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use gpu for AmberRelaxation if available #4

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use gpu for AmberRelaxation if available #4

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10 changes: 9 additions & 1 deletion inference.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@

import numpy as np
import torch
import simtk.openmm as openmm

from rhofold.data.balstn import BLASTN
from rhofold.rhofold import RhoFold
Expand Down Expand Up @@ -103,13 +104,20 @@ def main(config):
path=unrelaxed_model, chain_id=None,
confidence=output['plddt'][0].data.cpu().numpy(),
logger=logger)
# Check if CUDA is available in OpenMM
cuda_available = False
for i in range(openmm.Platform.getNumPlatforms()):
if openmm.Platform.getPlatform(i).getName().lower() == "cuda":
cuda_available = True
break

# Amber relaxation
if config.relax_steps is not None:
relax_steps = int(config.relax_steps)
if relax_steps > 0:
with timing(f'Amber Relaxation : {relax_steps} iterations', logger=logger):
amber_relax = AmberRelaxation(max_iterations=relax_steps, logger=logger)
use_gpu = cuda_available and config.device.startswith("cuda:")
amber_relax = AmberRelaxation(max_iterations=relax_steps, logger=logger, use_gpu=use_gpu)
relaxed_model = f'{config.output_dir}/relaxed_{relax_steps}_model.pdb'
amber_relax.process(unrelaxed_model, relaxed_model)

Expand Down