


import importlib
import shutil
import threading
import warnings
from typing import List

import fsspec
import fsspec.asyn

from . import compression
from .hffilesystem import HfFileSystem


_lowerCAmelCase:						List[Any]   				=       importlib.util.find_spec('s3fs') is not None

if _has_safs:
	from .safilesystem import SaFileSystem  # noqa: F401

_lowerCAmelCase:						List[compression.BaseCompressedFileFileSystem]   				=       [
    compression.BzaFileSystem,
    compression.GzipFileSystem,
    compression.LzaFileSystem,
    compression.XzFileSystem,
    compression.ZstdFileSystem,
]

# Register custom filesystems
for fs_class in COMPRESSION_FILESYSTEMS + [HfFileSystem]:
	if fs_class.protocol in fsspec.registry and fsspec.registry[fs_class.protocol] is not fs_class:
		warnings.warn(F"""A filesystem protocol was already set for {fs_class.protocol} and will be overwritten.""")
	fsspec.register_implementation(fs_class.protocol, fs_class, clobber=True)






def   _lowercase(					__a				:						str     ):
							if "://" in dataset_path:
														a__      =dataset_path.split('://'     )[1]
							return dataset_path






def   _lowercase(					__a				:						fsspec.AbstractFileSystem     ):
							if fs is not None and fs.protocol != "file":
														return True
							else:
														return False






def   _lowercase(					__a				:						fsspec.AbstractFileSystem    ,     __a				:						str    ,     __a				:						str     ):
							a__      =not is_remote_filesystem(__a     )
							if is_local:
														# LocalFileSystem.mv does copy + rm, it is more efficient to simply move a local directory
														shutil.move(fs._strip_protocol(__a     )    ,     fs._strip_protocol(__a     )     )
							else:
														fs.mv(__a    ,     __a    ,     recursive=__a     )







def   _lowercase(					):
							if hasattr(fsspec.asyn    ,     'reset_lock'     ):
														# for future fsspec>2022.05.0
														fsspec.asyn.reset_lock()
							else:
														a__      =None
														a__      =None
														a__      =threading.Lock()




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


UpperCamelCase__		 =     {
    '''configuration_convnext''': ['''CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ConvNextConfig''', '''ConvNextOnnxConfig''']
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase__		 =     ['''ConvNextFeatureExtractor''']
    UpperCamelCase__		 =     ['''ConvNextImageProcessor''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase__		 =     [
        '''CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''ConvNextForImageClassification''',
        '''ConvNextModel''',
        '''ConvNextPreTrainedModel''',
        '''ConvNextBackbone''',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCamelCase__		 =     [
        '''TFConvNextForImageClassification''',
        '''TFConvNextModel''',
        '''TFConvNextPreTrainedModel''',
    ]

if TYPE_CHECKING:
    from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_convnext import ConvNextFeatureExtractor
        from .image_processing_convnext import ConvNextImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_convnext import (
            CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
            ConvNextBackbone,
            ConvNextForImageClassification,
            ConvNextModel,
            ConvNextPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
    import sys

    UpperCamelCase__		 =     _LazyModule(__name__, globals()['''__file__'''], _import_structure)

