How to use test_l1 method in avocado

Best Python code snippet using avocado_python

fasttext_classify.py

Source:fasttext_classify.py

1# -*- coding: utf-8 -*-2"""3å¤çåå§æ°æ®ï¼çæè®ç»æ°æ®é4@author: bruce5"""6import os,re7import time8import fastText.FastText as ff9from read_write_tool import read_file10 11#è®ç»åç±»æ¨¡å12def fastText_classifier(train_data,test_data,model_save_path,result_save_path):13    files = []14    results = []15    if not os.path.exists(train_data):16        os.makedirs(train_data)17    if not os.path.exists(model_save_path):18        os.makedirs(model_save_path)19    if not os.path.exists(result_save_path):20        os.makedirs(result_save_path)2122    for level_one,test_l1 in zip(os.listdir(train_data),os.listdir(test_data)):23        print(level_one+'-->'+test_l1)2425        if '.txt' in level_one and '.txt' in test_l1:26            classifier=ff.train_supervised(train_data+level_one,ãlr=0.1,loss='hs',wordNgrams=2,epoch=100)27            #classifier = load_model.load_model(model_save_path+'train_level_1_classifier.model','nt')28            model = classifier.save_model(model_save_path+level_one+'_classifier.model') # ä¿åæ¨¡å29            classifier.get_labels() # è¾åºæ ç¾30            result = classifier.test(test_data+test_l1)31            files.append(level_one)32            results.append(result)33            print(result)34        else:35            data_list = os.listdir(train_data+level_one+'/')36            test_list = os.listdir(test_data+test_l1+'/')37            if not len(data_list) or not len(test_data):38                continue39            classifier=ff.train_supervised(train_data+level_one+'/'+data_list[0],lr=0.1,loss='hs',wordNgrams=2,epoch=50)40            #classifier = load_model.load_model(model_save_path+'train_level_1_classifier.model','nt')41            model = classifier.save_model(model_save_path+level_one+'_classifier.model') # ä¿åæ¨¡å42            classifier.get_labels() # è¾åºæ ç¾43            result = classifier.test(test_data+test_l1+'/'+test_list[0])44            files.append(data_list[0])45            results.append(result)46            print(result)47    print(files)48    print(results)4950    with open(result_save_path+'train_results.txt','w') as fp:51        for i,j in zip(files,results):52            fp.write(str(i)+'-->'+str(j))53            fp.write('\n')54    '''55    #linuxç³»ç»56    classifier=fasttext.supervised(train_data+'level_3_train.txt',lr=0.1,loss='hs',wordNgrams=2,epoch=100,lable_prefix='__lable__')57    model = classifier.save_model(model_save_path+'fastText_classifier.model') # ä¿åæ¨¡å58    classifier.get_labels() # è¾åºæ ç¾59    result = classifier.test(train_data+'level_3_train.txt')60    print(result) 61    # print("P@1:",result.precision)    #åç¡®ç62    # print("R@2:",result.recall)    #å¬åç63    # print("Number of examples:",result.nexamples)    #é¢æµéçä¾å64    '''65if __name__ == '__main__':66    train_path = '../datas/data_set/train/'67    test_path = '../datas/data_set/test/'68    model_save_path = '../datas/model/paper_train/'69    result_save_path = '../datas/results/paper_train/'
...

test_multipler.py

Source:test_multipler.py

1import pytest2from sandpit_package.mathers.multiplier import Multiplier3expected_op = "*"4test_l1 = 55test_r1 = 76expected_result1 = test_l1 * test_r17expected_msg1 = "%s %s %s = %s" % (test_l1, expected_op, test_r1, expected_result1)8test_l2 = "abc"9test_r2 = 510expected_result2 = test_l2 * test_r211expected_msg2 = "%s %s %s = %s" % (test_l2, expected_op, test_r2, expected_result2)12def test_init():13    with pytest.raises(Exception):14        x1 = Multiplier()15    with pytest.raises(Exception):16        x2 = Multiplier(test_l1)17    x3 = Multiplier(test_l1, test_r1)18    assert (x3.l, x3.r) == (test_l1, test_r1)19    x4 = Multiplier(test_l2, test_r2)20    assert (x4.l, x4.r) == (test_l2, test_r2)21def test_op_str():22    x = Multiplier(test_l1, test_r1)23    assert x._op_str() == expected_op24def test_result():25    x1 = Multiplier(test_l1, test_r1)26    assert x1.result() == expected_result127    x1 = Multiplier(test_r1, test_l1)28    assert x1.result() == expected_result129    x2 = Multiplier(test_l2, test_r2)30    assert x2.result() == expected_result231    x2 = Multiplier(test_r2, test_l2)32    assert x2.result() == expected_result233def test_msg():34    x1 = Multiplier(test_l1, test_r1)35    assert x1._msg() == expected_msg136    x2 = Multiplier(test_l2, test_r2)37    assert x2._msg() == expected_msg238def test_print(capsys):39    x1 = Multiplier(test_l1, test_r1)40    x1.print()...

test_adder.py

Source:test_adder.py

1import pytest2from sandpit_package.mathers.adder import Adder3expected_op = "+"4test_l1 = 55test_r1 = 76expected_result1 = test_l1 + test_r17expected_msg1 = "%s %s %s = %s" % (test_l1, expected_op, test_r1, expected_result1)8test_l2 = "abc"9test_r2 = "def"10expected_result2 = test_l2 + test_r211expected_msg2 = "%s %s %s = %s" % (test_l2, expected_op, test_r2, expected_result2)12def test_init():13    with pytest.raises(Exception):14        x1 = Adder()15    with pytest.raises(Exception):16        x2 = Adder(test_l1)17    x3 = Adder(test_l1, test_r1)18    assert (x3.l, x3.r) == (test_l1, test_r1)19    x4 = Adder(test_l2, test_r2)20    assert (x4.l, x4.r) == (test_l2, test_r2)21def test_op_str():22    x = Adder(test_l1, test_r1)23    assert x._op_str() == expected_op24def test_result():25    x1 = Adder(test_l1, test_r1)26    assert x1.result() == expected_result127    x1 = Adder(test_r1, test_l1)28    assert x1.result() == expected_result129    x2 = Adder(test_l2, test_r2)30    assert x2.result() == expected_result231    x2 = Adder(test_r2, test_l2)32    assert x2.result() != expected_result233def test_msg():34    x1 = Adder(test_l1, test_r1)35    assert x1._msg() == expected_msg136    x2 = Adder(test_l2, test_r2)37    assert x2._msg() == expected_msg238def test_print(capsys):39    x1 = Adder(test_l1, test_r1)40    x1.print()...

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