


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

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


class     __UpperCAmelCase							:


     """simple docstring"""


     def __init__(	self  ,       __A    ):
        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
           __a					=  deepcopy(__A    )
        elif os.path.exists(__A    ):
           with io.open(__A  ,       """r"""  ,       encoding="""utf-8"""    ) as f:
              __a					=  json.load(__A    )
        else:
           try:
              __a					=  baseaa.urlsafe_baadecode(__A    ).decode("""utf-8"""    )
              __a					=  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}'''    )

        __a					=  config

        self.set_stage_and_offload()


     def 	snake_case_  (	self    ):
        # 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.
        __a					=  self.get_value("""zero_optimization.stage"""  ,       -1    )

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


     def 	snake_case_  (	self  ,       __A    ):
        __a					=  self.config

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

        return config, ds_key


     def 	snake_case_  (	self  ,       __A  ,       __A=None    ):
        __a	,    __a					=  self.find_config_node(__A    )
        if config is None:
           return default
        return config.get(__A  ,       __A    )


     def 	snake_case_  (	self  ,       __A  ,       __A=False    ):
        __a					=  self.config

        # find the config node of interest if it exists
        __a					=  ds_key_long.split("""."""    )
        for node in nodes:
           __a					=  config
           __a					=  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 	snake_case_  (	self  ,       __A    ):
        __a					=  self.get_value(__A    )
        return False if value is None else bool(__A    )


     def 	snake_case_  (	self  ,       __A    ):
        __a					=  self.get_value(__A    )
        return False if value is None else not bool(__A    )


     def 	snake_case_  (	self    ):
        return self._stage == 2


     def 	snake_case_  (	self    ):
        return self._stage == 3


     def 	snake_case_  (	self    ):
        return self._offload







class     __UpperCAmelCase							:


     """simple docstring"""


     def __init__(	self  ,       __A    ):
        __a					=  engine


     def 	snake_case_  (	self  ,       __A  ,       **__A    ):
        # 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     __UpperCAmelCase							(       __A							):


     """simple docstring"""


     def __init__(	self  ,       __A    ):
        super().__init__(__A  ,       device_placement=__A  ,       scaler=__A    )
        __a					=  hasattr(self.optimizer  ,       """overflow"""    )


     def 	snake_case_  (	self  ,       __A=None    ):
        pass  # `accelerator.backward(loss)` is doing that automatically. Therefore, its implementation is not needed


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


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







class     __UpperCAmelCase							(       __A							):


     """simple docstring"""


     def __init__(	self  ,       __A  ,       __A    ):
        super().__init__(__A  ,       __A    )


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







class     __UpperCAmelCase							:


     """simple docstring"""


     def __init__(	self  ,       __A  ,       __A=0.001  ,       __A=0  ,       **__A    ):
        __a					=  params
        __a					=  lr
        __a					=  weight_decay
        __a					=  kwargs







class     __UpperCAmelCase							:


     """simple docstring"""


     def __init__(	self  ,       __A  ,       __A=None  ,       __A=0  ,       **__A    ):
        __a					=  optimizer
        __a					=  total_num_steps
        __a					=  warmup_num_steps
        __a					=  kwargs









import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


UpperCamelCase__ :   List[Any]						=							pytest.mark.integration





@pytest.mark.parametrize('path'  ,							['paws', 'csv']  )
def        __UpperCAmelCase						(							lowerCamelCase_ :     Any  ,							lowerCamelCase_ :     int  )       ->  Any:







			"""simple docstring"""





			inspect_dataset(lowerCamelCase_  ,							lowerCamelCase_  )
			SCREAMING_SNAKE_CASE_   : List[str]					  =      path + '.py'
			assert script_name in os.listdir(lowerCamelCase_  )
			assert "__pycache__" not in os.listdir(lowerCamelCase_  )





@pytest.mark.filterwarnings('ignore:inspect_metric is deprecated:FutureWarning'  )
@pytest.mark.filterwarnings('ignore:metric_module_factory is deprecated:FutureWarning'  )
@pytest.mark.parametrize('path'  ,							['accuracy']  )
def        __UpperCAmelCase						(							lowerCamelCase_ :     Optional[int]  ,							lowerCamelCase_ :     Dict  )       ->  Optional[Any]:







