在 keras 中训练并行模型与顺序

Question

我有以下代码，它使用不同的数据集并行训练相同的模型。我想知道我在这段代码中得到的结果与我使用相应的数据集一一训练模型有什么区别。非常感谢任何帮助。

from keras.layers import *
from keras.models import Model, Sequential
import numpy as np
import random
import test
index=[]
for i in range(10):
    index.append(random.sample(range(0, 201), 10))
x_tr=[]
y_tr=[]
x_te=[]
y_te=[]

aa = test.train_data(index[0])
X_train0, Y_train0, X_Test0, Y_Test0 = test.ddata(aa)
aa = test.train_data(index[1])
X_train1, Y_train1, X_Test1, Y_Test1 = test.ddata(aa)
aa = test.train_data(index[2])
X_train2, Y_train2, X_Test2, Y_Test2 = test.ddata(aa)
aa = test.train_data(index[3])
X_train3, Y_train3, X_Test3, Y_Test3 = test.ddata(aa)
aa = test.train_data(index[4])
X_train4, Y_train4, X_Test4, Y_Test4 = test.ddata(aa)
aa = test.train_data(index[5])
X_train5, Y_train5, X_Test5, Y_Test5 = test.ddata(aa)
aa = test.train_data(index[6])
X_train6, Y_train6, X_Test6,Y_Test6 = test.ddata(aa)
aa = test.train_data(index[7])
X_train7, Y_train7, X_Test7, Y_Test7 = test.ddata(aa)
aa = test.train_data(index[8])
X_train8, Y_train8, X_Test8, Y_Test8 = test.ddata(aa)
aa = test.train_data(index[9])
X_train9, Y_train9, X_Test9, Y_Test9 = test.ddata(aa)


m=test.get_model()
inp0=Input((5,10,10,1))
inp1=Input((5,10,10,1))
inp2=Input((5,10,10,1))
inp3=Input((5,10,10,1))
inp4=Input((5,10,10,1))
inp5=Input((5,10,10,1))
inp6=Input((5,10,10,1))
inp7=Input((5,10,10,1))
inp8=Input((5,10,10,1))
inp9=Input((5,10,10,1))
out0=m(inp0)
out1=m(inp1)
out2=m(inp2)
out3=m(inp3)
out4=m(inp4)
out5=m(inp5)
out6=m(inp6)
out7=m(inp7)
out8=m(inp8)
out9=m(inp9)





model = Model([inp0,inp1,inp2,inp3,inp4,inp5,inp6,inp7,inp8,inp9],[out0,out1,out2,out3,out4,out5,out6,out7,out8,out9])
model.compile(optimizer='adam', loss='mse')
model.fit([X_train0,X_train1,X_train2,X_train3,X_train4,X_train5,X_train6,X_train7,X_train8,X_train9],[Y_train0,Y_train1,Y_train2,Y_train3,Y_train4,Y_train5,Y_train6,Y_train7,Y_train8,Y_train9], epochs = 50)
ypred0,ypred1,ypred2,ypred3,ypred4,ypred5,ypred6,ypred7,ypred8,ypred9 = model.predict([X_Test0,X_Test1,X_Test2,X_Test3,X_Test4,X_Test5,X_Test6,X_Test7,X_Test8,X_Test9])
print(ypred0.shape)

FYI-test 是我从中获取数据的另一个地方。

Answer 1

最好并行训练或一次全部训练而不是顺序训练。

如果您按顺序训练它，最终可能会过度拟合您训练模型的最后一个数据集。