From 7a4d041dc24b4bba0ea5d55c90bff7c193b836fa Mon Sep 17 00:00:00 2001 From: 17427 <1742785947@qq.com> Date: Wed, 18 Oct 2023 21:03:17 +0800 Subject: [PATCH] cws --- 杭州日电量/industry_elec_cws.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/杭州日电量/industry_elec_cws.py b/杭州日电量/industry_elec_cws.py index 1a106da..5d63c12 100644 --- a/杭州日电量/industry_elec_cws.py +++ b/杭州日电量/industry_elec_cws.py @@ -58,6 +58,7 @@ def to_data(file_dir, excel): df = (df - min_value) / (max_value - min_value) dataset_x, dataset_y = create_dataset(df, DAYS_FOR_TRAIN) + print() print('len(dataset_x:)', len(dataset_x)) # 划分训练集和测试集 @@ -91,7 +92,7 @@ def to_data(file_dir, excel): train_loss.append(loss.item()) b = time.time() - print(excel,industry,'训练用时',b-a) + print(excel, industry, '训练用时', b - a) # 保存模型 # torch.save(model.state_dict(),save_filename) @@ -121,7 +122,7 @@ def to_data(file_dir, excel): result_eight = pd.DataFrame({'pred_test': pred_test[-31:], 'real': df[-31:]}) target = (result_eight['pred_test'][-3:].sum() - result_eight['real'][-3:].sum()) / result_eight[ 'real'].sum() - print(target) + # print(target) with open(fr'.\cws_to_data\{excel[:2]}.txt', 'a', encoding='utf-8') as f: tmp_data = {'city': excel[:2], 'industry': industry, "month_deviation_rate": round(target, 5)} f.write(str(tmp_data) + "\n")