

import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict



@dataclass
class SCREAMING_SNAKE_CASE     (  __snake_case			):
  """simple docstring"""






  lowerCamelCase   :      Optional[Any]										=ComputeEnvironment.AMAZON_SAGEMAKER
  lowerCamelCase   :      str										=True
  lowerCamelCase   :      str										="ml.p3.2xlarge"
  lowerCamelCase   :      Any										="accelerate_sagemaker_execution_role"
  lowerCamelCase   :      List[str]										="hf-sm"
  lowerCamelCase   :      Any										="us-east-1"
  lowerCamelCase   :      List[str]										=1
  lowerCamelCase   :      int										="accelerate-sagemaker-1"
  lowerCamelCase   :      Any										="1.6"
  lowerCamelCase   :      Tuple										="4.4"
  lowerCamelCase   :      Optional[Any]										="train.py"
  lowerCamelCase   :      Optional[int]										=[
      "--model_name_or_path",
      "bert",
      "--do_train",
      "False",
      "--epochs",
      "3",
      "--learning_rate",
      "5e-5",
      "--max_steps",
      "50.5",
  ]
  lowerCamelCase   :      int										=[
      "--model_name_or_path",
      "bert",
      "--do_train",
      "--do_test",
      "False",
      "--do_predict",
      "--epochs",
      "3",
      "--learning_rate",
      "5e-5",
      "--max_steps",
      "50.5",
  ]






class SCREAMING_SNAKE_CASE     (  unittest.TestCase			):
  """simple docstring"""






  def 	SCREAMING_SNAKE_CASE   (      self			:   Any   )							->     Optional[Any]:






     """simple docstring"""







     __lowerCAmelCase  :      Tuple    =						_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args   )
     assert isinstance(converted_args["""model_name_or_path"""]	,							a_   )
     assert isinstance(converted_args["""do_train"""]	,							a_   )
     assert isinstance(converted_args["""epochs"""]	,							a_   )
     assert isinstance(converted_args["""learning_rate"""]	,							a_   )
     assert isinstance(converted_args["""max_steps"""]	,							a_   )

     with pytest.raises(a_   ):
        _convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args   )





# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

__UpperCAmelCase								=			"""2.13.1"""

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse("""3.7"""):
   raise ImportWarning(
       """To use `datasets`, Python>=3.7 is required, and the current version of Python doesn't match this condition."""
   )

if version.parse(pyarrow.__version__).major < 8:
   raise ImportWarning(
       """To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn't match this condition.\n"""
       """If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`."""
   )

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

__UpperCAmelCase								=			concatenate_datasets
__UpperCAmelCase								=			DownloadConfig
__UpperCAmelCase								=			DownloadManager
__UpperCAmelCase								=			DownloadMode
__UpperCAmelCase								=			DownloadConfig
__UpperCAmelCase								=			DownloadMode
__UpperCAmelCase								=			DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager


