learned_embedding_*.pkl files

[brycejoh16]

right now the user has to use the following lines of code in order to run the submodels_module.py scripts. idk if this is how it is suppose to be, or what you were hoping for alex. but might be useful to put these files into predicted_seq_files.zip file.

df=['seq_to_assay_train_1,8,10'] #this is just an example

#import sequence_to_assay model (red box)
#currently use a embedding_fnn_linear model to predict assays 1,8,10.
#will probabaly change when I find the most accurate model
s2a_params=[[1,8,10],'emb_cnn',1]
s2a=mb.seq_to_assay_model(*s2a_params)

#now save the sequence embeddings, file is under /datasets/predicted/learned_embedding_[model properties], col='learned_embedding'
#saves 3 different embeddings from 3 different models
s2a.save_sequence_embeddings(df)