使用Keras Functional API的多个输入 [英] Multiple inputs with Keras Functional API

问题描述

Keras似乎缺少有关功能API的文档，但我可能会弄错一切.

It seems that Keras lacks documentation regarding functional API but I might be getting it all wrong.

我有多个独立的输入，并且我想预测每个输入的输出.到目前为止，这是我的代码:

I have multiple independent inputs and I want to predict an output for each input. Here's my code so far:

 hour = Input(shape=(1,1), name='hour')
 hour_output = LSTM(1, name='hour_output')(hour)

 port = Input(shape=(1,1), name='port')
 port_output = LSTM(1, name='port_output')(port)

 model = Model(inputs=[hour, port], outputs = [hour_output, port_output])

 model.compile(loss="mean_squared_error", optimizer="adam", metrics=['accuracy'])
 model.fit(trainX, trainY, epochs=10 batch_size=1, verbose=2, shuffle=False)

我为此遇到的错误:

ValueError:没有为"hour_output"提供数据.需要每个键中的数据:['hour_output'，'port_output']

ValueError: No data provided for "hour_output". Need data for each key in: ['hour_output', 'port_output']

我也很难获得正确的输入，因此我最终使用了示例结构为{'hour': array([[[0]], [[1]], [[3]]]) }的字典.我也不喜欢(使用字典).

I also had a hard time getting the right input for this, so I ended up using dictionary with example structure:{'hour': array([[[0]], [[1]], [[3]]]) }. I don't like that (using dict) either.

请注意，我有更多输入要使用，这很有意义，但是现在我只是在尝试使模型正常工作.

Note that I have more inputs to use and for this to make sense, but now I am just trying to make the model work.

推荐答案

在您的model.fit中，您需要提供一个长度为2的输入列表，因为您在模型中定义了两个输入.

In your model.fit you need to provide a list of inputs with length = 2, since you define two inputs in your Model.

在train_hour和train_port中拆分您的训练数据，然后像这样调用fit:

Split your training data in train_hour and train_port and call fit like:

model.fit([train_X_hour, train_X_port], [train_Y_hour, train_Y_port] epochs=10, batch_size=1, verbose=2, shuffle=False)

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