



"""simple docstring"""







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

import pytest
from parameterized import 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.py",
            "model_name_or_path": "distilbert-base-cased",
            "instance_type": "ml.g4dn.xlarge",
            "results": {"train_runtime": 6_5_0, "eval_accuracy": 0.6, "eval_loss": 0.9},
        },
        {
            "framework": "tensorflow",
            "script": "run_tf.py",
            "model_name_or_path": "distilbert-base-cased",
            "instance_type": "ml.g4dn.xlarge",
            "results": {"train_runtime": 6_0_0, "eval_accuracy": 0.3, "eval_loss": 0.9},
        },
    ]    )
class        __A       (	unittest.TestCase    ):







		'''simple docstring'''





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






				"""simple docstring"""



				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=_snake_case			,)
				assert hasattr(self			,'''env'''						)







		def 					UpperCAmelCase    (	self						:  List[Any]			,_snake_case						:  Any=1						)					->		Any:






				"""simple docstring"""



				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}-single"""			,instance_count=_snake_case			,instance_type=self.instance_type			,debugger_hook_config=_snake_case			,hyperparameters={**self.env.hyperparameters, '''model_name_or_path''': self.model_name_or_path}			,metric_definitions=self.env.metric_definitions			,py_version='''py36'''			,)







		def 					UpperCAmelCase    (	self						:  Tuple			,_snake_case						:  List[Any]						)					->		List[Any]:






				"""simple docstring"""



				TrainingJobAnalytics(_snake_case						).export_csv(f"""{self.env.test_path}/{job_name}_metrics.csv"""						)







		def 					UpperCAmelCase    (	self						:  List[Any]						)					->		Optional[int]:






				"""simple docstring"""



				lowercase__   :    Tuple				=			self.create_estimator()

				# run training
				estimator.fit()

				# result dataframe
				lowercase__   :    Any				=			TrainingJobAnalytics(estimator.latest_training_job.name						).dataframe()

				# extract kpis
				lowercase__   :    Any				=			list(result_metrics_df[result_metrics_df.metric_name == '''eval_accuracy''']['''value''']						)
				lowercase__   :    Dict				=			list(result_metrics_df[result_metrics_df.metric_name == '''eval_loss''']['''value''']						)
				# get train time from SageMaker job, this includes starting, preprocessing, stopping
				lowercase__   :    List[Any]				=			(
				    Session().describe_training_job(estimator.latest_training_job.name						).get('''TrainingTimeInSeconds'''			,999_999						)
				)

				# 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}			,_snake_case						)





'''simple docstring'''






# using dfs for finding eulerian path traversal




def     snake_case_					(     lowerCAmelCase_       ,   lowerCAmelCase_       ,   lowerCAmelCase_       ,   lowerCAmelCase_=None		)->		List[str]:





       '''simple docstring'''


       _UpperCAmelCase  :						Any			     = (path or []) + [u]
       for v in graph[u]:
              if visited_edge[u][v] is False:
                     _UpperCAmelCase     ,_UpperCAmelCase  :						Tuple			     = True, True
                     _UpperCAmelCase  :						List[Any]			     = dfs(lowerCAmelCase_       ,   lowerCAmelCase_       ,   lowerCAmelCase_       ,   lowerCAmelCase_		)
       return path




def     snake_case_					(     lowerCAmelCase_       ,   lowerCAmelCase_		)->		Optional[int]:





       '''simple docstring'''


       _UpperCAmelCase  :						Optional[Any]			     = 0
       _UpperCAmelCase  :						Optional[int]			     = -1
       for i in range(lowerCAmelCase_		):
              if i not in graph.keys():
                     continue
              if len(graph[i]		) % 2 == 1:
                     odd_degree_nodes += 1
                     _UpperCAmelCase  :						Optional[int]			     = i
       if odd_degree_nodes == 0:
              return 1, odd_node
       if odd_degree_nodes == 2:
              return 2, odd_node
       return 3, odd_node




def     snake_case_					(     lowerCAmelCase_       ,   lowerCAmelCase_		)->		List[Any]:





       '''simple docstring'''


       _UpperCAmelCase  :						str			     = [[False for _ in range(max_node + 1		)] for _ in range(max_node + 1		)]
       _UpperCAmelCase     ,_UpperCAmelCase  :						int			     = check_circuit_or_path(lowerCAmelCase_       ,   lowerCAmelCase_		)
       if check == 3:
              print("""graph is not Eulerian"""		)
              print("""no path"""		)
              return
       _UpperCAmelCase  :						Dict			     = 1
       if check == 2:
              _UpperCAmelCase  :						Dict			     = odd_node
              print("""graph has a Euler path"""		)
       if check == 1:
              print("""graph has a Euler cycle"""		)
       _UpperCAmelCase  :						Dict			     = dfs(lowerCAmelCase_       ,   lowerCAmelCase_       ,   lowerCAmelCase_		)
       print(lowerCAmelCase_		)




def     snake_case_					(     )->		Union[str, Any]:





       '''simple docstring'''


       _UpperCAmelCase  :						Any			     = {1: [2, 3, 4], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [4]}
       _UpperCAmelCase  :						int			     = {1: [2, 3, 4, 5], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [1, 4]}
       _UpperCAmelCase  :						Tuple			     = {1: [2, 3, 4], 2: [1, 3, 4], 3: [1, 2], 4: [1, 2, 5], 5: [4]}
       _UpperCAmelCase  :						List[Any]			     = {1: [2, 3], 2: [1, 3], 3: [1, 2]}
       _UpperCAmelCase  :						List[str]			     = {
           1: [],
           2: []
           # all degree is zero
       }
       _UpperCAmelCase  :						Union[str, Any]			     = 10
       check_euler(lowerCAmelCase_       ,   lowerCAmelCase_		)
       check_euler(lowerCAmelCase_       ,   lowerCAmelCase_		)
       check_euler(lowerCAmelCase_       ,   lowerCAmelCase_		)
       check_euler(lowerCAmelCase_       ,   lowerCAmelCase_		)
       check_euler(lowerCAmelCase_       ,   lowerCAmelCase_		)


if __name__ == "__main__":
   main()



