Use of log file log in python

A record of the training process

train_metrics = {
    
    "train_loss": 5, "train_acc": 6}
val_metrics = {
    
    "val_loss": 7, "val_acc": 8}

epochs = 10

metriclog = open('metric_2' + '.log', 'w')  # 创建日志文件
metriclog.write("train_loss" + "  " + "train_score" + "  " + "epoch" + "\n")

for epoch in range(1, epochs + 1):
    train_metrics["epoch"] = epoch
    metriclog.write(str(train_metrics["train_loss"])+"  "+str(train_metrics["train_acc"])+"  "+str(train_metrics["epoch"])+'\n')

    metriclog.flush()
metriclog.close()

The result is

train_metrics = {
    
    "train_loss": 5, "train_acc": 6}
val_metrics = {
    
    "val_loss": 7, "val_acc": 8}

epochs = 10
metriclog = open('metric_2' + '.log', 'w')  # 创建日志文件

metriclog.write("train_loss" + "  " + "train_score" + "  " + "val_loss" + "  " + "val_score" + "  " + "epoch" + "\n")

for epoch in range(1, epochs + 1):
    val_metrics["epoch"] = epoch
    metriclog.write(str(train_metrics["train_loss"]) + "  " + str(train_metrics["train_acc"]) + '  ')
    metriclog.write(str(val_metrics["val_loss"]) + "  " + str(val_metrics["val_acc"]) + "  " + str(val_metrics["epoch"]) + '\n')
    metriclog.flush()
metriclog.close()

The advantage of using the log file to record the training process is that opening and viewing the log file during training will not affect the training process and will not interrupt the program.