From e7b34afbb4f09f66e0aa14b9a41e8d2eca8bece6 Mon Sep 17 00:00:00 2001
From: Alex Rubinsteyn <alex.rubinsteyn@gmail.com>
Date: Wed, 4 May 2016 17:16:16 -0400
Subject: [PATCH] small fix to training script
---
script/mhcflurry-train-class1-allele-specific-models.py | 9 ++-------
test/test_neural_nets.py | 4 ++--
2 files changed, 4 insertions(+), 9 deletions(-)
diff --git a/script/mhcflurry-train-class1-allele-specific-models.py b/script/mhcflurry-train-class1-allele-specific-models.py
index 5c0c8748..26970ff6 100755
--- a/script/mhcflurry-train-class1-allele-specific-models.py
+++ b/script/mhcflurry-train-class1-allele-specific-models.py
@@ -46,13 +46,8 @@ from keras.optimizers import RMSprop
from mhcflurry.common import normalize_allele_name
from mhcflurry.data import load_allele_datasets
from mhcflurry.class1_binding_predictor import Class1BindingPredictor
-from mhcflurry.class1_allele_specific_hyperparameters import (
- add_hyperparameter_arguments_to_parser
-)
-from mhcflurry.paths import (
- CLASS1_MODEL_DIRECTORY,
- CLASS1_DATA_DIRECTORY
-)
+from mhcflurry.feedforward_hyperparameters import add_hyperparameter_arguments_to_parser
+from mhcflurry.paths import (CLASS1_MODEL_DIRECTORY, CLASS1_DATA_DIRECTORY)
from mhcflurry.imputation import create_imputed_datasets, imputer_from_name
CSV_FILENAME = "combined_human_class1_dataset.csv"
diff --git a/test/test_neural_nets.py b/test/test_neural_nets.py
index 38c84441..5d4380d0 100644
--- a/test/test_neural_nets.py
+++ b/test/test_neural_nets.py
@@ -17,7 +17,7 @@ def test_make_embedding_network_properties():
optimizer=RMSprop(lr=0.7, rho=0.9, epsilon=1e-6))
eq_(nn.layers[0].input_dim, 3)
eq_(nn.loss, mse)
- eq_(nn.optimizer.lr, 0.7)
+ eq_(nn.optimizer.lr.eval(), 0.7)
print(nn.layers)
# embedding + flatten + (dense->activation) * hidden layers and last layer
eq_(len(nn.layers), 2 + 2 * (1 + len(layer_sizes)))
@@ -34,7 +34,7 @@ def test_make_hotshot_network_properties():
optimizer=RMSprop(lr=0.7, rho=0.9, epsilon=1e-6))
eq_(nn.layers[0].input_dim, 6)
eq_(nn.loss, mse)
- eq_(nn.optimizer.lr, 0.7)
+ eq_(nn.optimizer.lr.eval(), 0.7)
print(nn.layers)
eq_(len(nn.layers), 2 + 2 * (1 + len(layer_sizes)))
--
GitLab