
"""simple docstring"""





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


UpperCamelCase_					:						Tuple				= logging.get_logger(__name__)

UpperCamelCase_					:						Dict				= {
    '''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json''',
    # See all GPTNeoX models at https://huggingface.co/models?filter=gpt_neox
}



class __lowerCAmelCase				(					_lowercase      ):




			"""simple docstring"""







			snake_case	      =				"gpt_neox"




			def __init__(				self						:					Dict       ,   _snake_case						:					List[Any]=50_432       ,   _snake_case						:					Optional[Any]=6_144       ,   _snake_case						:					Dict=44       ,   _snake_case						:					Any=64       ,   _snake_case						:					Any=24_576       ,   _snake_case						:					str="gelu"       ,   _snake_case						:					List[Any]=0.2_5       ,   _snake_case						:					Union[str, Any]=10_000       ,   _snake_case						:					int=0.0       ,   _snake_case						:					int=0.0       ,   _snake_case						:					Any=0.1       ,   _snake_case						:					str=2_048       ,   _snake_case						:					Any=0.0_2       ,   _snake_case						:					Optional[Any]=1e-5       ,   _snake_case						:					List[str]=True       ,   _snake_case						:					Union[str, Any]=0       ,   _snake_case						:					Optional[Any]=2       ,   _snake_case						:					Dict=False       ,   _snake_case						:					Union[str, Any]=True       ,   _snake_case						:					List[Any]=None       ,   **_snake_case						:					Any       ,   )      -> str:







								"""simple docstring"""
								super().__init__(bos_token_id=_snake_case       ,   eos_token_id=_snake_case       ,   **_snake_case	)
								A_				 =						vocab_size
								A_				 =						max_position_embeddings
								A_				 =						hidden_size
								A_				 =						num_hidden_layers
								A_				 =						num_attention_heads
								A_				 =						intermediate_size
								A_				 =						hidden_act
								A_				 =						rotary_pct
								A_				 =						rotary_emb_base
								A_				 =						attention_dropout
								A_				 =						hidden_dropout
								A_				 =						classifier_dropout
								A_				 =						initializer_range
								A_				 =						layer_norm_eps
								A_				 =						use_cache
								A_				 =						tie_word_embeddings
								A_				 =						use_parallel_residual
								A_				 =						rope_scaling
								self._rope_scaling_validation()

								if self.hidden_size % self.num_attention_heads != 0:
													raise ValueError(
													    "The hidden size is not divisble by the number of attention heads! Make sure to update them!"	)






			def      lowerCamelCase__     (				self						:					Dict	)      -> Tuple:







								"""simple docstring"""
								if self.rope_scaling is None:
													return

								if not isinstance(self.rope_scaling       ,   _snake_case	) or len(self.rope_scaling	) != 2:
													raise ValueError(
													    "`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, "
													    F'got {self.rope_scaling}'	)
								A_				 =						self.rope_scaling.get("type"       ,   _snake_case	)
								A_				 =						self.rope_scaling.get("factor"       ,   _snake_case	)
								if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
													raise ValueError(
													    F'`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}'	)
								if rope_scaling_factor is None or not isinstance(_snake_case       ,   _snake_case	) or rope_scaling_factor <= 1.0:
													raise ValueError(F'`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'	)






"""simple docstring"""





import os

import pytest
from attr import dataclass


UpperCamelCase_					:						str				= '''us-east-1'''  # defaults region



@dataclass
class __lowerCAmelCase				:




			"""simple docstring"""







			snake_case	      =				42
			snake_case	      =				"arn:aws:iam::558105141721:role/sagemaker_execution_role"
			snake_case	      =				{
			    "task_name": "mnli",
			    "per_device_train_batch_size": 16,
			    "per_device_eval_batch_size": 16,
			    "do_train": True,
			    "do_eval": True,
			    "do_predict": True,
			    "output_dir": "/opt/ml/model",
			    "overwrite_output_dir": True,
			    "max_steps": 5_00,
			    "save_steps": 55_00,
			}
			snake_case	      =				{**hyperparameters, "max_steps": 10_00}




			@property
			def      lowerCamelCase__     (				self						:					int	)      -> str:







								"""simple docstring"""
								if self.framework == "pytorch":
													return [
													    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
													    {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
													    {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
													]
								else:
													return [
													    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
													    {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
													    {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
													]




			@property
			def      lowerCamelCase__     (				self						:					Any	)      -> str:







								"""simple docstring"""
								return F'{self.framework}-transfromers-test'




			@property
			def      lowerCamelCase__     (				self						:					List[Any]	)      -> str:







								"""simple docstring"""
								return F'./tests/sagemaker/scripts/{self.framework}'






			@property
			def      lowerCamelCase__     (				self						:					Any	)      -> str:







								"""simple docstring"""
								if self.framework == "pytorch":
													return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
								else:
													return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"





@pytest.fixture(scope="class"				)
def 							A_     (__a				):

					'''simple docstring'''





					A_				 =						SageMakerTestEnvironment(framework=request.cls.framework				)




