




def SCREAMING_SNAKE_CASE       ( lowercase_				,       lowercase_		)     -> int:



       """simple docstring"""

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







def SCREAMING_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))







from typing import TYPE_CHECKING

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


_lowerCamelCase			:	Union[str, Any]							 =     {"""configuration_dpt""": ["""DPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DPTConfig"""]}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase			:	Optional[Any]							 =     ["""DPTFeatureExtractor"""]
  _lowerCamelCase			:	int							 =     ["""DPTImageProcessor"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase			:	Optional[int]							 =     [
      """DPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """DPTForDepthEstimation""",
      """DPTForSemanticSegmentation""",
      """DPTModel""",
      """DPTPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_dpt import DPTFeatureExtractor
    from .image_processing_dpt import DPTImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_dpt import (
        DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
        DPTForDepthEstimation,
        DPTForSemanticSegmentation,
        DPTModel,
        DPTPreTrainedModel,
    )


else:
  import sys

  _lowerCamelCase			:	Any							 =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


