Common variable name acronym for Pytorch or Tensorflow?
I have seen var name like ninp (num_input), nhid (num_hidden), emsize (embedding size) in pytorch example github repo. What are some of other common acronyms and their meaning/context?

These are common terminologies used in Sequence Models (e.g. RNNs, LSTMs, GRUs etc.,) Here is a description of what those terms mean:

ninp (num_input)  : Dimension of the vectors in the embedding matrix
emsize (embedding size): Dimension of the vectors in the embedding matrix
 nhid (num_hidden): how many "hidden" units that we want to have in each hidden layer  

Pictorial description might help to understand it better. Below is a nice illustration. (Credits: Killian Levacher)



In the above figure emsize, is the embedding size (i.e. dimensionality of the embedding vector). This depends on the model architecture but most people would use something like 300.





In the above figure, we have five neurons in each "hidden" layer. Hence, the nhid value is 5. Output layer would have the dimensionality equal to the vocabulary size, so that a probability distribution is generated over all the tokens in the vocabulary.
