



"""simple docstring"""

from typing import TYPE_CHECKING

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


lowercase__					:						Any												=						{'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FocalNetConfig']}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowercase__					:						Dict												=						[
         'FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST',
         'FocalNetForImageClassification',
         'FocalNetForMaskedImageModeling',
         'FocalNetBackbone',
         'FocalNetModel',
         'FocalNetPreTrainedModel',
     ]

if TYPE_CHECKING:
     from .configuration_focalnet import FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP, FocalNetConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_focalnet import (
              FOCALNET_PRETRAINED_MODEL_ARCHIVE_LIST,
              FocalNetBackbone,
              FocalNetForImageClassification,
              FocalNetForMaskedImageModeling,
              FocalNetModel,
              FocalNetPreTrainedModel,
          )

else:
     import sys

     lowercase__					:						Union[str, Any]												=						_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)










"""simple docstring"""

from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available




@dataclass
class  _UpperCAmelCase (    lowerCAmelCase__):
 _lowerCAmelCase     :    Union[List[PIL.Image.Image], np.ndarray]
 _lowerCAmelCase     :    Optional[List[bool]]


if is_transformers_available() and is_torch_available():
     from .pipeline_semantic_stable_diffusion import SemanticStableDiffusionPipeline





