

import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_with_pabee

from transformers.testing_utils import TestCasePlus


logging.basicConfig(level=logging.DEBUG)

A_						:     int			  =				logging.getLogger()


def  __a    (				) ->       Dict:






    '''simple docstring'''
    __UpperCAmelCase			   =     argparse.ArgumentParser()
    parser.add_argument('''-f''' )
    __UpperCAmelCase			   =     parser.parse_args()
    return args.f
class    A_				( _a  ):


    '''simple docstring'''






    def        lowerCAmelCase_  (self					)       -> Dict:
        __UpperCAmelCase			   =     logging.StreamHandler(sys.stdout					)
        logger.addHandler(lowercase__					)

        __UpperCAmelCase			   =     self.get_auto_remove_tmp_dir()
        __UpperCAmelCase			   =     F'''
            run_glue_with_pabee.py
            --model_type albert
            --model_name_or_path albert-base-v2
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --task_name mrpc
            --do_train
            --do_eval
            --per_gpu_train_batch_size=2
            --per_gpu_eval_batch_size=1
            --learning_rate=2e-5
            --max_steps=50
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            '''.split()

        with patch.object(lowercase__       , '''argv'''       , lowercase__					):
            __UpperCAmelCase			   =     run_glue_with_pabee.main()
            for value in result.values():
                self.assertGreaterEqual(lowercase__       , 0.75					)







# this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus

# 1. pip install sentencepiece
#
# 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt

# 3. build
import sentencepiece as spm

# pegasus:
# 1. no bos
# 2. eos_id is 1
# 3. unk_id is 2
# build a sample spm file accordingly
spm.SentencePieceTrainer.train(
    '--input=botchan.txt --model_prefix=test_sentencepiece_no_bos --bos_id=-1 --unk_id=2  --eos_id=1  --vocab_size=1000'
)

# 4. now update the fixture
# mv test_sentencepiece_no_bos.model ../../tests/fixtures/




