






import json

import requests

from .fetch_github_info import AUTHENTICATED_USER_ENDPOINT, fetch_github_info

def        SCREAMING_SNAKE_CASE_					(						snake_case__							)					->     Optional[int]:




							class        lowercase_  :



								"""simple docstring"""





								def __init__(							self		,      __SCREAMING_SNAKE_CASE    )						->None:
															assert isinstance(__SCREAMING_SNAKE_CASE		,      (bytes, str)    )
															lowerCAmelCase     		=		content




								def       SCREAMING_SNAKE_CASE_    (							self    )						->Any:
															return json.loads(self.content    )

							def mock_response(*snake_case__       ,  **snake_case__							):
														assert args[0] == AUTHENTICATED_USER_ENDPOINT
														assert "Authorization" in kwargs["headers"]
														assert kwargs["headers"]["Authorization"].startswith('''token '''							)
														assert "Accept" in kwargs["headers"]
														return FakeResponse(B'''{"login":"test","id":1}'''							)

							monkeypatch.setattr(snake_case__       ,  '''get'''       ,  snake_case__							)
							lowerCAmelCase     		=		fetch_github_info('''token'''							)
							assert result["login"] == "test"
							assert result["id"] == 1




# as due to their complexity multi-gpu tests could impact other tests, and to aid debug we have those in a separate module.

import os
import sys

from transformers.testing_utils import TestCasePlus, execute_subprocess_async, get_gpu_count, require_torch_gpu, slow

from .utils import load_json




class        lowercase_  (  UpperCamelCase_						):



	"""simple docstring"""





	@classmethod
	def       SCREAMING_SNAKE_CASE_    (							cls    )						->Union[str, Any]:
								return cls




	@slow
	@require_torch_gpu
	def       SCREAMING_SNAKE_CASE_    (							self    )						->int:
								lowerCAmelCase     		=		self.get_auto_remove_tmp_dir()
								lowerCAmelCase     		=		F"\n            --model_name Helsinki-NLP/opus-mt-en-ro\n            --save_dir {output_dir}\n            --data_dir {self.test_file_dir_str}/test_data/wmt_en_ro\n            --num_beams 2\n            --task translation\n        ".split()

								# we want this test to run even if there is only one GPU, but if there are more we use them all
								lowerCAmelCase     		=		get_gpu_count()
								lowerCAmelCase     		=		F"\n            -m torch.distributed.launch\n            --nproc_per_node={n_gpu}\n            {self.test_file_dir}/run_distributed_eval.py\n        ".split()
								lowerCAmelCase     		=		[sys.executable] + distributed_args + args
								execute_subprocess_async(__SCREAMING_SNAKE_CASE		,      env=self.get_env()    )

								lowerCAmelCase     		=		os.path.join(__SCREAMING_SNAKE_CASE		,      '''test_bleu.json'''    )
								lowerCAmelCase     		=		load_json(__SCREAMING_SNAKE_CASE    )
								# print(metrics)
								self.assertGreaterEqual(metrics['''bleu''']		,      25    )



