"""simple docstring"""




import logging
import os

from .state import PartialState
class     UpperCamelCase__(			logging.LoggerAdapter ):





						@staticmethod
						def 				snake_case__	(       __UpperCAmelCase     )					->				List[Any]:
													A__	     =							PartialState()
													return not main_process_only or (main_process_only and state.is_main_process)





						def 				snake_case__	(       self		,__UpperCAmelCase		,__UpperCAmelCase		,*__UpperCAmelCase		,**__UpperCAmelCase     )					->				Union[str, Any]:
													if PartialState._shared_state == {}:
																				raise RuntimeError(
																				    'You must initialize the accelerate state by calling either `PartialState()` or `Accelerator()` before using the logging utility.'     )
													A__	     =							kwargs.pop('main_process_only'		,__UpperCAmelCase     )
													A__	     =							kwargs.pop('in_order'		,__UpperCAmelCase     )

													if self.isEnabledFor(__UpperCAmelCase     ):
																				if self._should_log(__UpperCAmelCase     ):
																											A__     ,  A__	     =							self.process(__UpperCAmelCase		,__UpperCAmelCase     )
																											self.logger.log(__UpperCAmelCase		,__UpperCAmelCase		,*__UpperCAmelCase		,**__UpperCAmelCase     )

																				elif in_order:
																											A__	     =							PartialState()
																											for i in range(state.num_processes     ):
																																		if i == state.process_index:
																																									A__     ,  A__	     =							self.process(__UpperCAmelCase		,__UpperCAmelCase     )
																																									self.logger.log(__UpperCAmelCase		,__UpperCAmelCase		,*__UpperCAmelCase		,**__UpperCAmelCase     )
																																		state.wait_for_everyone()






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__ = None				):






							"""simple docstring"""





							if log_level is None:
														A__	     =							os.environ.get('ACCELERATE_LOG_LEVEL'       ,    UpperCamelCase__				)
							A__	     =							logging.getLogger(UpperCamelCase__				)
							if log_level is not None:
														logger.setLevel(log_level.upper()				)
														logger.root.setLevel(log_level.upper()				)
							return MultiProcessAdapter(UpperCamelCase__       ,    {}				)






"""simple docstring"""




from typing import TYPE_CHECKING

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


__lowerCamelCase											=  {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCamelCase											=  ["GLPNFeatureExtractor"]
				__lowerCamelCase											=  ["GLPNImageProcessor"]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCamelCase											=  [
				    "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "GLPNForDepthEstimation",
				    "GLPNLayer",
				    "GLPNModel",
				    "GLPNPreTrainedModel",
				]


if TYPE_CHECKING:
				from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_glpn import GLPNFeatureExtractor
								from .image_processing_glpn import GLPNImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_glpn import (
								    GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
								    GLPNForDepthEstimation,
								    GLPNLayer,
								    GLPNModel,
								    GLPNPreTrainedModel,
								)


else:
				import sys

				__lowerCamelCase											=  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





