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





class 					A							(    unittest.TestCase					):


   def       lowercase_				(self					:						str		)						->    int:
         """simple docstring"""



         UpperCAmelCase__								=  _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		)




from typing import TYPE_CHECKING

from ...utils import _LazyModule


UpperCamelCase__    							= {'tokenization_bertweet': ['BertweetTokenizer']}


if TYPE_CHECKING:
      from .tokenization_bertweet import BertweetTokenizer

else:
      import sys

      UpperCamelCase__    							= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



