From 44bdd65b6c8245e779f45dfbb36a3e369a8daf50 Mon Sep 17 00:00:00 2001
From: Tim O'Donnell <timodonnell@gmail.com>
Date: Fri, 7 Jun 2019 16:48:39 -0400
Subject: [PATCH] fix
---
.../models_class1_pan/generate_hyperparameters.py | 2 +-
mhcflurry/train_pan_allele_models_command.py | 5 +++--
2 files changed, 4 insertions(+), 3 deletions(-)
diff --git a/downloads-generation/models_class1_pan/generate_hyperparameters.py b/downloads-generation/models_class1_pan/generate_hyperparameters.py
index fe05e313..ea728dc3 100644
--- a/downloads-generation/models_class1_pan/generate_hyperparameters.py
+++ b/downloads-generation/models_class1_pan/generate_hyperparameters.py
@@ -48,7 +48,7 @@ base_hyperparameters = {
}
grid = []
-for layer_sizes in [[1024, 512], [512, 512], [1024, 1024]]:
+for layer_sizes in [[512, 256], [1024, 512], [1024, 1024]]:
for l1 in [0.0, 0.0001, 0.001, 0.01]:
new = deepcopy(base_hyperparameters)
new["layer_sizes"] = layer_sizes
diff --git a/mhcflurry/train_pan_allele_models_command.py b/mhcflurry/train_pan_allele_models_command.py
index 9880f804..fa530d15 100644
--- a/mhcflurry/train_pan_allele_models_command.py
+++ b/mhcflurry/train_pan_allele_models_command.py
@@ -434,7 +434,7 @@ def train_model(
train_peptides = EncodableSequences(train_data.peptide.values)
train_alleles = AlleleEncoding(
train_data.allele.values, borrow_from=allele_encoding)
- train_target = from_ic50(train_data.measurement_value)
+ train_target = from_ic50(train_data.measurement_value.values)
model = Class1NeuralNetwork(**hyperparameters)
@@ -468,6 +468,7 @@ def train_model(
peptides=peptides,
affinities=affinities,
allele_encoding=alleles)
+
fit_time = time.time() - start
start = time.time()
predictions = model.predict(
@@ -484,7 +485,7 @@ def train_model(
mask = train_data.measurement_inequality == inequality
predictions[mask.values] = func(
predictions[mask.values],
- train_data.loc[mask.values].measurement_value.values)
+ train_data.loc[mask].measurement_value.values)
score_mse = numpy.mean((from_ic50(predictions) - train_target)**2)
score_time = time.time() - start
print(
--
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