load_weights
仅设置网络的权重。您仍然需要在调用之前定义其体系结构
load_weights
：
def create_model(): model = Sequential() model.add(Dense(64, input_dim=14, init='uniform')) model.add(LeakyReLU(alpha=0.3)) model.add(BatchNormalization(epsilon=1e-06, mode=0, momentum=0.9, weights=None)) model.add(Dropout(0.5)) model.add(Dense(64, init='uniform')) model.add(LeakyReLU(alpha=0.3)) model.add(BatchNormalization(epsilon=1e-06, mode=0, momentum=0.9, weights=None)) model.add(Dropout(0.5)) model.add(Dense(2, init='uniform')) model.add(Activation('softmax')) return modeldef train(): model = create_model() sgd = SGD(lr=0.1, decay=1e-6, momentum=0.9, nesterov=True) model.compile(loss='binary_crossentropy', optimizer=sgd) checkpointer = ModelCheckpoint(filepath="/tmp/weights.hdf5", verbose=1, save_best_only=True) model.fit(X_train, y_train, nb_epoch=20, batch_size=16, show_accuracy=True, validation_split=0.2, verbose=2, callbacks=[checkpointer])def load_trained_model(weights_path): model = create_model() model.load_weights(weights_path)
