The following diagram illustrates the variety of neural network processing modes:
Rectangles represent tensors, arrows represent functions, red is input, blue is output, and green is the tensor state.
From left to right, we have the following:
- Plain feed-forward network, fixed-size input, and fixed-size output, for example, image classification
- Sequence output, for example, image captioning that takes one image and outputs a set of words identifying items in the image
- Sequence input, for example, sentiment identification (like our IMDb application) where a sentence is classed as being of positive or negative sentiment
- Both sequence input and output, for example, machine translation where an RNN takes an English sentence and translates it into a French output
- Synced sequence both input and output, for example, video classification that is like...
