# Examples of "one to many" for RNN/LSTM

Are there any examples dealing with "one to many" kind of LSTM?

Basically I am trying to build a model which takes an input vector $$a$$ and gives an output of $$[b_1; b_2 ;b_3; b_4, \ldots; b_n]$$ where $$b_i$$ is a vector. The vectors $$a$$ and $$b_1, b_2, b_3$$ ... etc have different sizes.

I can't seem to find any examples in literature to begin understanding how to format the input and output, or even how to work around training and testing part. Can RNN even deal with different input and output size in the first place?

Another doubt I have is that lot of blogs on RNN state that they are difficult to train due to their complexity. Why is it so?

• – Tim
Apr 25, 2019 at 7:54
• Thanks! The link shows that a chain model is difficult to implement in Keras. Are there any examples/papers where one-to-many has been used practically? Apr 25, 2019 at 8:09