

'''simple docstring'''



def       snake_case   (	snake_case      : int					,		snake_case      : int			) ->  int:


    """simple docstring"""


    return int((input_a, input_a).count(0			) == 0			)


def       snake_case   (	) ->  None:


    """simple docstring"""


    assert and_gate(0					,		0			) == 0
    assert and_gate(0					,		1			) == 0
    assert and_gate(1					,		0			) == 0
    assert and_gate(1					,		1			) == 1


if __name__ == "__main__":
     test_and_gate()
     print(and_gate(1, 0))
     print(and_gate(0, 0))
     print(and_gate(0, 1))
     print(and_gate(1, 1))








'''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 				_snake_case					(   a_			):
  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





