


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

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







class       lowerCamelCase__   :





     def __init__(self		,     UpperCAmelCase       )     ->   Tuple:




      if isinstance(SCREAMING_SNAKE_CASE__		,     SCREAMING_SNAKE_CASE__       ):
       # 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
       _lowercase							      =deepcopy(SCREAMING_SNAKE_CASE__       )
      elif os.path.exists(SCREAMING_SNAKE_CASE__       ):
       with io.open(SCREAMING_SNAKE_CASE__		,     '''r'''		,     encoding='''utf-8'''       ) as f:
        _lowercase							      =json.load(SCREAMING_SNAKE_CASE__       )
      else:
       try:
        _lowercase							      =baseaa.urlsafe_baadecode(SCREAMING_SNAKE_CASE__       ).decode('''utf-8'''       )
        _lowercase							      =json.loads(SCREAMING_SNAKE_CASE__       )
       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}"       )

      _lowercase							      =config

      self.set_stage_and_offload()





     def      __A					(self       )     ->   str:
      _lowercase							      =self.get_value('''zero_optimization.stage'''		,     -1       )

      # offload
      _lowercase							      =False
      if self.is_zeroa() or self.is_zeroa():
       _lowercase							      =set(['''cpu''', '''nvme''']       )
       _lowercase							      =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:
        _lowercase							      =True





     def      __A					(self		,     UpperCAmelCase       )     ->   Any:
      _lowercase							      =self.config

      # find the config node of interest if it exists
      _lowercase							      =ds_key_long.split('''.'''       )
      _lowercase							      =nodes.pop()
      for node in nodes:
       _lowercase							      =config.get(SCREAMING_SNAKE_CASE__       )
       if config is None:
        return None, ds_key

      return config, ds_key





     def      __A					(self		,     UpperCAmelCase		,     UpperCAmelCase=None       )     ->   Dict:
      _lowercase							      =self.find_config_node(SCREAMING_SNAKE_CASE__       )
      if config is None:
       return default
      return config.get(SCREAMING_SNAKE_CASE__		,     SCREAMING_SNAKE_CASE__       )





     def      __A					(self		,     UpperCAmelCase		,     UpperCAmelCase=False       )     ->   Union[str, Any]:
      _lowercase							      =self.config

      # find the config node of interest if it exists
      _lowercase							      =ds_key_long.split('''.'''       )
      for node in nodes:
       _lowercase							      =config
       _lowercase							      =config.get(SCREAMING_SNAKE_CASE__       )
       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(SCREAMING_SNAKE_CASE__       )





     def      __A					(self		,     UpperCAmelCase       )     ->   Any:
      _lowercase							      =self.get_value(SCREAMING_SNAKE_CASE__       )
      return False if value is None else bool(SCREAMING_SNAKE_CASE__       )





     def      __A					(self		,     UpperCAmelCase       )     ->   int:
      _lowercase							      =self.get_value(SCREAMING_SNAKE_CASE__       )
      return False if value is None else not bool(SCREAMING_SNAKE_CASE__       )





     def      __A					(self       )     ->   List[Any]:
      return self._stage == 2





     def      __A					(self       )     ->   List[Any]:
      return self._stage == 3





     def      __A					(self       )     ->   Optional[Any]:
      return self._offload







class       lowerCamelCase__   :





     def __init__(self		,     UpperCAmelCase       )     ->   Dict:
      _lowercase							      =engine





     def      __A					(self		,     UpperCAmelCase		,     **UpperCAmelCase       )     ->   Any:
      self.engine.backward(SCREAMING_SNAKE_CASE__		,     **SCREAMING_SNAKE_CASE__       )

      # 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       lowerCamelCase__   (       a__):





     def __init__(self		,     UpperCAmelCase       )     ->   Union[str, Any]:
      super().__init__(SCREAMING_SNAKE_CASE__		,     device_placement=SCREAMING_SNAKE_CASE__		,     scaler=SCREAMING_SNAKE_CASE__       )
      _lowercase							      =hasattr(self.optimizer		,     '''overflow'''       )





     def      __A					(self		,     UpperCAmelCase=None       )     ->   Optional[Any]:
      pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed





     def      __A					(self       )     ->   Optional[Any]:
      pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed





     @property
     def      __A					(self       )     ->   Optional[int]:




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







class       lowerCamelCase__   (       a__):





     def __init__(self		,     UpperCAmelCase		,     UpperCAmelCase       )     ->   List[str]:
      super().__init__(SCREAMING_SNAKE_CASE__		,     SCREAMING_SNAKE_CASE__       )





     def      __A					(self       )     ->   Optional[int]:
      pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed







class       lowerCamelCase__   :





     def __init__(self		,     UpperCAmelCase		,     UpperCAmelCase=0.001		,     UpperCAmelCase=0		,     **UpperCAmelCase       )     ->   Dict:
      _lowercase							      =params
      _lowercase							      =lr
      _lowercase							      =weight_decay
      _lowercase							      =kwargs







class       lowerCamelCase__   :





     def __init__(self		,     UpperCAmelCase		,     UpperCAmelCase=None		,     UpperCAmelCase=0		,     **UpperCAmelCase       )     ->   Dict:
      _lowercase							      =optimizer
      _lowercase							      =total_num_steps
      _lowercase							      =warmup_num_steps
      _lowercase							      =kwargs



"""simple docstring"""




import math
import unittest

def lowercase_  (   _snake_case						):
							assert isinstance(_snake_case   ,_snake_case						) and (
							    number >= 0
							), "'number' must been an int and positive"

							if 1 < number < 4:
														# 2 and 3 are primes
														return True
							elif number < 2 or number % 2 == 0 or number % 3 == 0:
														# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
														return False

							# All primes number are in format of 6k +/- 1
							for i in range(5   ,int(math.sqrt(_snake_case						) + 1						)   ,6						):
														if number % i == 0 or number % (i + 2) == 0:
																					return False
							return True



class 	lowerCAmelCase_						(unittest.TestCase  ):


				"""simple docstring"""



				def 	__magic_name__    (self    )					->		Dict:



											"""simple docstring"""




											self.assertTrue(is_prime(2    )    )
											self.assertTrue(is_prime(3    )    )
											self.assertTrue(is_prime(5    )    )
											self.assertTrue(is_prime(7    )    )
											self.assertTrue(is_prime(11    )    )
											self.assertTrue(is_prime(13    )    )
											self.assertTrue(is_prime(17    )    )
											self.assertTrue(is_prime(19    )    )
											self.assertTrue(is_prime(23    )    )
											self.assertTrue(is_prime(29    )    )



				def 	__magic_name__    (self    )					->		List[Any]:



											"""simple docstring"""




											with self.assertRaises(SCREAMING_SNAKE_CASE__    ):
																		is_prime(-19    )
											self.assertFalse(
											    is_prime(0    )   ,       """Zero doesn't have any positive factors, primes must have exactly two."""   ,       )
											self.assertFalse(
											    is_prime(1    )   ,       """One only has 1 positive factor, primes must have exactly two."""   ,       )
											self.assertFalse(is_prime(2 * 2    )    )
											self.assertFalse(is_prime(2 * 3    )    )
											self.assertFalse(is_prime(3 * 3    )    )
											self.assertFalse(is_prime(3 * 5    )    )
											self.assertFalse(is_prime(3 * 5 * 7    )    )


if __name__ == "__main__":
					unittest.main()




