





from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_						       =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_						       =	{
    """abeja/gpt-neox-japanese-2.7b""": """https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json""",
}

class 		UpperCamelCase__			(				lowerCAmelCase_       ):



     '''simple docstring'''

     __snake_case   :     Union[str, Any]		     =      "gpt_neox_japanese"






     def __init__(							self						:   Dict						,lowerCamelCase__						:   str=32000						,lowerCamelCase__						:   Any=2560						,lowerCamelCase__						:   Dict=32						,lowerCamelCase__						:   Optional[Any]=32						,lowerCamelCase__						:   Tuple=4						,lowerCamelCase__						:   Union[str, Any]="gelu"						,lowerCamelCase__						:   Union[str, Any]=1.00						,lowerCamelCase__						:   str=10000						,lowerCamelCase__						:   List[str]=2048						,lowerCamelCase__						:   Union[str, Any]=0.02						,lowerCamelCase__						:   List[str]=1e-5						,lowerCamelCase__						:   int=True						,lowerCamelCase__						:   int=31996						,lowerCamelCase__						:   Union[str, Any]=31999						,lowerCamelCase__						:   Optional[int]=0.1						,lowerCamelCase__						:   Optional[int]=0.0						,**lowerCamelCase__						:   int						,)					->		List[str]:




           '''simple docstring'''


           super().__init__(bos_token_id=lowerCamelCase__						,eos_token_id=lowerCamelCase__						,**lowerCamelCase__	)
           SCREAMING_SNAKE_CASE		=						vocab_size
           SCREAMING_SNAKE_CASE		=						max_position_embeddings
           SCREAMING_SNAKE_CASE		=						hidden_size
           SCREAMING_SNAKE_CASE		=						num_hidden_layers
           SCREAMING_SNAKE_CASE		=						num_attention_heads
           SCREAMING_SNAKE_CASE		=						intermediate_multiple_size
           SCREAMING_SNAKE_CASE		=						hidden_act
           SCREAMING_SNAKE_CASE		=						rotary_pct
           SCREAMING_SNAKE_CASE		=						rotary_emb_base
           SCREAMING_SNAKE_CASE		=						initializer_range
           SCREAMING_SNAKE_CASE		=						layer_norm_eps
           SCREAMING_SNAKE_CASE		=						use_cache
           SCREAMING_SNAKE_CASE		=						attention_dropout
           SCREAMING_SNAKE_CASE		=						hidden_dropout









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 		UpperCamelCase__			(				lowerCAmelCase_       ):



     '''simple docstring'''

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



     '''simple docstring'''

     def     SCREAMING_SNAKE_CASE__  (							self						:   Union[str, Any]	)					->		int:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args	)
           assert isinstance(converted_args["""model_name_or_path"""]						,lowerCamelCase__	)
           assert isinstance(converted_args["""do_train"""]						,lowerCamelCase__	)
           assert isinstance(converted_args["""epochs"""]						,lowerCamelCase__	)
           assert isinstance(converted_args["""learning_rate"""]						,lowerCamelCase__	)
           assert isinstance(converted_args["""max_steps"""]						,lowerCamelCase__	)

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


