

from typing import TYPE_CHECKING

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


lowerCamelCase     =      {
    '''configuration_flava''': [
        '''FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''FlavaConfig''',
        '''FlavaImageCodebookConfig''',
        '''FlavaImageConfig''',
        '''FlavaMultimodalConfig''',
        '''FlavaTextConfig''',
    ],
}

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase     =      ['''FlavaFeatureExtractor''']
       lowerCamelCase     =      ['''FlavaImageProcessor''']
       lowerCamelCase     =      ['''FlavaProcessor''']

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase     =      [
           '''FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''FlavaForPreTraining''',
           '''FlavaImageCodebook''',
           '''FlavaImageModel''',
           '''FlavaModel''',
           '''FlavaMultimodalModel''',
           '''FlavaPreTrainedModel''',
           '''FlavaTextModel''',
       ]

if TYPE_CHECKING:
       from .configuration_flava import (
           FLAVA_PRETRAINED_CONFIG_ARCHIVE_MAP,
           FlavaConfig,
           FlavaImageCodebookConfig,
           FlavaImageConfig,
           FlavaMultimodalConfig,
           FlavaTextConfig,
       )

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_flava import FlavaFeatureExtractor
              from .image_processing_flava import FlavaImageProcessor
              from .processing_flava import FlavaProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flava import (
                  FLAVA_PRETRAINED_MODEL_ARCHIVE_LIST,
                  FlavaForPreTraining,
                  FlavaImageCodebook,
                  FlavaImageModel,
                  FlavaModel,
                  FlavaMultimodalModel,
                  FlavaPreTrainedModel,
                  FlavaTextModel,
              )

else:
       import sys

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



from dataclasses import dataclass
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
# Copied from diffusers.pipelines.stable_diffusion.__init__.StableDiffusionPipelineOutput with Stable->Alt
class 		__magic_name__    (							lowerCamelCase__							):

   '''simple docstring'''




   lowerCamelCase__				:			Union[List[PIL.Image.Image], np.ndarray]
   lowerCamelCase__				:			Optional[List[bool]]


if is_transformers_available() and is_torch_available():
       from .modeling_roberta_series import RobertaSeriesModelWithTransformation
       from .pipeline_alt_diffusion import AltDiffusionPipeline
       from .pipeline_alt_diffusion_imgaimg import AltDiffusionImgaImgPipeline
