'''simple docstring'''
import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


a      =  logging.getLogger(__name__)






@dataclass
class 			__lowercase		(						UpperCAmelCase_						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						field(
         default=0.0			,							metadata={'''help''': '''The label smoothing epsilon to apply (if not zero).'''}						)
     SCREAMING_SNAKE_CASE__		   =						field(default=UpperCAmelCase_			,							metadata={'''help''': '''Whether to SortishSamler or not.'''}						)
     SCREAMING_SNAKE_CASE__		   =						field(
         default=UpperCAmelCase_			,							metadata={'''help''': '''Whether to use generate to calculate generative metrics (ROUGE, BLEU).'''}						)
     SCREAMING_SNAKE_CASE__		   =						field(default=UpperCAmelCase_			,							metadata={'''help''': '''whether to use adafactor'''}						)
     SCREAMING_SNAKE_CASE__		   =						field(
         default=UpperCAmelCase_			,							metadata={'''help''': '''Encoder layer dropout probability. Goes into model.config.'''}						)
     SCREAMING_SNAKE_CASE__		   =						field(
         default=UpperCAmelCase_			,							metadata={'''help''': '''Decoder layer dropout probability. Goes into model.config.'''}						)
     SCREAMING_SNAKE_CASE__		   =						field(default=UpperCAmelCase_			,							metadata={'''help''': '''Dropout probability. Goes into model.config.'''}						)
     SCREAMING_SNAKE_CASE__		   =						field(
         default=UpperCAmelCase_			,							metadata={'''help''': '''Attention dropout probability. Goes into model.config.'''}						)
     SCREAMING_SNAKE_CASE__		   =						field(
         default='''linear'''			,							metadata={'''help''': f'''Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()						)}'''}			,							)




'''simple docstring'''
from urllib.parse import quote

import pytest

from datasets.utils.hub import hf_hub_url







@pytest.mark.parametrize('repo_id'				,     ['canonical_dataset_name', 'org-name/dataset-name']			)
@pytest.mark.parametrize('path'				,     ['filename.csv', 'filename with blanks.csv']			)
@pytest.mark.parametrize('revision'				,     [None, 'v2']			)
def  _UpperCamelCase (     _a	:	Any				,     _a	:	int				,     _a	:	Dict			):




    """simple docstring"""



    __UpperCamelCase	:	List[Any]		    =  hf_hub_url(repo_id=_a				,     path=_a				,     revision=_a			)
    assert url == f"""https://huggingface.co/datasets/{repo_id}/resolve/{revision or 'main'}/{quote(_a			)}"""



