LSTM自动编码器关于Keras尺寸的问题

Question

I am trying to make an autoencoder with Keras. I am having error as follows

ValueError: Error when checking input: expected lstm_1_input to have 3 dimensions, but got array with shape (480, 7)

These are the following data info

df.shape => (480, 7)

timesteps = 15
dim = 7
lH = LossHistory()

model = Sequential()
model.add(LSTM(50, input_shape=(timesteps,dim), return_sequences=True))
model.add(Dense(dim))
model.compile(loss='mae',optimizer = 'adam')

and here is the problem while using fit

model.fit(data,data, epochs=20, batch_size=100, validation_data=(data,data),verbose=0, shuffle=False, callbacks=[lH])

Answer 1

From this link , you can setup an auto-encoder as

inputs = Input(shape=(timesteps, input_dim))
encoded = LSTM(latent_dim)(inputs)

decoded = RepeatVector(timesteps)(encoded)
decoded = LSTM(input_dim, return_sequences=True)(decoded)

sequence_autoencoder = Model(inputs, decoded)
encoder = Model(inputs, encoded)

But you should decide on time steps per sample. For example, if you decide to have 10 steps per each sample, then you can "chop" your whole data with 480 observations into 48 samples each with 10 time steps. Now the input shape would be (48, 10, 7).