





'''simple docstring'''







from typing import TYPE_CHECKING

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


A						    =							{
    '''configuration_swin2sr''': ['''SWIN2SR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swin2SRConfig'''],
}


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A						    =							[
        '''SWIN2SR_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''Swin2SRForImageSuperResolution''',
        '''Swin2SRModel''',
        '''Swin2SRPreTrainedModel''',
    ]


try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A						    =							['''Swin2SRImageProcessor''']


if TYPE_CHECKING:
    from .configuration_swinasr import SWIN2SR_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinaSRConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_swinasr import (
            SWIN2SR_PRETRAINED_MODEL_ARCHIVE_LIST,
            SwinaSRForImageSuperResolution,
            SwinaSRModel,
            SwinaSRPreTrainedModel,
        )

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .image_processing_swinasr import SwinaSRImageProcessor


else:
    import sys

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









'''simple docstring'''







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 							__SCREAMING_SNAKE_CASE			(       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