From 41737bbbae736530b348b63a2bff58e3f814a5bb Mon Sep 17 00:00:00 2001 From: Wen-Chao Hu Date: Fri, 31 Mar 2023 21:38:40 +0800 Subject: [PATCH] [FIX] No longer use example.py --- examples/example.py | 77 --------------------------------------------- 1 file changed, 77 deletions(-) delete mode 100644 examples/example.py diff --git a/examples/example.py b/examples/example.py deleted file mode 100644 index 897490f..0000000 --- a/examples/example.py +++ /dev/null @@ -1,77 +0,0 @@ -# coding: utf-8 -# ================================================================# -# Copyright (C) 2021 Freecss All rights reserved. -# -# File Name ：share_example.py -# Author ：freecss -# Email ：karlfreecss@gmail.com -# Created Date ：2021/06/07 -# Description ： -# -# ================================================================# - -import sys -sys.path.append("../") - -from abl.utils.plog import logger, INFO -import torch.nn as nn -import torch - -from abl.models.nn import LeNet5, SymbolNet -from abl.models.basic_model import BasicModel, BasicDataset -from abl.models.wabl_models import DecisionTree, WABLBasicModel - -from multiprocessing import Pool -from abl.abducer.abducer_base import AbducerBase, HED_Abducer -from abl.abducer.kb import add_KB, HWF_KB, prolog_KB, HED_prolog_KB -from datasets.mnist_add.get_mnist_add import get_mnist_add -from datasets.hwf.get_hwf import get_hwf -from datasets.hed.get_hed import get_hed, split_equation -from abl import framework_hed - - -def run_test(): - - # kb = add_KB() - kb = HWF_KB(GKB_flag=True) - abducer = AbducerBase(kb, 'confidence') - - # kb = HED_prolog_KB(pseudo_label_list=[1, 0, '+', '='], pl_file='../examples/datasets/hed/learn_add.pl') - # abducer = HED_Abducer(kb) - - recorder = logger() - - # total_train_data = get_hed(train=True) - # train_data, val_data = split_equation(total_train_data, 3, 1) - # test_data = get_hed(train=False) - - # train_data = get_mnist_add(train=True, get_pseudo_label=True) - # test_data = get_mnist_add(train=False, get_pseudo_label=True) - - train_data = get_hwf(train=True, get_pseudo_label=True) - test_data = get_hwf(train=False, get_pseudo_label=True) - - # cls = LeNet5(num_classes=len(kb.pseudo_label_list), image_size=(train_data[0][0][0].shape[1:])) - cls = SymbolNet(num_classes=len(kb.pseudo_label_list), image_size=(train_data[0][0][0].shape[1:])) - device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") - - # framework_hed.hed_pretrain(kb, cls, recorder) - - criterion = nn.CrossEntropyLoss() - optimizer = torch.optim.RMSprop(cls.parameters(), lr=0.001, weight_decay=1e-6) - # optimizer = torch.optim.Adam(cls.parameters(), lr=0.001, betas=(0.9, 0.99)) - - base_model = BasicModel(cls, criterion, optimizer, device, save_interval=1, save_dir=recorder.save_dir, batch_size=32, num_epochs=1, recorder=recorder) - model = WABLBasicModel(base_model, kb.pseudo_label_list) - - # model, mapping = framework_hed.train_with_rule(model, abducer, train_data, val_data, select_num=10, min_len=5, max_len=8) - # framework_hed.hed_test(model, abducer, mapping, train_data, test_data, min_len=5, max_len=8) - - framework_hed.train(model, abducer, train_data, test_data, sample_num=-1, verbose=1) - - recorder.dump() - return True - - -if __name__ == "__main__": - run_test() \ No newline at end of file