qq_44174803的博客

下面是两个深度学习模型的融合代码：具体需要哪两个模型进行融合需要自己替换成相应的模型层model1 = Sequential()#input model1.add(Dense(32, input_shape=(NUM_FEAT1,1)))model1.add(Activation("elu"))model1.add(Dropout(0.5))model1.add(Dense(16))model1.add(Activation("elu"))model1.add(Dropout(0.25))

支持time_stamp的设置from math import sqrtfrom numpy import concatenatefrom matplotlib import pyplotfrom pandas import read_csvfrom pandas import DataFramefrom pandas import concatfrom sklearn.preprocessing import MinMaxScalerfrom sklearn.preprocessing i

使用下述代码便能查看从模型最初到当前epoch所花费的训练时间from datetime import datetimeimport tensorflow as tfimport matplotlib.pyplot as plt# 回调——————打印总训练时间（从最初到当前epoch所花费的时间）class timecallback(tf.keras.callbacks.Callback): def __init__(self): self.times = []