





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowerCAmelCase_     =     {
    "configuration_efficientformer": [
        "EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "EfficientFormerConfig",
    ]
}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowerCAmelCase_     =     ["EfficientFormerImageProcessor"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowerCAmelCase_     =     [
          "EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
          "EfficientFormerForImageClassification",
          "EfficientFormerForImageClassificationWithTeacher",
          "EfficientFormerModel",
          "EfficientFormerPreTrainedModel",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowerCAmelCase_     =     [
          "TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
          "TFEfficientFormerForImageClassification",
          "TFEfficientFormerForImageClassificationWithTeacher",
          "TFEfficientFormerModel",
          "TFEfficientFormerPreTrainedModel",
      ]

if TYPE_CHECKING:
      from .configuration_efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .image_processing_efficientformer import EfficientFormerImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_efficientformer import (
                EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                EfficientFormerForImageClassification,
                EfficientFormerForImageClassificationWithTeacher,
                EfficientFormerModel,
                EfficientFormerPreTrainedModel,
            )
      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_efficientformer import (
                TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFEfficientFormerForImageClassification,
                TFEfficientFormerForImageClassificationWithTeacher,
                TFEfficientFormerModel,
                TFEfficientFormerPreTrainedModel,
            )

else:
      import sys

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









a__   :					Tuple 						=      "Tobias Carryer"

from time import time



class    UpperCAmelCase__:

   '''simple docstring'''




   def __init__(    self	:      str      ,					lowerCAmelCase	:      List[str]      ,					lowerCAmelCase	:      Any      ,					lowerCAmelCase	:      str      ,					lowerCAmelCase	:      str=int(time()))						->					List[Any]:  # noqa: B008




         """simple docstring"""

         lowercase__  =	multiplier
         lowercase__  =	increment
         lowercase__  =	modulo
         lowercase__  =	seed



   def       UpperCAmelCase		(    self	:      int)						->					Tuple:




         """simple docstring"""

         lowercase__  =	(self.multiplier * self.seed + self.increment) % self.modulo
         return self.seed


if __name__ == "__main__":
       # Show the LCG in action.
       a__   :					str 						=      LinearCongruentialGenerator(1_66_45_25, 10_13_90_42_23, 2 << 31)
       while True:
              print(lcg.next_number())
