



'''simple docstring'''


from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import torch

from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available







@dataclass
class 	UpperCAmelCase	(		__a):


 '''simple docstring'''




 __magic_name__					: Union[List[np.ndarray], torch.FloatTensor]


try:
  if not (is_transformers_available() and is_torch_available()):
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
  from .pipeline_text_to_video_synth import TextToVideoSDPipeline
  from .pipeline_text_to_video_synth_imgaimg import VideoToVideoSDPipeline  # noqa: F401
  from .pipeline_text_to_video_zero import TextToVideoZeroPipeline







'''simple docstring'''


from .testing import (
    are_the_same_tensors,
    execute_subprocess_async,
    require_bnb,
    require_cpu,
    require_cuda,
    require_huggingface_suite,
    require_mps,
    require_multi_gpu,
    require_multi_xpu,
    require_safetensors,
    require_single_gpu,
    require_single_xpu,
    require_torch_min_version,
    require_tpu,
    require_xpu,
    skip,
    slow,
)
from .training import RegressionDataset, RegressionModel, RegressionModelaXPU


from .scripts import test_script, test_sync, test_ops  # isort: skip


