From a9a88a148935be4b807036f6c008383f5a860bcd Mon Sep 17 00:00:00 2001
From: Tim O'Donnell <timodonnell@gmail.com>
Date: Mon, 24 Jun 2019 12:21:57 -0400
Subject: [PATCH] fix
---
mhcflurry/class1_neural_network.py | 1 +
mhcflurry/custom_loss.py | 4 ++--
2 files changed, 3 insertions(+), 2 deletions(-)
diff --git a/mhcflurry/class1_neural_network.py b/mhcflurry/class1_neural_network.py
index 92cf8b27..c1f8e106 100644
--- a/mhcflurry/class1_neural_network.py
+++ b/mhcflurry/class1_neural_network.py
@@ -718,6 +718,7 @@ class Class1NeuralNetwork(object):
y_values,
]),
}
+ adjusted_inequalities_with_random_negatives = None
if sample_weights is not None:
sample_weights_with_random_negatives = numpy.concatenate([
numpy.ones(int(num_random_negative.sum())),
diff --git a/mhcflurry/custom_loss.py b/mhcflurry/custom_loss.py
index 641fd099..eabdd130 100644
--- a/mhcflurry/custom_loss.py
+++ b/mhcflurry/custom_loss.py
@@ -82,7 +82,7 @@ class MSEWithInequalities(Loss):
def encode_y(y, inequalities=None):
y = array(y, dtype="float32")
if isnan(y).any():
- raise ValueError("y contains NaN")
+ raise ValueError("y contains NaN: %s" % str(y))
if (y > 1.0).any():
raise ValueError("y contains values > 1.0")
if (y < 0.0).any():
@@ -141,7 +141,7 @@ class MSEWithInequalitiesAndMultipleOutputs(Loss):
def encode_y(y, inequalities=None, output_indices=None):
y = array(y, dtype="float32")
if isnan(y).any():
- raise ValueError("y contains NaN")
+ raise ValueError("y contains NaN: %s" % str(y))
if (y > 1.0).any():
raise ValueError("y contains values > 1.0")
if (y < 0.0).any():
--
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