





from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE   						=		{
    """configuration_swin2sr""": ["""SWIN2SR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Swin2SRConfig"""],
}


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


try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_SCREAMING_SNAKE_CASE   						=		["""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

						_SCREAMING_SNAKE_CASE   						=		_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 is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
 from .image_encoder import PaintByExampleImageEncoder
 from .pipeline_paint_by_example import PaintByExamplePipeline

