

'''simple docstring'''




_lowerCAmelCase         =						"Tobias Carryer"

from time import time






class   _SCREAMING_SNAKE_CASE   :



 def __init__(   self		:   Tuple			,				a__		:   Optional[Any]			,				a__		:   Tuple			,				a__		:   List[Any]			,				a__		:   Optional[Any]=int(time()      )      ):  # noqa: B008
      __magic_name__						       =    multiplier
      __magic_name__						       =    increment
      __magic_name__						       =    modulo
      __magic_name__						       =    seed



 def 			snake_case__  (   self		:   Tuple      ):
      __magic_name__						       =    (self.multiplier * self.seed + self.increment) % self.modulo
      return self.seed


if __name__ == "__main__":
      # Show the LCG in action.
      _lowerCAmelCase         =						LinearCongruentialGenerator(1664525, 1013904223, 2 << 31)
      while True:
            print(lcg.next_number())









'''simple docstring'''




from typing import TYPE_CHECKING

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


_lowerCAmelCase         =						{"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCAmelCase         =						["GLPNFeatureExtractor"]
      _lowerCAmelCase         =						["GLPNImageProcessor"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCAmelCase         =						[
          "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST",
          "GLPNForDepthEstimation",
          "GLPNLayer",
          "GLPNModel",
          "GLPNPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_glpn import GLPNFeatureExtractor
            from .image_processing_glpn import GLPNImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_glpn import (
                GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
                GLPNForDepthEstimation,
                GLPNLayer,
                GLPNModel,
                GLPNPreTrainedModel,
            )


else:
      import sys

      _lowerCAmelCase         =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






