Reputation: 41
Following is the code to create model. Model has 2 input layers, 1 embedding, LSTM, attention, and dense layer. I am getting an error (image attached) when I am trying to execute model.fit with multiple inputs.
Not sure why? Please explain.
MAX_SEQUENCE_LENGTH = 20
# First input layer
sequence_ip = Input(shape=(MAX_SEQUENCE_LENGTH,), dtype='int32')
# Second input layer
time_Decay_ip = Input(shape=(MAX_SEQUENCE_LENGTH,), dtype='float32')
# Adding embedding layer
embedding_layer = Embedding(vocab_length, output_dim = 32, input_length=seq_length, trainable=True)
embedded_sequences = embedding_layer(sequence_ip)
l_gru = LSTM(100, return_sequences=True)(embedded_sequences)
l_att = attention()([l_gru, time_Decay_ip])
preds = Dense(1, activation='softmax', trainable = True)(l_att)
model = Model([sequence_ip, time_Decay_ip], preds)
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['acc'])
model.summary()
model.fit(x = [np.array(X_train), np.array(time_decay_tr)], y = np.array(Y_train), validation_data=(X_test, Y_test), nb_epoch=10, batch_size=9)
Upvotes: 0
Views: 327
Reputation: 693
I had this error when using keras, there are multiple ways to fix this:
You can either uninstall and reinstall the data you are using, Or you can uninstall and reinstall tensorflow.
You also need to check if your GPU is running trying to run CUDA (fron NVIDIA cards) if it is and you dont have a NVIDIA GPU use the CPU
Upvotes: 2