			"""simple docstring"""





			inspect_metric(lowerCamelCase_  ,							lowerCamelCase_  )
			SCREAMING_SNAKE_CASE_   : Tuple					  =      path + '.py'
			assert script_name in os.listdir(lowerCamelCase_  )
			assert "__pycache__" not in os.listdir(lowerCamelCase_  )





@pytest.mark.parametrize(
    'path, config_name, expected_splits'  ,							[
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]  ,							)
def        __UpperCAmelCase						(							lowerCamelCase_ :     List[str]  ,							lowerCamelCase_ :     Dict  ,							lowerCamelCase_ :     Optional[Any]  )       ->  Optional[int]:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : int					  =      get_dataset_config_info(lowerCamelCase_  ,							config_name=lowerCamelCase_  )
			assert info.config_name == config_name
			assert list(info.splits.keys()  ) == expected_splits





@pytest.mark.parametrize(
    'path, config_name, expected_exception'  ,							[
        ('paws', None, ValueError),
    ]  ,							)
def        __UpperCAmelCase						(							lowerCamelCase_ :     Union[str, Any]  ,							lowerCamelCase_ :     Optional[int]  ,							lowerCamelCase_ :     int  )       ->  List[Any]:







			"""simple docstring"""





			with pytest.raises(lowerCamelCase_  ):
						get_dataset_config_info(lowerCamelCase_  ,							config_name=lowerCamelCase_  )





@pytest.mark.parametrize(
    'path, expected'  ,							[
        ('squad', 'plain_text'),
        ('acronym_identification', 'default'),
        ('lhoestq/squad', 'plain_text'),
        ('lhoestq/test', 'default'),
        ('lhoestq/demo1', 'lhoestq--demo1'),
        ('dalle-mini/wit', 'dalle-mini--wit'),
    ]  ,							)
def        __UpperCAmelCase						(							lowerCamelCase_ :     Tuple  ,							lowerCamelCase_ :     List[Any]  )       ->  Dict:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : str					  =      get_dataset_config_names(lowerCamelCase_  )
			assert expected in config_names





@pytest.mark.parametrize(
    'path, expected_configs, expected_splits_in_first_config'  ,							[
        ('squad', ['plain_text'], ['train', 'validation']),
        ('dalle-mini/wit', ['dalle-mini--wit'], ['train']),
        ('paws', ['labeled_final', 'labeled_swap', 'unlabeled_final'], ['train', 'test', 'validation']),
    ]  ,							)
def        __UpperCAmelCase						(							lowerCamelCase_ :     List[Any]  ,							lowerCamelCase_ :     int  ,							lowerCamelCase_ :     Union[str, Any]  )       ->  Optional[int]:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : str					  =      get_dataset_infos(lowerCamelCase_  )
			assert list(infos.keys()  ) == expected_configs
			SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      expected_configs[0]
			assert expected_config in infos
			SCREAMING_SNAKE_CASE_   : Any					  =      infos[expected_config]
			assert info.config_name == expected_config
			assert list(info.splits.keys()  ) == expected_splits_in_first_config





@pytest.mark.parametrize(
    'path, expected_config, expected_splits'  ,							[
        ('squad', 'plain_text', ['train', 'validation']),
        ('dalle-mini/wit', 'dalle-mini--wit', ['train']),
        ('paws', 'labeled_final', ['train', 'test', 'validation']),
    ]  ,							)
def        __UpperCAmelCase						(							lowerCamelCase_ :     Union[str, Any]  ,							lowerCamelCase_ :     List[str]  ,							lowerCamelCase_ :     str  )       ->  str:







			"""simple docstring"""





			SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      get_dataset_infos(lowerCamelCase_  )
			assert expected_config in infos
			SCREAMING_SNAKE_CASE_   : Tuple					  =      infos[expected_config]
			assert info.config_name == expected_config
			assert list(info.splits.keys()  ) == expected_splits





@pytest.mark.parametrize(
    'path, config_name, expected_exception'  ,							[
        ('paws', None, ValueError),
    ]  ,							)
def        __UpperCAmelCase						(							lowerCamelCase_ :     int  ,							lowerCamelCase_ :     int  ,							lowerCamelCase_ :     int  )       ->  int:







			"""simple docstring"""





			with pytest.raises(lowerCamelCase_  ):
						get_dataset_split_names(lowerCamelCase_  ,							config_name=lowerCamelCase_  )



