






import os

import pytest
from attr import dataclass


UpperCamelCase								=		"us-east-1"  # defaults region

@dataclass
class 				lowerCAmelCase_	:
				_UpperCamelCase					:       str
				_UpperCamelCase					:       int							       = "arn:aws:iam::558105141721:role/sagemaker_execution_role"
				_UpperCamelCase					:       Dict							       = {
				    "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": 500,
				    "save_steps": 5500,
				}
				_UpperCamelCase					:       int							       = {**hyperparameters, "max_steps": 1000}


				@property
				def 						__a					(					self      ):
											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 						__a					(					self      ):
											return F"""{self.framework}-transfromers-test"""


				@property
				def 						__a					(					self      ):
											return F"""./tests/sagemaker/scripts/{self.framework}"""


				@property
				def 						__a					(					self      ):
											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    __magic_name__    (	SCREAMING_SNAKE_CASE				)     ->    Any:
							_lowercase							:   List[Any] 							=   SageMakerTestEnvironment(framework=request.cls.framework				)








from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE__					:     Optional[int]       =     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__					:     List[str]       =     {
    'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/config.json',
    'umberto-commoncrawl-cased-v1': (
        'https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'
    ),
    'umberto-wikipedia-uncased-v1': (
        'https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'
    ),
}


class 		_SCREAMING_SNAKE_CASE     (						A     ):
     __SCREAMING_SNAKE_CASE     					=    '''camembert'''


     def __init__(  self							,					A_=3_05_22							,					A_=7_68							,					A_=12							,					A_=12							,					A_=30_72							,					A_="gelu"							,					A_=0.1							,					A_=0.1							,					A_=5_12							,					A_=2							,					A_=0.0_2							,					A_=1e-12							,					A_=1							,					A_=0							,					A_=2							,					A_="absolute"							,					A_=True							,					A_=None							,					**A_							,					):
       super().__init__(pad_token_id=A_							,					bos_token_id=A_							,					eos_token_id=A_							,					**A_    )

       _UpperCAmelCase		:							Optional[Any]							=     vocab_size
       _UpperCAmelCase		:							int							=     hidden_size
       _UpperCAmelCase		:							Any							=     num_hidden_layers
       _UpperCAmelCase		:							Optional[Any]							=     num_attention_heads
       _UpperCAmelCase		:							Dict							=     hidden_act
       _UpperCAmelCase		:							str							=     intermediate_size
       _UpperCAmelCase		:							str							=     hidden_dropout_prob
       _UpperCAmelCase		:							List[Any]							=     attention_probs_dropout_prob
       _UpperCAmelCase		:							List[Any]							=     max_position_embeddings
       _UpperCAmelCase		:							Union[str, Any]							=     type_vocab_size
       _UpperCAmelCase		:							List[Any]							=     initializer_range
       _UpperCAmelCase		:							Optional[Any]							=     layer_norm_eps
       _UpperCAmelCase		:							int							=     position_embedding_type
       _UpperCAmelCase		:							Tuple							=     use_cache
       _UpperCAmelCase		:							Any							=     classifier_dropout


class 		_SCREAMING_SNAKE_CASE     (						A     ):


     @property
     def        __snake_case(  self    ):
       if self.task == "multiple-choice":
         _UpperCAmelCase		:							Any							=     {0: """batch""", 1: """choice""", 2: """sequence"""}
       else:
         _UpperCAmelCase		:							List[Any]							=     {0: """batch""", 1: """sequence"""}
       return OrderedDict(
           [
               ("""input_ids""", dynamic_axis),
               ("""attention_mask""", dynamic_axis),
           ]    )





