






'''simple docstring'''







import json
import os
import subprocess
import unittest
from ast import literal_eval

import pytest
from parameterized import parameterized, parameterized_class

from . import is_sagemaker_available


if is_sagemaker_available():
							from sagemaker import Session, TrainingJobAnalytics
							from sagemaker.huggingface import HuggingFace




@pytest.mark.skipif(
    literal_eval(os.getenv('TEST_SAGEMAKER' ,'False'      )      ) is not True ,reason='Skipping test because should only be run when releasing minor transformers version' ,)
@pytest.mark.usefixtures('sm_env'      )
@parameterized_class(
    [
        {
            'framework': 'pytorch',
            'script': 'run_glue_model_parallelism.py',
            'model_name_or_path': 'roberta-large',
            'instance_type': 'ml.p3dn.24xlarge',
            'results': {'train_runtime': 1600, 'eval_accuracy': 0.3, 'eval_loss': 1.2},
        },
        {
            'framework': 'pytorch',
            'script': 'run_glue.py',
            'model_name_or_path': 'roberta-large',
            'instance_type': 'ml.p3dn.24xlarge',
            'results': {'train_runtime': 1600, 'eval_accuracy': 0.3, 'eval_loss': 1.2},
        },
    ]      )
class 		UpperCamelCase__     (unittest.TestCase      ):




		'''simple docstring'''





		def       UpperCamelCase_       (   self							):
								if self.framework == "pytorch":
														subprocess.run(
														    F'''cp ./examples/pytorch/text-classification/run_glue.py {self.env.test_path}/run_glue.py'''.split() ,encoding="""utf-8""" ,check=_lowerCAmelCase ,)
								assert hasattr(self ,"""env"""							)






		def       UpperCamelCase_       (   self ,_lowerCAmelCase							):
								# configuration for running training on smdistributed Model Parallel
								lowerCamelCase__								=	{
								    """enabled""": True,
								    """processes_per_host""": 8,
								}
								lowerCamelCase__								=	{
								    """enabled""": True,
								    """parameters""": {
								        """microbatches""": 4,
								        """placement_strategy""": """spread""",
								        """pipeline""": """interleaved""",
								        """optimize""": """speed""",
								        """partitions""": 4,
								        """ddp""": True,
								    },
								}

								lowerCamelCase__								=	{"""smdistributed""": {"""modelparallel""": smp_options}, """mpi""": mpi_options}

								lowerCamelCase__								=	"""trainer""" if self.script == """run_glue.py""" else """smtrainer"""
								# creates estimator
								return HuggingFace(
								    entry_point=self.script ,source_dir=self.env.test_path ,role=self.env.role ,image_uri=self.env.image_uri ,base_job_name=F'''{self.env.base_job_name}-{instance_count}-smp-{name_extension}''' ,instance_count=_lowerCAmelCase ,instance_type=self.instance_type ,debugger_hook_config=_lowerCAmelCase ,hyperparameters={
								        **self.env.hyperparameters,
								        """model_name_or_path""": self.model_name_or_path,
								        """max_steps""": 5_00,
								    } ,metric_definitions=self.env.metric_definitions ,distribution=_lowerCAmelCase ,py_version="""py36""" ,)






		def       UpperCamelCase_       (   self ,_lowerCAmelCase							):
								TrainingJobAnalytics(_lowerCAmelCase							).export_csv(F'''{self.env.test_path}/{job_name}_metrics.csv'''							)






		@parameterized.expand([(1,)]							)
		def       UpperCamelCase_       (   self ,_lowerCAmelCase							):
								# create estimator
								lowerCamelCase__								=	self.create_estimator(_lowerCAmelCase							)

								# run training
								estimator.fit()

								# result dataframe
								lowerCamelCase__								=	TrainingJobAnalytics(estimator.latest_training_job.name							).dataframe()

								# extract kpis
								lowerCamelCase__								=	list(result_metrics_df[result_metrics_df.metric_name == """eval_accuracy"""]["""value"""]							)
								lowerCamelCase__								=	list(result_metrics_df[result_metrics_df.metric_name == """eval_loss"""]["""value"""]							)
								# get train time from SageMaker job, this includes starting, preprocessing, stopping
								lowerCamelCase__								=	(
								    Session().describe_training_job(estimator.latest_training_job.name							).get("""TrainingTimeInSeconds""" ,99_99_99							)
								)

								# assert kpis
								assert train_runtime <= self.results["train_runtime"]
								assert all(t >= self.results["""eval_accuracy"""] for t in eval_accuracy							)
								assert all(t <= self.results["""eval_loss"""] for t in eval_loss							)

								# dump tests result into json file to share in PR
								with open(F'''{estimator.latest_training_job.name}.json''' ,"""w"""							) as outfile:
														json.dump({"""train_time""": train_runtime, """eval_accuracy""": eval_accuracy, """eval_loss""": eval_loss} ,_lowerCAmelCase							)




from ..utils import DummyObject, requires_backends



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  List[str]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Any    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  List[Any]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  List[Any]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  List[Any]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Union[str, Any]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Dict    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  List[Any]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  List[str]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  List[Any]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  List[Any]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Any    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Optional[int]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  str    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Dict    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  int    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  int    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  str    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  List[Any]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  List[str]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Optional[int]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Union[str, Any]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Tuple    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  List[Any]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  str    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Dict    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  str    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Any    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Union[str, Any]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Optional[Any]    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



class        _a		(metaclass=__magic_name__							):


					'''simple docstring'''






					UpperCAmelCase__:  Tuple    				=			['''sentencepiece''']






					def __init__(					self       ,			*A__       ,			**A__     ):
						requires_backends(self       ,			["""sentencepiece"""]     )



