--- a
+++ b/config.py
@@ -0,0 +1,51 @@
+# -*- coding: utf-8 -*-
+'''
+@time: 2019/9/8 18:45
+
+@ author: javis
+'''
+import os
+
+
+class Config:
+    # for data_process.py
+    #root = r'D:\ECG'
+    root = r'data'
+    train_dir = os.path.join(root, 'hf_round1_train/train')
+    test_dir = os.path.join(root, 'hf_round1_testA/testA')
+    train_label = os.path.join(root, 'hf_round1_label.txt')
+    test_label = os.path.join(root, 'hf_round1_subA.txt')
+    arrythmia = os.path.join(root, 'hf_round1_arrythmia.txt')
+    train_data = os.path.join(root, 'train.pth')
+
+    # for train
+    #训练的模型名称
+    model_name = 'resnet34'
+    #在第几个epoch进行到下一个state,调整lr
+    stage_epoch = [32,64,128]
+    #训练时的batch大小
+    batch_size = 64
+    #label的类别数
+    num_classes = 55
+    #最大训练多少个epoch
+    max_epoch = 256
+    #目标的采样长度
+    target_point_num = 2048
+    #保存模型的文件夹
+    ckpt = 'ckpt'
+    #保存提交文件的文件夹
+    sub_dir = 'submit'
+    #初始的学习率
+    lr = 1e-3
+    #保存模型当前epoch的权重
+    current_w = 'current_w.pth'
+    #保存最佳的权重
+    best_w = 'best_w.pth'
+    # 学习率衰减 lr/=lr_decay
+    lr_decay = 10
+
+    #for test
+    temp_dir=os.path.join(root,'temp')
+
+
+config = Config()