

'''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      lowercase_      (lowerCamelCase__ ):




  """simple docstring"""




  SCREAMING_SNAKE_CASE       :    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




_lowerCAmelCase  :      int			 ="""
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/transformers.git
"""

_lowerCAmelCase  :      List[str]			 =[{"""type""": """code""", """content""": INSTALL_CONTENT}]
_lowerCAmelCase  :      int			 ={
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}