Add a target_width parameter to keras.utils.timeseries_dataset_from_array about tf-keras HOT 4 OPEN

@To3No7,
Thank you for the issue. Could you please provide any specific Use-case for the above feature which might help us to analyse the issue. Thank you!

from tf-keras.

As part of a course I am teaching in deep learning one part is time series forecasting with RNNs. We work with the Jena weather data, following in part the Tensorflow example https://www.tensorflow.org/tutorials/structured_data/time_series.

Part of this exercise is to:

• Make two different models that should both predict what the temperature will be 24 hours ahead based on the last 24 hours' readings. That is, if your input sequence e.g. runs from hour 1 through hour 24, then you should predict what the temperature is at hour 48. Do this using these two methods:
  • Part 2.1. Direct prediction of the value you are looking for (single-step with a new target time-step). That is, use 24 hours of input values to predict only one output value. 24 hours ahead (hour 48).
  • Part 2.2. Make a prediction of all intermediate values as well. That is, again use 24 hours of input values, but predict all values from hour 25 through hour 48. Your output will now be a 24-value long vector at each prediction (Single shot prediction).
• Note that for these two models we are only interested in the quality of the prediction at hour 48, so you need to find a way to measure the performance for this particular hour in order to compare the models against model 2.1 and among themselves.
  Compare these two models and analyze the difference in results, e.g. which gives the best prediction?

Thus to do the Part 2.2 the students need to have target_width of 24 instead of 1.

Some year back I have been suggesting the students should use the windowing function from the tensorflow tutorial, but this spring I suggested they use the keras function timeseries_dataset_from_array instead as that would be a more clean solution. However, as timeseries_dataset_from_array didn’t have a target_width, almost no student was able to implement a correct datasetgen for Part 2.2 and I had to quickly hack together a solution for them to use (as seen above).

Is this clear enough?

I might be able to provide solution code, but this have to be done privately for obvious reasons.

from tf-keras.

@sachinprasadhs @qlzh727 @tilakrayal I'll pick this one up

from tf-keras.