




"""simple docstring"""





from typing import TYPE_CHECKING

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


A				=							{
    """configuration_maskformer""": ["""MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MaskFormerConfig"""],
    """configuration_maskformer_swin""": ["""MaskFormerSwinConfig"""],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A				=							["""MaskFormerFeatureExtractor"""]
					A				=							["""MaskFormerImageProcessor"""]


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A				=							[
					    """MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """MaskFormerForInstanceSegmentation""",
					    """MaskFormerModel""",
					    """MaskFormerPreTrainedModel""",
					]
					A				=							[
					    """MaskFormerSwinBackbone""",
					    """MaskFormerSwinModel""",
					    """MaskFormerSwinPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
					from .configuration_maskformer_swin import MaskFormerSwinConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_maskformer import MaskFormerFeatureExtractor
										from .image_processing_maskformer import MaskFormerImageProcessor
					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_maskformer import (
										    MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MaskFormerForInstanceSegmentation,
										    MaskFormerModel,
										    MaskFormerPreTrainedModel,
										)
										from .modeling_maskformer_swin import (
										    MaskFormerSwinBackbone,
										    MaskFormerSwinModel,
										    MaskFormerSwinPreTrainedModel,
										)


else:
					import sys

					A				=							_LazyModule(__name__, globals()["""__file__"""], _import_structure)






"""simple docstring"""

from typing import Optional
from urllib.parse import quote

import huggingface_hub as hfh
from packaging import version


def lowerCAmelCase_   (					UpperCamelCase__						:			str					, UpperCamelCase__						:			str					, UpperCamelCase__						:			Optional[str] = None			):






 """simple docstring"""







 if version.parse(hfh.__version__			).release < version.parse("""0.11.0"""			).release:
  # old versions of hfh don't url-encode the file path
  __lowercase						=						quote(UpperCamelCase__			)
 return hfh.hf_hub_url(UpperCamelCase__					, UpperCamelCase__					, repo_type="""dataset"""					, revision=UpperCamelCase__			)
