


"""simple docstring"""


# 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 snake_case   (	_UpperCamelCase):







		@classmethod
		def 			a_			(       cls   :							Union[str, Any]		)							->    Dict:





						'''simple docstring'''







						return cls







		@slow
		@require_torch_gpu
		def 			a_			(       self   :							int		)							->    List[str]:





						'''simple docstring'''







						_A       	=      self.get_auto_remove_tmp_dir()
						_A       	=      F"""
            --model_name Helsinki-NLP/opus-mt-en-ro
            --save_dir {output_dir}
            --data_dir {self.test_file_dir_str}/test_data/wmt_en_ro
            --num_beams 2
            --task translation
        """.split()

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

						_A       	=      os.path.join(a__     , "test_bleu.json"		)
						_A       	=      load_json(a__		)
						# print(metrics)
						self.assertGreaterEqual(metrics["bleu"]     , 25		)



"""simple docstring"""


import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from unittest.mock import Mock, patch

import diffusers.utils.hub_utils
class snake_case   (	unittest.TestCase):







		@patch("diffusers.utils.hub_utils.get_full_repo_name"		)
		def 			a_			(       self   :							Any     , a__   :							Mock		)							->    None:





						'''simple docstring'''







						_A       	=      "full_repo_name"
						with TemporaryDirectory() as tmpdir:
										# Dummy args values
										_A       	=      Mock()
										_A       	=      tmpdir
										_A       	=      0
										_A       	=      "hub_token"
										_A       	=      "dataset_name"
										_A       	=      0.0_1
										_A       	=      10_00_00
										_A       	=      1_00_00
										_A       	=      0.0_1
										_A       	=      0.0_2
										_A       	=      0.0_3
										_A       	=      0.0_0_0_5
										_A       	=      0.0_0_0_0_0_1
										_A       	=      1
										_A       	=      10
										_A       	=      0.0_0_1
										_A       	=      0.1
										_A       	=      0.2
										_A       	=      True

										# Model card mush be rendered and saved
										diffusers.utils.hub_utils.create_model_card(a__     , model_name="model_name"		)
										self.assertTrue((Path(a__		) / "README.md").is_file()		)