deeplearning.py 文件源码

def model_Train(X_tr, Y_tr, arch, actfn='sigmoid', last_act='sigmoid', reg_coeff=0.0,
                num_epoch=100, batch_size=1000, sgd_lr=1e-5, sgd_decay=0.0, sgd_mom=0.0,
                    sgd_Nesterov=False, EStop=False):
    call_ES = EarlyStopping(monitor='val_acc', patience=6, mode='auto')
    model = gen_Model(num_units=arch, actfn=actfn, reg_coeff=reg_coeff, last_act=last_act)
    sgd = SGD(lr=0.05, decay=1e-6, momentum=0.9, nesterov=True)
    model.compile(loss='categorical_crossentropy', optimizer=sgd, metrics=['accuracy'])

    if EStop:
        model.fit(X_tr, Y_tr, nb_epoch=num_epoch, batch_size=batch_size, callbacks=[call_ES],
                   validation_split=0.1, validation_data=None, shuffle=True)
    else:
        model.fit(X_tr, Y_tr, batch_size=100, nb_epoch=10, shuffle=True, verbose=1,show_accuracy=True,validation_split=0.2)
    return model