





from __future__ import annotations

import os
from typing import Any

import requests

lowerCAmelCase							:       int					 =	"""https://api.github.com"""

# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowerCAmelCase							:       Tuple					 =	BASE_URL + """/user"""

# https://github.com/settings/tokens
lowerCAmelCase							:       Any					 =	os.environ.get("""USER_TOKEN""", """""")






def 		lowerCAmelCase  (	UpperCamelCase__   :   str					)      ->    dict[Any, Any]:

						"""simple docstring"""





						__SCREAMING_SNAKE_CASE:				Optional[int]           =   {
						    '''Authorization''': F"""token {auth_token}""",
						    '''Accept''': '''application/vnd.github.v3+json''',
						}
						return requests.get(UpperCamelCase__       ,			headers=UpperCamelCase__					).json()


if __name__ == "__main__":  # pragma: no cover
							if USER_TOKEN:
														for key, value in fetch_github_info(USER_TOKEN).items():
																					print(f'''{key}: {value}''')
							else:
														raise ValueError("""'USER_TOKEN' field cannot be empty.""")










import baseaa
import io
import json
import os
from copy import deepcopy

from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler





class 				a			:






				def __init__(  self			, _lowerCAmelCase					):

										"""simple docstring"""




										if isinstance(_lowerCAmelCase			, _lowerCAmelCase					):
																# Don't modify user's data should they want to reuse it (e.g. in tests), because once we
																# modified it, it will not be accepted here again, since `auto` values would have been overridden
																__SCREAMING_SNAKE_CASE:				Optional[int]           =   deepcopy(_lowerCAmelCase					)
										elif os.path.exists(_lowerCAmelCase					):
																with io.open(_lowerCAmelCase			, '''r'''			, encoding='''utf-8'''					) as f:
																						__SCREAMING_SNAKE_CASE:				int           =   json.load(_lowerCAmelCase					)
										else:
																try:
																						__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   baseaa.urlsafe_baadecode(_lowerCAmelCase					).decode('''utf-8'''					)
																						__SCREAMING_SNAKE_CASE:				List[Any]           =   json.loads(_lowerCAmelCase					)
																except (UnicodeDecodeError, AttributeError, ValueError):
																						raise ValueError(
																						    f"""Expected a string path to an existing deepspeed config, or a dictionary, or a base64 encoded string. Received: {config_file_or_dict}"""					)

										__SCREAMING_SNAKE_CASE:				str           =   config

										self.set_stage_and_offload()






				def 			snake_case_    (  self					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				str           =   self.get_value('''zero_optimization.stage'''			, -1					)

										# offload
										__SCREAMING_SNAKE_CASE:				Dict           =   False
										if self.is_zeroa() or self.is_zeroa():
																__SCREAMING_SNAKE_CASE:				str           =   set(['''cpu''', '''nvme''']					)
																__SCREAMING_SNAKE_CASE:				Tuple           =   set(
																    [
																        self.get_value('''zero_optimization.offload_optimizer.device'''					),
																        self.get_value('''zero_optimization.offload_param.device'''					),
																    ]					)
																if len(offload_devices & offload_devices_valid					) > 0:
																						__SCREAMING_SNAKE_CASE:				Dict           =   True






				def 			snake_case_    (  self			, _lowerCAmelCase					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				int           =   self.config

										# find the config node of interest if it exists
										__SCREAMING_SNAKE_CASE:				Optional[Any]           =   ds_key_long.split('''.'''					)
										__SCREAMING_SNAKE_CASE:				Union[str, Any]           =   nodes.pop()
										for node in nodes:
																__SCREAMING_SNAKE_CASE:				int           =   config.get(_lowerCAmelCase					)
																if config is None:
																						return None, ds_key

										return config, ds_key






				def 			snake_case_    (  self			, _lowerCAmelCase			, _lowerCAmelCase=None					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE       ,__SCREAMING_SNAKE_CASE:				List[Any]           =   self.find_config_node(_lowerCAmelCase					)
										if config is None:
																return default
										return config.get(_lowerCAmelCase			, _lowerCAmelCase					)






				def 			snake_case_    (  self			, _lowerCAmelCase			, _lowerCAmelCase=False					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				str           =   self.config

