"""simple docstring"""


from typing import TYPE_CHECKING

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


__A       			=      {
    """configuration_imagegpt""": ["""IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ImageGPTConfig""", """ImageGPTOnnxConfig"""]
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __A       			=      ["""ImageGPTFeatureExtractor"""]
 __A       			=      ["""ImageGPTImageProcessor"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __A       			=      [
     """IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """ImageGPTForCausalImageModeling""",
     """ImageGPTForImageClassification""",
     """ImageGPTModel""",
     """ImageGPTPreTrainedModel""",
     """load_tf_weights_in_imagegpt""",
 ]


if TYPE_CHECKING:
 from .configuration_imagegpt import IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, ImageGPTConfig, ImageGPTOnnxConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_imagegpt import ImageGPTFeatureExtractor
  from .image_processing_imagegpt import ImageGPTImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_imagegpt import (
      IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
      ImageGPTForCausalImageModeling,
      ImageGPTForImageClassification,
      ImageGPTModel,
      ImageGPTPreTrainedModel,
      load_tf_weights_in_imagegpt,
  )

else:
 import sys

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

"""simple docstring"""


from doctest import testmod
from math import sqrt

def 						UpperCamelCase				(	_lowerCAmelCase   :							int						):
    __a			      =						[]
    if num < 1:
        return facs
    facs.append(1						)
    if num == 1:
        return facs
    facs.append(_lowerCAmelCase						)
    for i in range(2				, int(sqrt(_lowerCAmelCase						)						) + 1						):
        if num % i == 0:  # If i is a factor of num
            facs.append(_lowerCAmelCase						)
            __a			      =						num // i  # num//i is the other factor of num
            if d != i:  # If d and i are distinct
                facs.append(_lowerCAmelCase						)  # we have found another factor
    facs.sort()
    return facs


if __name__ == "__main__":
 testmod(name="""factors_of_a_number""", verbose=True)
