






from __future__ import annotations

from enum import Enum







class     UpperCAmelCase_		(      lowercase				):



      """simple docstring"""
      UpperCamelCase_       :      Union[str, Any]     =24
      UpperCamelCase_       :      Union[str, Any]     =21
      UpperCamelCase_       :      int     =18
      UpperCamelCase_       :      int     =15
      UpperCamelCase_       :      Dict     =12
      UpperCamelCase_       :      Dict     =9
      UpperCamelCase_       :      str     =6
      UpperCamelCase_       :      str     =3
      UpperCamelCase_       :      int     =2
      UpperCamelCase_       :      Optional[int]     =1
      UpperCamelCase_       :      List[Any]     =-1
      UpperCamelCase_       :      int     =-2
      UpperCamelCase_       :      Tuple     =-3
      UpperCamelCase_       :      int     =-6
      UpperCamelCase_       :      str     =-9
      UpperCamelCase_       :      Any     =-12
      UpperCamelCase_       :      Dict     =-15
      UpperCamelCase_       :      Union[str, Any]     =-18
      UpperCamelCase_       :      Tuple     =-21
      UpperCamelCase_       :      Union[str, Any]     =-24







class     UpperCAmelCase_		(      lowercase				):



      """simple docstring"""
      UpperCamelCase_       :      Tuple     =8
      UpperCamelCase_       :      Tuple     =7
      UpperCamelCase_       :      Optional[Any]     =6
      UpperCamelCase_       :      List[Any]     =5
      UpperCamelCase_       :      Dict     =4
      UpperCamelCase_       :      Dict     =3
      UpperCamelCase_       :      Optional[int]     =2
      UpperCamelCase_       :      Optional[Any]     =1







def 						_A     (       SCREAMING_SNAKE_CASE__						:			float  ,						SCREAMING_SNAKE_CASE__						:			str | SIUnit  ,						SCREAMING_SNAKE_CASE__						:			str | SIUnit  ,						):
    if isinstance(SCREAMING_SNAKE_CASE__  ,						SCREAMING_SNAKE_CASE__ ):
        UpperCamelCase :Union[str, Any]										=     SIUnit[known_prefix.lower()]
    if isinstance(SCREAMING_SNAKE_CASE__  ,						SCREAMING_SNAKE_CASE__ ):
        UpperCamelCase :Optional[Any]										=     SIUnit[unknown_prefix.lower()]
    UpperCamelCase :float										=     known_amount * (
        10 ** (known_prefix.value - unknown_prefix.value)
    )
    return unknown_amount


def 						_A     (       SCREAMING_SNAKE_CASE__						:			float  ,						SCREAMING_SNAKE_CASE__						:			str | BinaryUnit  ,						SCREAMING_SNAKE_CASE__						:			str | BinaryUnit  ,						):
    if isinstance(SCREAMING_SNAKE_CASE__  ,						SCREAMING_SNAKE_CASE__ ):
        UpperCamelCase :Tuple										=     BinaryUnit[known_prefix.lower()]
    if isinstance(SCREAMING_SNAKE_CASE__  ,						SCREAMING_SNAKE_CASE__ ):
        UpperCamelCase :Optional[Any]										=     BinaryUnit[unknown_prefix.lower()]
    UpperCamelCase :float										=     known_amount * (
        2 ** ((known_prefix.value - unknown_prefix.value) * 10)
    )
    return unknown_amount


if __name__ == "__main__":
 import doctest

 doctest.testmod()













# 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     UpperCAmelCase_		(      lowercase				):



      """simple docstring"""
      @classmethod
      def 					UpperCAmelCase		(       cls				)       ->   List[Any]:
          return cls




      @slow
      @require_torch_gpu
      def 					UpperCAmelCase		(       self				)       ->   int:
          UpperCamelCase :int										=     self.get_auto_remove_tmp_dir()
          UpperCamelCase :List[str]										=     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
          UpperCamelCase :List[str]										=     get_gpu_count()
          UpperCamelCase :Optional[Any]										=     F'''
            -m torch.distributed.launch
            --nproc_per_node={n_gpu}
            {self.test_file_dir}/run_distributed_eval.py
        '''.split()
          UpperCamelCase :List[Any]										=     [sys.executable] + distributed_args + args
          execute_subprocess_async(SCREAMING_SNAKE_CASE_					,       env=self.get_env()				)

          UpperCamelCase :Tuple										=     os.path.join(SCREAMING_SNAKE_CASE_					,       '''test_bleu.json'''				)
          UpperCamelCase :str										=     load_json(SCREAMING_SNAKE_CASE_				)
          # print(metrics)
          self.assertGreaterEqual(metrics['''bleu''']					,       25				)





