheduler.set_timesteps(__magic_name__				)
													for t in self.progress_bar(self.scheduler.timesteps				):
																			UpperCAmelCase_     : Optional[int]         =					self.unet(__magic_name__    ,       __magic_name__				).sample

																			UpperCAmelCase_     : str         =					self.scheduler.step(__magic_name__    ,       __magic_name__    ,       __magic_name__				).prev_sample

													UpperCAmelCase_     : int         =					(image / 2 + 0.5).clamp(0    ,       1				)
													UpperCAmelCase_     : Any         =					image.cpu().permute(0    ,       2    ,       3    ,       1				).numpy()
													if output_type == "pil":
																			UpperCAmelCase_     : Optional[int]         =					self.numpy_to_pil(__magic_name__				)

													if not return_dict:
																			return (image,)

													return ImagePipelineOutput(images=__magic_name__				)





