



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__(				lowerCamelCase						):

   '''simple docstring'''




   A     :	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





import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


a__   :					Optional[Any] 						=      logging.get_logger(__name__)



class    UpperCAmelCase__(				lowerCamelCase						):

   '''simple docstring'''




   def __init__(    self	:      Optional[Any]      ,					*lowerCAmelCase	:      Optional[Any]      ,					**lowerCAmelCase	:      List[Any])						->					None:




         """simple docstring"""

         warnings.warn(
             'The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
             ' use GLPNImageProcessor instead.'      ,					lowerCAmelCase      ,					)
         super().__init__(*lowerCAmelCase      ,					**lowerCAmelCase)
