I am slowly but surely making my way through learning about Neural Networks with Axon, but I did have this question. For some reason, my predicted values have the same shape as my input tensor (which is 60 x 60 x 1) and I am not sure the reason why. I expected the predicted values to have the shape (60, ), (as in, a single vector with 60 elements), but that is not the case for some reason.

In case you need it, here is my model:

input = Axon.input("input", shape: {prediction_days, 1})

model =
  input
  |> Axon.lstm(50)
  |> then(fn {seq, _} -> seq end)
  |> Axon.dropout(rate: 0.2)
  |> Axon.lstm(50)
  |> then(fn {seq, _} -> seq end)
  |> Axon.dropout(rate: 0.2)
  |> Axon.lstm(50)
  |> then(fn {seq, _} -> seq end)
  |> Axon.dropout(rate: 0.2)
  |> Axon.dense(1, activation: :sigmoid)

And here is my prediction code:

params =
  model
  |> Axon.Loop.trainer(:mean_squared_error, :adam)
  |> Axon.Loop.metric(:mean_absolute_error, "MAE")
  |> Axon.Loop.run(Stream.zip(batched_x_train, batched_y_train), %{}, epochs: 25, compiler: EXLA)

y_pred = Axon.predict(model, params, x_test)

What am I missing here? Thanks!