Keras loaded model output is different from the training model output
When I train my model it has a two-dimension output - it is (none, 1) - corresponding to the time series I'm trying to predict. But whenever I load the saved model in order to make predictions, it has a three-dimensional output - (none, 40, 1) - where 40 corresponds to the n_steps required to fit the conv1D network. What is wrong?
Here is the code:
df = np.load('Principal.npy')
# Conv1D
#model = load_model('ModeloConv1D.h5')
model = autoencoder_conv1D((2, 20, 17), n_steps=40)
model.load_weights('weights_35067.hdf5')
# summarize model.
model.summary()
# load dataset
df = df
# split into input (X) and output (Y) variables
X = f.separar_interface(df, n_steps=40)
# THE X INPUT SHAPE (59891, 17) length and attributes, respectively ##
# conv1D input format
X = X.reshape(X.shape[0], 2, 20, X.shape[2])
# Make predictions
test_predictions = model.predict(X)
## test_predictions.shape = (59891, 40, 1)
test_predictions = model.predict(X).flatten()
##test_predictions.shape = (2395640, 1)
plt.figure(3)
plt.plot(test_predictions)
plt.legend('Prediction')
plt.show()
In the plot below you can see that it is plotting the input format.
Here is the network architecture:
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
time_distributed_70 (TimeDis (None, 1, 31, 24) 4104
_________________________________________________________________
time_distributed_71 (TimeDis (None, 1, 4, 24) 0
_________________________________________________________________
time_distributed_72 (TimeDis (None, 1, 4, 48) 9264
_________________________________________________________________
time_distributed_73 (TimeDis (None, 1, 1, 48) 0
_________________________________________________________________
time_distributed_74 (TimeDis (None, 1, 1, 64) 12352
_________________________________________________________________
time_distributed_75 (TimeDis (None, 1, 1, 64) 0
_________________________________________________________________
time_distributed_76 (TimeDis (None, 1, 64) 0
_________________________________________________________________
lstm_17 (LSTM) (None, 100) 66000
_________________________________________________________________
repeat_vector_9 (RepeatVecto (None, 40, 100) 0
_________________________________________________________________
lstm_18 (LSTM) (None, 40, 100) 80400
_________________________________________________________________
time_distributed_77 (TimeDis (None, 40, 1024) 103424
_________________________________________________________________
dropout_9 (Dropout) (None, 40, 1024) 0
_________________________________________________________________
dense_18 (Dense) (None, 40, 1) 1025
=================================================================
Topic multi-output reshape keras neural-network
Category Data Science