										# find the config node of interest if it exists
										__SCREAMING_SNAKE_CASE:				str           =   ds_key_long.split('''.'''					)
										for node in nodes:
																__SCREAMING_SNAKE_CASE:				Tuple           =   config
																__SCREAMING_SNAKE_CASE:				List[str]           =   config.get(_lowerCAmelCase					)
																if config is None:
																						if must_exist:
																												raise ValueError(f"""Can't find {ds_key_long} entry in the config: {self.config}"""					)
																						else:
																												return

        # if found remove it
										if parent_config is not None:
																parent_config.pop(_lowerCAmelCase					)






				def 			snake_case_    (  self			, _lowerCAmelCase					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Optional[Any]           =   self.get_value(_lowerCAmelCase					)
										return False if value is None else bool(_lowerCAmelCase					)






				def 			snake_case_    (  self			, _lowerCAmelCase					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Any           =   self.get_value(_lowerCAmelCase					)
										return False if value is None else not bool(_lowerCAmelCase					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										return self._stage == 2






				def 			snake_case_    (  self					):

										"""simple docstring"""




										return self._stage == 3






				def 			snake_case_    (  self					):

										"""simple docstring"""




										return self._offload





class 				a			:






				def __init__(  self			, _lowerCAmelCase					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				Optional[int]           =   engine






				def 			snake_case_    (  self			, _lowerCAmelCase			, **_lowerCAmelCase					):

										"""simple docstring"""




										self.engine.backward(_lowerCAmelCase			, **_lowerCAmelCase					)

										# Deepspeed's `engine.step` performs the following operations:
										# - gradient accumulation check
										# - gradient clipping
										# - optimizer step
										# - zero grad
										# - checking overflow
										# - lr_scheduler step (only if engine.lr_scheduler is not None)
										self.engine.step()
										# and this plugin overrides the above calls with no-ops when Accelerate runs under
										# Deepspeed, but allows normal functionality for non-Deepspeed cases thus enabling a simple
										# training loop that works transparently under many training regimes.





class 				a			(      __lowercase			):






				def __init__(  self			, _lowerCAmelCase					):

										"""simple docstring"""




										super().__init__(_lowerCAmelCase			, device_placement=_lowerCAmelCase			, scaler=_lowerCAmelCase					)
										__SCREAMING_SNAKE_CASE:				str           =   hasattr(self.optimizer			, '''overflow'''					)






				def 			snake_case_    (  self			, _lowerCAmelCase=None					):

										"""simple docstring"""




										pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed






				def 			snake_case_    (  self					):

										"""simple docstring"""




										pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed






				@property
				def 			snake_case_    (  self					):

										"""simple docstring"""




										if self.__has_overflow__:
																return self.optimizer.overflow
										return False





class 				a			(      __lowercase			):






				def __init__(  self			, _lowerCAmelCase			, _lowerCAmelCase					):

										"""simple docstring"""




										super().__init__(_lowerCAmelCase			, _lowerCAmelCase					)






				def 			snake_case_    (  self					):

										"""simple docstring"""




										pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed





class 				a			:






				def __init__(  self			, _lowerCAmelCase			, _lowerCAmelCase=0.001			, _lowerCAmelCase=0			, **_lowerCAmelCase					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				str           =   params
										__SCREAMING_SNAKE_CASE:				int           =   lr
										__SCREAMING_SNAKE_CASE:				List[str]           =   weight_decay
										__SCREAMING_SNAKE_CASE:				List[Any]           =   kwargs





class 				a			:






				def __init__(  self			, _lowerCAmelCase			, _lowerCAmelCase=None			, _lowerCAmelCase=0			, **_lowerCAmelCase					):

										"""simple docstring"""




										__SCREAMING_SNAKE_CASE:				int           =   optimizer
										__SCREAMING_SNAKE_CASE:				int           =   total_num_steps
										__SCREAMING_SNAKE_CASE:				Optional[int]           =   warmup_num_steps
										__SCREAMING_SNAKE_CASE:				str           =   kwargs



