Skip to content
No description, website, or topics provided.
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
.gitattributes
README.md
helpers.py
model.py
model_utils.py
train.py
train_model.sh

README.md

NAOMI

Code for paper titled NAOMI: Non-Autoregressive Multiresolution Sequence Imputation

Code is written with PyTorch v0.4.1 (Python 3.6.5). Download the data from here and put into data/ folder.

To train the model:

First open visdom, then adjust hyperparameters in train_model.sh and run the shell file.

Detailed explanations of hyperparameters:

--model: “NAOMI” or “SingleRes”

--task: “basketball” or “billiard”

--y_dim: 10 for basketball and 2 for billiard

--rnn_dim and --n_layers: gru cell size for all models, including forward and backward rnns

--dec1_dim to --dec16_dim: For NAOMI, these values correspond to dimensions of different decoders. For SingleRes, only dec1_dim is used for decoder.

--pre_start_lr: initial learning rate for supervised pretrain

--pretrain: supervised pretrain epochs

--highest: largest stepsize for NAOMI decoders, should be 2^n

--discrim_rnn_dim and --discrim_layers: discriminator rnn size

--policy_learning_rate: learning rate for generator in adversarial training

--discrim_learning_rate: learning rate for discriminator in adversarial training

--pretrain_disc_iter: number of iterations to pretrain discriminator

--max_iter_num: number of adversarial training iterations

You can’t perform that action at this time.