





"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


a						: Union[str, Any]     	=			logging.get_logger(__name__)

a						: Dict     	=			{
    '''kssteven/ibert-roberta-base''': '''https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json''',
    '''kssteven/ibert-roberta-large''': '''https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json''',
    '''kssteven/ibert-roberta-large-mnli''': (
        '''https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json'''
    ),
}


class        __UpperCamelCase				(						a__						):
							lowerCamelCase   :					Optional[int]      					="""ibert"""






							def __init__(   self      ,					lowerCAmelCase__=3_0522      ,					lowerCAmelCase__=768      ,					lowerCAmelCase__=12      ,					lowerCAmelCase__=12      ,					lowerCAmelCase__=3072      ,					lowerCAmelCase__="gelu"      ,					lowerCAmelCase__=0.1      ,					lowerCAmelCase__=0.1      ,					lowerCAmelCase__=512      ,					lowerCAmelCase__=2      ,					lowerCAmelCase__=0.02      ,					lowerCAmelCase__=1E-12      ,					lowerCAmelCase__=1      ,					lowerCAmelCase__=0      ,					lowerCAmelCase__=2      ,					lowerCAmelCase__="absolute"      ,					lowerCAmelCase__=False      ,					lowerCAmelCase__="none"      ,					**lowerCAmelCase__      ,					)	-> str:
								super().__init__(pad_token_id=lowerCAmelCase__      ,					bos_token_id=lowerCAmelCase__      ,					eos_token_id=lowerCAmelCase__      ,					**lowerCAmelCase__      )

								a      :		List[str]	=				vocab_size
								a      :		List[Any]	=				hidden_size
								a      :		Tuple	=				num_hidden_layers
								a      :		Optional[int]	=				num_attention_heads
								a      :		Optional[Any]	=				hidden_act
								a      :		Union[str, Any]	=				intermediate_size
								a      :		List[Any]	=				hidden_dropout_prob
								a      :		Optional[int]	=				attention_probs_dropout_prob
								a      :		Optional[Any]	=				max_position_embeddings
								a      :		str	=				type_vocab_size
								a      :		str	=				initializer_range
								a      :		Tuple	=				layer_norm_eps
								a      :		Union[str, Any]	=				position_embedding_type
								a      :		Union[str, Any]	=				quant_mode
								a      :		Union[str, Any]	=				force_dequant


class        __UpperCamelCase				(						a__						):






							@property
							def     __a   (   self      )	-> Mapping[str, Mapping[int, str]]:
								if self.task == "multiple-choice":
									a      :		Dict	=				{0: "batch", 1: "choice", 2: "sequence"}
								else:
									a      :		Dict	=				{0: "batch", 1: "sequence"}
								return OrderedDict(
								    [
								        ("input_ids", dynamic_axis),
								        ("attention_mask", dynamic_axis),
								    ]      )









"""simple docstring"""




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






							def     __a   (   self      )	-> List[str]:
								# If no defaults are changed, `to_kwargs` returns an empty dict.
								a      :		str	=				_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      )


