'''simple docstring'''





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    :    List[str]   ,			__a    :    Any ):
         if isinstance(__a   ,			__a ):
              # 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
              UpperCAmelCase_           =   deepcopy(__a )
         elif os.path.exists(__a ):
              with io.open(__a   ,			"r"   ,			encoding="utf-8" ) as f:
                   UpperCAmelCase_           =   json.load(__a )
         else:
              try:
                   UpperCAmelCase_           =   baseaa.urlsafe_baadecode(__a ).decode("utf-8" )
                   UpperCAmelCase_           =   json.loads(__a )
              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}""" )

         UpperCAmelCase_           =   config

         self.set_stage_and_offload()



    def 					_lowercase						(self    :    Optional[Any] ):
         # zero stage - this is done as early as possible, before model is created, to allow
         # ``is_deepspeed_zero3_enabled`` query and getting to the early deepspeed config object
         # during ``zero.Init()`` which needs to know the dtype, and some other hparams.
         UpperCAmelCase_           =   self.get_value("zero_optimization.stage"   ,			-1 )

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



    def 					_lowercase						(self    :    Tuple   ,			__a    :    int ):
         UpperCAmelCase_           =   self.config

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

         return config, ds_key



    def 					_lowercase						(self    :    Union[str, Any]   ,			__a    :    Union[str, Any]   ,			__a    :    List[Any]=None ):
         UpperCAmelCase_    , UpperCAmelCase_           =   self.find_config_node(__a )
         if config is None:
              return default
         return config.get(__a   ,			__a )



    def 					_lowercase						(self    :    Optional[int]   ,			__a    :    List[str]   ,			__a    :    Tuple=False ):
         UpperCAmelCase_           =   self.config

         # find the config node of interest if it exists
         UpperCAmelCase_           =   ds_key_long.split("." )
         for node in nodes:
              UpperCAmelCase_           =   config
              UpperCAmelCase_           =   config.get(__a )
              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(__a )



    def 					_lowercase						(self    :    Dict   ,			__a    :    Any ):
         UpperCAmelCase_           =   self.get_value(__a )
         return False if value is None else bool(__a )



    def 					_lowercase						(self    :    Dict   ,			__a    :    List[Any] ):
         UpperCAmelCase_           =   self.get_value(__a )
         return False if value is None else not bool(__a )



    def 					_lowercase						(self    :    Any ):
         return self._stage == 2



    def 					_lowercase						(self    :    Union[str, Any] ):
         return self._stage == 3






    def 					_lowercase						(self    :    Dict ):
         return self._offload




class        __A      :



    def __init__(self    :    Dict   ,			__a    :    List[str] ):
         UpperCAmelCase_           =   engine






    def 					_lowercase						(self    :    str   ,			__a    :    Tuple   ,			**__a    :    Tuple ):
         # runs backpropagation and handles mixed precision
         self.engine.backward(__a   ,			**__a )

         # 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      ( UpperCamelCase__	):



    def __init__(self    :    Union[str, Any]   ,			__a    :    int ):
         super().__init__(__a   ,			device_placement=__a   ,			scaler=__a )
         UpperCAmelCase_           =   hasattr(self.optimizer   ,			"overflow" )



    def 					_lowercase						(self    :    Dict   ,			__a    :    List[Any]=None ):
         pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed



    def 					_lowercase						(self    :    List[str] ):
         pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed






    @property
    def 					_lowercase						(self    :    str ):
         if self.__has_overflow__:
              return self.optimizer.overflow
         return False




class        __A      ( UpperCamelCase__	):



    def __init__(self    :    Optional[int]   ,			__a    :    Any   ,			__a    :    int ):
         super().__init__(__a   ,			__a )






    def 					_lowercase						(self    :    List[str] ):
         pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed




class        __A      :



    def __init__(self    :    Dict   ,			__a    :    Optional[int]   ,			__a    :    Dict=0.0_01   ,			__a    :    Any=0   ,			**__a    :    Dict ):
         UpperCAmelCase_           =   params
         UpperCAmelCase_           =   lr
         UpperCAmelCase_           =   weight_decay
         UpperCAmelCase_           =   kwargs




class        __A      :



    def __init__(self    :    Optional[int]   ,			__a    :    List[str]   ,			__a    :    List[str]=None   ,			__a    :    Dict=0   ,			**__a    :    Dict ):
         UpperCAmelCase_           =   optimizer
         UpperCAmelCase_           =   total_num_steps
         UpperCAmelCase_           =   warmup_num_steps
         UpperCAmelCase_           =   kwargs








import requests
from bsa import BeautifulSoup
def 				UpperCAmelCase_					(							__snake_case = "https://www.worldometers.info/coronavirus"						)     ->			dict:







 """simple docstring"""


 _lowercase							      =BeautifulSoup(requests.get(__snake_case						).text     ,						'''html.parser'''						)
 _lowercase							      =soup.findAll('''h1'''						)
 _lowercase							      =soup.findAll('''div'''     ,						{'''class''': '''maincounter-number'''}						)
 keys += soup.findAll('''span'''     ,						{'''class''': '''panel-title'''}						)
 values += soup.findAll('''div'''     ,						{'''class''': '''number-table-main'''}						)
 return {key.text.strip(): value.text.strip() for key, value in zip(__snake_case     ,						__snake_case						)}


if __name__ == "__main__":
  print('''\033[1m''' + '''COVID-19 Status of the World''' + '''\033[0m\n''')
  for key, value in world_covidaa_stats().items():
    print(f'''{key}\n{value}\n''')

