From b910d1e70368329a321354ce100be7808ff666ab Mon Sep 17 00:00:00 2001
From: Tim O'Donnell <timodonnell@gmail.com>
Date: Sat, 14 Sep 2019 19:33:41 -0400
Subject: [PATCH] fix
---
mhcflurry/class1_affinity_predictor.py | 13 ++++++++++++-
mhcflurry/class1_neural_network.py | 14 ++++++++++----
2 files changed, 22 insertions(+), 5 deletions(-)
diff --git a/mhcflurry/class1_affinity_predictor.py b/mhcflurry/class1_affinity_predictor.py
index 4eacb9a1..57637888 100644
--- a/mhcflurry/class1_affinity_predictor.py
+++ b/mhcflurry/class1_affinity_predictor.py
@@ -360,13 +360,24 @@ class Class1AffinityPredictor(object):
sub_manifest_df = self.manifest_df.loc[
self.manifest_df.model_name.isin(model_names_to_write)
- ]
+ ].copy()
+ # Network JSON configs may have changed since the models were added,
+ # for example due to changes to the allele representation layer.
+ # So we update the JSON configs here also.
+ updated_network_config_jsons = []
for (_, row) in sub_manifest_df.iterrows():
+ updated_network_config_jsons.append(
+ json.dumps(row.model.get_config()))
weights_path = self.weights_path(models_dir, row.model_name)
Class1AffinityPredictor.save_weights(
row.model.get_weights(), weights_path)
logging.info("Wrote: %s", weights_path)
+ sub_manifest_df["config_json"] = updated_network_config_jsons
+ self.manifest_df.loc[
+ sub_manifest_df.index,
+ "config_json"
+ ] = updated_network_config_jsons
write_manifest_df = self.manifest_df[[
c for c in self.manifest_df.columns if c != "model"
diff --git a/mhcflurry/class1_neural_network.py b/mhcflurry/class1_neural_network.py
index 411ba54d..78e7ad69 100644
--- a/mhcflurry/class1_neural_network.py
+++ b/mhcflurry/class1_neural_network.py
@@ -1369,7 +1369,8 @@ class Class1NeuralNetwork(object):
layer = original_model.get_layer("allele_representation")
existing_weights_shape = (layer.input_dim, layer.output_dim)
self.set_allele_representations(
- numpy.zeros(shape=(0,) + existing_weights_shape.shape[1:]))
+ numpy.zeros(shape=(0,) + existing_weights_shape[1:]),
+ force_surgery=True)
def set_allele_representations(self, allele_representations, force_surgery=False):
@@ -1397,15 +1398,18 @@ class Class1NeuralNetwork(object):
import keras.backend as K
import tensorflow as tf
- reshaped = allele_representations.reshape(
- (allele_representations.shape[0], -1))
+ reshaped = allele_representations.reshape((
+ allele_representations.shape[0],
+ numpy.product(allele_representations.shape[1:])
+ ))
original_model = self.network()
layer = original_model.get_layer("allele_representation")
existing_weights_shape = (layer.input_dim, layer.output_dim)
# Only changes to the number of supported alleles (not the length of
# the allele sequences) are allowed.
- assert existing_weights_shape[1:] == reshaped.shape[1:]
+ assert existing_weights_shape[1:] == reshaped.shape[1:], (
+ existing_weights_shape, reshaped.shape)
if existing_weights_shape[0] > reshaped.shape[0] and not force_surgery:
# Extend with NaNs so we can avoid having to reshape the weights
@@ -1439,6 +1443,8 @@ class Class1NeuralNetwork(object):
def throw(*args, **kwargs):
raise RuntimeError("Using a disabled model!")
original_model.predict = \
+ original_model.to_json = \
+ original_model.get_weights = \
original_model.fit = \
original_model.fit_generator = throw
--
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