

'''simple docstring'''




def    lowerCamelCase__		(    SCREAMING_SNAKE_CASE   : Union[str, Any]    ):
  if not numbers:
    return 0

  if not isinstance(lowerCAmelCase__							, (list, tuple)    ) or not all(
      isinstance(lowerCAmelCase__							, lowerCAmelCase__    ) for number in numbers    ):
    raise ValueError('numbers must be an iterable of integers'    )

  UpperCAmelCase    				=						UpperCAmelCase    				=						UpperCAmelCase    				=						numbers[0]

  for i in range(1							, len(lowerCAmelCase__    )    ):
    # update the maximum and minimum subarray products
    UpperCAmelCase    				=						numbers[i]
    if number < 0:
      UpperCAmelCase				,   UpperCAmelCase    				=						min_till_now, max_till_now
    UpperCAmelCase    				=						max(lowerCAmelCase__							, max_till_now * number    )
    UpperCAmelCase    				=						min(lowerCAmelCase__							, min_till_now * number    )

    # update the maximum product found till now
    UpperCAmelCase    				=						max(lowerCAmelCase__							, lowerCAmelCase__    )

  return max_prod






from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE							    =							{
    'configuration_autoformer': [
        'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'AutoformerConfig',
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE							    =							[
      'AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
      'AutoformerForPrediction',
      'AutoformerModel',
      'AutoformerPreTrainedModel',
  ]


if TYPE_CHECKING:
  from .configuration_autoformer import (
      AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      AutoformerConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_autoformer import (
        AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        AutoformerForPrediction,
        AutoformerModel,
        AutoformerPreTrainedModel,
    )

else:
  import sys

  SCREAMING_SNAKE_CASE							    =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



