kfzyqin / TextFlow

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

Latent Normalizing Flows for Discrete Sequences

This code provides an implementation for and reproduces results from Latent Normalizing Flows for Discrete Sequences Zachary Ziegler, Alexander Rush ICML 2019

Dependencies

The code was tested with python 3.6, pytorch 0.4.1, torchtext 0.2.3, and CUDA 9.2.

Character-level language modeling:

PTB data with Mikolov preprocessing is checked in.

Baseline and proposed models can be trained with:

python main.py --dataset ptb --run_name charptb_baselinelstm --model_type baseline --dropout_p 0.1 --optim sgd --lr 20
python main.py --dataset ptb --run_name charptb_discreteflow_af-af 
python main.py --dataset ptb --run_name charptb_discreteflow_af-scf --hiddenflow_scf_layers
python main.py --dataset ptb --run_name charptb_discreteflow_iaf-scf --dropout_p 0 --hiddenflow_flow_layers 3 --hiddenflow_scf_layers --prior_type IAF

Evaluation on the test set is run with e.g.

python main.py --dataset ptb --run_name charptb_baselinelstm --model_type baseline --dropout_p 0.1 --optim sgd --lr 20 --load_dir output/charptb_baselinelstm/saves/<save> --evaluate

Polyphonic music:

Commands to train the baseline and proposed models are

Nottingham:

python main.py --indep_bernoulli --dataset nottingham --run_name nottingham_baselinelstm --model_type baseline --dropout_p 0.1 --optim sgd --lr 20 --patience 4
python main.py --indep_bernoulli --dataset nottingham --run_name nottingham_discreteflow_af-af --patience 2 --ELBO_samples 1 --B_train 5 --B_val 1 --initial_kl_zero 20 --kl_rampup_time 15
python main.py --indep_bernoulli --dataset nottingham --run_name nottingham_discreteflow_af-scf --patience 2 --ELBO_samples 1 --B_train 5 --B_val 1 --initial_kl_zero 20 --kl_rampup_time 15 --hiddenflow_scf_layers
python main.py --indep_bernoulli --dataset nottingham --run_name nottingham_discreteflow_iaf-scf --patience 2 --ELBO_samples 1 --B_train 5 --B_val 1 --initial_kl_zero 20 --kl_rampup_time 15 --hiddenflow_scf_layers --prior_type IAF

Piano_midi

python main.py --indep_bernoulli --dataset piano_midi --run_name piano_midi_baselinelstm --model_type baseline --dropout_p 0.1 --optim sgd --lr 20 --patience 4
python main.py --indep_bernoulli --dataset piano_midi --run_name piano_midi_discreteflow_af-af --patience 2 --ELBO_samples 1 --B_train 1 --B_val 1 --initial_kl_zero 20 --kl_rampup_time 15 --nll_samples 4 --grad_accum 8
python main.py --indep_bernoulli --dataset piano_midi --run_name piano_midi_discreteflow_af-scf --patience 2 --ELBO_samples 1 --B_train 1 --B_val 1 --initial_kl_zero 20 --kl_rampup_time 15 --nll_samples 4 --grad_accum 8 --hiddenflow_scf_layers
python main.py --indep_bernoulli --dataset piano_midi --run_name piano_midi_discreteflow_iaf-scf --patience 2 --ELBO_samples 1 --B_train 1 --B_val 1 --initial_kl_zero 20 --kl_rampup_time 15 --nll_samples 4 --grad_accum 8 --hiddenflow_scf_layers --prior_type IAF

Musedata

python main.py --indep_bernoulli --dataset muse_data --run_name muse_data_baselinelstm --model_type baseline --dropout_p 0.1 --optim sgd --lr 20 --patience 4
python main.py --indep_bernoulli --dataset muse_data --run_name muse_data_discreteflow_af-af --patience 2 --ELBO_samples 1 --B_train 1 --B_val 1 --initial_kl_zero 20 --kl_rampup_time 15 --nll_samples 4 --grad_accum 8
python main.py --indep_bernoulli --dataset muse_data --run_name muse_data_discreteflow_af-scf --patience 2 --ELBO_samples 1 --B_train 1 --B_val 1 --initial_kl_zero 20 --kl_rampup_time 15 --nll_samples 4 --grad_accum 8 --hiddenflow_scf_layers
python main.py --indep_bernoulli --dataset muse_data --run_name muse_data_discreteflow_iaf-scf --patience 2 --ELBO_samples 1 --B_train 1 --B_val 1 --initial_kl_zero 20 --kl_rampup_time 15 --nll_samples 4 --grad_accum 8 --hiddenflow_scf_layers --prior_type IAF

JSB_chorales

python main.py --indep_bernoulli --dataset jsb_chorales --run_name jsb_chorales_baselinelstm --model_type baseline --dropout_p 0.1 --optim sgd --lr 20 --patience 4
python main.py --indep_bernoulli --dataset jsb_chorales --run_name jsb_chorales_discreteflow_af-af --patience 2 --ELBO_samples 1 --B_train 5 --B_val 64 --initial_kl_zero 20 --kl_rampup_time 15
python main.py --indep_bernoulli --dataset jsb_chorales --run_name jsb_chorales_discreteflow_af-scf --patience 2 --ELBO_samples 1 --B_train 5 --B_val 64 --initial_kl_zero 20 --kl_rampup_time 15 --hiddenflow_scf_layers
python main.py --indep_bernoulli --dataset jsb_chorales --run_name jsb_chorales_discreteflow_iaf-scf --patience 2 --ELBO_samples 1 --B_train 5 --B_val 64 --initial_kl_zero 20 --kl_rampup_time 15 --hiddenflow_scf_layers --prior_type IAF

About

License:MIT License


Languages

Language:Python 100.0%