metadata
license: mit
tags:
- phylogenetics
- biology
DeepPhylo checkpoints
Trained models for Deep Generative Models for Phylogenetic Inference with Complex Evolutionary Processes. These are the exact checkpoints behind the paper's NELBO bar chart and its RF-vs-sites / RF-vs-taxa figures.
Five methods (BU, MO, TD, PF2, QF) on three simulated datasets: jc (DNA, Jukes-Cantor), cat (amino
acids, CAT mixture), indels (DNA, GTR with indels and realignment).
| Directory | Method | Dataset | Step | Size |
|---|---|---|---|---|
BU_JC |
Bottom up | JC | 26,000 | 224 MiB |
MO_JC |
Middle out | JC | 26,000 | 224 MiB |
TD_JC |
Top down | JC | 22,000 | 224 MiB |
PF2_JC |
Phyloformer 2 (baseline) | JC | 16,000 | 299 MiB |
QF_JC |
QuartFormer (baseline) | JC | 56,000 | 26 MiB |
BU_CAT |
Bottom up | CAT | 26,000 | 224 MiB |
MO_CAT |
Middle out | CAT | 26,000 | 224 MiB |
TD_CAT |
Top down | CAT | 22,000 | 224 MiB |
PF2_CAT |
Phyloformer 2 (baseline) | CAT | 16,000 | 299 MiB |
QF_CAT |
QuartFormer (baseline) | CAT | 60,000 | 26 MiB |
BU_Indels |
Bottom up | Indels | 26,000 | 224 MiB |
MO_Indels |
Middle out | Indels | 24,000 | 224 MiB |
TD_Indels |
Top down | Indels | 22,000 | 224 MiB |
PF2_Indels |
Phyloformer 2 (baseline) | Indels | 14,000 | 299 MiB |
QF_Indels |
QuartFormer (baseline) | Indels | 50,000 | 26 MiB |
Each directory holds model.ckpt and the config.yaml of the run that produced
it, which is what the code reads to rebuild the model.
Usage
Clone DeepPhylo, then place a
directory here under checkpoints/ and name it in run=:
python sample.py run=BU_JC sampling.path=out.pkl
See the repository README for greedy vs. consensus decoding.
MANIFEST.tsv lists the training run id, step, size and SHA-256 of every file.