How to use the mhcflurry.Class1AffinityPredictor.load function in mhcflurry
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openvax / mhctools / mhctools / mhcflurry.py View on Github 
# Keras and its backend (either Theano or TF) which end up
# slowing down responsive for any CLI application using MHCtools
from mhcflurry import Class1AffinityPredictor
BasePredictor.__init__(
self,
alleles=alleles,
default_peptide_lengths=default_peptide_lengths,
min_peptide_length=8,
max_peptide_length=15)
if predictor:
self.predictor = predictor
elif models_path:
logging.info("Loading MHCflurry models from %s" % models_path)
self.predictor = Class1AffinityPredictor.load(models_path)
else:
self.predictor = Class1AffinityPredictor.load()
# relying on BasePredictor and MHCflurry to both normalize
# allele names the same way using mhcnames
for allele in self.alleles:
if allele not in self.predictor.supported_alleles:
raise UnsupportedAllele(allele)
