






'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_UpperCamelCase		:		Union[str, Any]								=			{'configuration_yoso': ['YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YosoConfig']}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_UpperCamelCase		:		int								=			[
						    'YOSO_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'YosoForMaskedLM',
						    'YosoForMultipleChoice',
						    'YosoForQuestionAnswering',
						    'YosoForSequenceClassification',
						    'YosoForTokenClassification',
						    'YosoLayer',
						    'YosoModel',
						    'YosoPreTrainedModel',
						]


if TYPE_CHECKING:
						from .configuration_yoso import YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP, YosoConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_yoso import (
												    YOSO_PRETRAINED_MODEL_ARCHIVE_LIST,
												    YosoForMaskedLM,
												    YosoForMultipleChoice,
												    YosoForQuestionAnswering,
												    YosoForSequenceClassification,
												    YosoForTokenClassification,
												    YosoLayer,
												    YosoModel,
												    YosoPreTrainedModel,
												)


else:
						import sys

						_UpperCamelCase		:		List[Any]								=			_LazyModule(__name__, globals()['__file__'], _import_structure)










'''simple docstring'''





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 				snake_case__     (			unittest.TestCase):




					def 						A     (       self       :						Optional[Any]     )  ->    List[str]:
								UpperCAmelCase_     :   Optional[Any]       =   '''runwayml/stable-diffusion-v1-5'''
								UpperCAmelCase_     :   Optional[int]       =   TextToVideoZeroPipeline.from_pretrained(_A							,				torch_dtype=torch.floataa     ).to('''cuda'''     )
								UpperCAmelCase_     :   Tuple       =   DDIMScheduler.from_config(pipe.scheduler.config     )
								UpperCAmelCase_     :   Tuple       =   torch.Generator(device='''cuda'''     ).manual_seed(0     )

								UpperCAmelCase_     :   List[Any]       =   '''A bear is playing a guitar on Times Square'''
								UpperCAmelCase_     :   List[Any]       =   pipe(prompt=_A							,				generator=_A     ).images

								UpperCAmelCase_     :   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(_A							,				_A     )


