

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     (  UpperCamelCase__			):
  """simple docstring"""






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






     """simple docstring"""







     __lowerCAmelCase  :      int    =						_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   )





__UpperCAmelCase								=			"""
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""

__UpperCAmelCase								=			[{"""type""": """code""", """content""": INSTALL_CONTENT}]
__UpperCAmelCase								=			{
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}


