
from typing import TYPE_CHECKING

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


A  :			int     				=				{
    'configuration_oneformer': ['ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OneFormerConfig'],
    'processing_oneformer': ['OneFormerProcessor'],
}

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

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					A  :			Tuple     				=				[
					    'ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'OneFormerForUniversalSegmentation',
					    'OneFormerModel',
					    'OneFormerPreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_oneformer import ONEFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, OneFormerConfig
					from .processing_oneformer import OneFormerProcessor

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_oneformer import OneFormerImageProcessor
					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_oneformer import (
										    ONEFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    OneFormerForUniversalSegmentation,
										    OneFormerModel,
										    OneFormerPreTrainedModel,
										)


else:
					import sys

					A  :			Optional[Any]     				=				_LazyModule(__name__, globals()['__file__'], _import_structure)

import os

from apache_beam.io.filesystems import FileSystems
from apache_beam.pipeline import Pipeline

from .logging import get_logger


A  :			Optional[int]     				=				2 << 2_0  # 2mb
A  :			Optional[int]     				=				get_logger(__name__)







class     __A(				a    ):




				def        SCREAMING_SNAKE_CASE_	(  self       )					->   Union[str, Any]:


								'''simple docstring'''




								__a    							=					self._options.get_all_options().get('''runner'''       )
								return runner in [None, "DirectRunner", "PortableRunner"]



def 					__lowerCAmelCase    (    a__		,					a__		,					a__=False						) ->						Union[str, Any]:
				__a    							=					FileSystems
				if fs.exists(a__						):
								if force_upload:
												logger.info(F"""Remote path already exist: {remote_file_path}. Overwriting it as force_upload=True."""						)
								else:
												logger.info(F"""Remote path already exist: {remote_file_path}. Skipping it as force_upload=False."""						)
												return
				with fs.create(a__						) as remote_file:
								with open(a__		,					'''rb'''						) as local_file:
												__a    							=					local_file.read(a__						)
												while chunk:
																remote_file.write(a__						)
																__a    							=					local_file.read(a__						)






def 					__lowerCAmelCase    (    a__		,					a__		,					a__=False						) ->						Dict:
				__a    							=					FileSystems
				if os.path.exists(a__						):
								if force_download:
												logger.info(F"""Local path already exist: {remote_file_path}. Overwriting it as force_upload=True."""						)
								else:
												logger.info(F"""Local path already exist: {remote_file_path}. Skipping it as force_upload=False."""						)
												return
				with fs.open(a__						) as remote_file:
								with open(a__		,					'''wb'''						) as local_file:
												__a    							=					remote_file.read(a__						)
												while chunk:
																local_file.write(a__						)
																__a    							=					remote_file.read(a__						)