shapeworld.py
generates the shapeworld datasetmodels.py
contains code for the models listed in the paper/models/
contains pretrained models
train.py
file can be used to train the models with the following arguments:--dataset
specifies the dataset to train on (shapeworld
orcolors
)--generalization
specifies the generalization type if training the model to generalize to new colors (new_color
), combinations (new_combo
), or shapes (new_shape
)
--vocab
flag generates a new vocab file--s0
flag trains a literal speaker--l0
flag trains a literal listener--amortized
flag trains an amortized speaker--penalty
specifies the utterance cost function (length
)--lmbd
specifies the cost function parameter
juliaiwhite / amortized-rsa Goto Github PK
View Code? Open in Web Editor NEWLearning to refer informatively by amortizing pragmatic reasoning