



import warnings

from .state import AcceleratorState, GradientState


warnings.filterwarnings("ignore", category=UserWarning, module="torch.optim.lr_scheduler")



class 	_lowercase							:





	"""simple docstring"""




	def __init__(self		,       lowerCamelCase_		,       lowerCamelCase_		,       lowerCamelCase_ = True		,       lowerCamelCase_ = False		):
						"""simple docstring"""

						a					     =   scheduler
						a					     =   optimizers if isinstance(lowerCamelCase_		,       (list, tuple)		) else [optimizers]
						a					     =   split_batches
						a					     =   step_with_optimizer
						a					     =   GradientState()




	def      UpperCamelCase_       (self		,       *lowerCamelCase_		,       **lowerCamelCase_		):
						"""simple docstring"""

						if not self.step_with_optimizer:
											# No link between scheduler and optimizer -> just step
											self.scheduler.step(*lowerCamelCase_		,       **lowerCamelCase_		)
											return

						# Otherwise, first make sure the optimizer was stepped.
						if not self.gradient_state.sync_gradients:
											if self.gradient_state.adjust_scheduler:
																self.scheduler._step_count += 1
											return

						for opt in self.optimizers:
											if opt.step_was_skipped:
																return
						if self.split_batches:
											# Split batches -> the training dataloader batch size is not changed so one step per training step
											self.scheduler.step(*lowerCamelCase_		,       **lowerCamelCase_		)
						else:
											# Otherwise the training dataloader batch size was multiplied by `num_processes`, so we need to do
											# num_processes steps per training step
											a					     =   AcceleratorState().num_processes
											for _ in range(lowerCamelCase_		):
																# Special case when using OneCycle and `drop_last` was not used
																if hasattr(self.scheduler		,       "total_steps"		):
																					if self.scheduler._step_count <= self.scheduler.total_steps:
																										self.scheduler.step(*lowerCamelCase_		,       **lowerCamelCase_		)
																else:
																					self.scheduler.step(*lowerCamelCase_		,       **lowerCamelCase_		)




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						return self.scheduler.get_last_lr()




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						return self.scheduler.state_dict()




	def      UpperCamelCase_       (self		,       lowerCamelCase_		):
						"""simple docstring"""

						self.scheduler.load_state_dict(lowerCamelCase_		)




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						return self.scheduler.get_lr()




	def      UpperCamelCase_       (self		,       *lowerCamelCase_		,       **lowerCamelCase_		):
						"""simple docstring"""

						return self.scheduler.print_lr(*lowerCamelCase_		,       **lowerCamelCase_		)





'''simple docstring'''




# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse

from .config import config_command_parser
from .config_args import default_config_file, load_config_from_file  # noqa: F401
from .default import default_command_parser
from .update import update_command_parser



def 	a			( lowerCamelCase__=None    ):
			'''simple docstring'''





			A_	:						int	=     argparse.ArgumentParser(add_help=lowerCamelCase__						,      allow_abbrev=lowerCamelCase__    )
			# The main config parser
			A_	:						int	=     config_command_parser(lowerCamelCase__    )
			# The subparser to add commands to
			A_	:						int	=     config_parser.add_subparsers(title="""subcommands"""						,      dest="""subcommand"""    )

			# Then add other parsers with the parent parser
			default_command_parser(lowerCamelCase__						,      parents=[parent_parser]    )
			update_command_parser(lowerCamelCase__						,      parents=[parent_parser]    )

			return config_parser



def 	a			( ):
			'''simple docstring'''





			A_	:						Optional[int]	=     get_config_parser()
			A_	:						List[str]	=     config_parser.parse_args()

			if not hasattr(lowerCamelCase__						,      """func"""    ):
						config_parser.print_help()
						exit(1    )

			# Run
			args.func(lowerCamelCase__    )


if __name__ == "__main__":
						main()