
import unittest

import torch

from diffusers import DDIMScheduler, TextToVideoZeroPipeline
from diffusers.utils import load_pt, require_torch_gpu, slow

from ..test_pipelines_common import assert_mean_pixel_difference





@slow
@require_torch_gpu
class 						lowercase       (  unittest.TestCase					):
					def lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    Optional[Any]				      =			'''runwayml/stable-diffusion-v1-5'''
								lowerCAmelCase__ :    Dict				      =			TextToVideoZeroPipeline.from_pretrained(SCREAMING_SNAKE_CASE__ ,	torch_dtype=torch.floataa    ).to('''cuda'''    )
								lowerCAmelCase__ :    str				      =			DDIMScheduler.from_config(pipe.scheduler.config    )
								lowerCAmelCase__ :    List[Any]				      =			torch.Generator(device='''cuda'''    ).manual_seed(0    )

								lowerCAmelCase__ :    Any				      =			'''A bear is playing a guitar on Times Square'''
								lowerCAmelCase__ :    Optional[Any]				      =			pipe(prompt=SCREAMING_SNAKE_CASE__ ,	generator=SCREAMING_SNAKE_CASE__    ).images

								lowerCAmelCase__ :    List[Any]				      =			load_pt(
								    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text-to-video/A bear is playing a guitar on Times Square.pt'''    )

								assert_mean_pixel_difference(SCREAMING_SNAKE_CASE__ ,	SCREAMING_SNAKE_CASE__    )





import abc
import copy
import dataclasses
from dataclasses import dataclass
from typing import ClassVar, Dict, Type, TypeVar

from ..features import Features


A__       :   Tuple   						=					TypeVar("""T""", bound="""TaskTemplate""")





@dataclass(frozen=__UpperCamelCase					)
class 						lowercase       (  abc.ABC					):
					# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
					__a					=    42
					__a					=    42
					__a					=    42
					def lowercase_			(		self ,	SCREAMING_SNAKE_CASE__    ):
								"""simple docstring"""







								return copy.deepcopy(self    )
					@property
					def lowercase_			(		self    ):
								"""simple docstring"""







								return Features(**self.input_schema ,	**self.label_schema    )
					@property
					@abc.abstractmethod
					def lowercase_			(		self    ):
								"""simple docstring"""







								raise NotImplementedError
					@classmethod
					def lowercase_			(		cls ,	SCREAMING_SNAKE_CASE__    ):
								"""simple docstring"""







								lowerCAmelCase__ :    List[Any]				      =			{f.name for f in dataclasses.fields(cls    )}
								return cls(**{k: v for k, v in template_dict.items() if k in field_names}    )



