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Posted to commits@camel.apache.org by nf...@apache.org on 2022/04/28 09:08:49 UTC
[camel] branch CAMEL-17537/upgrade-djl-to-0.16 created (now b19c4a05389)
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nfilotto pushed a change to branch CAMEL-17537/upgrade-djl-to-0.16
in repository https://gitbox.apache.org/repos/asf/camel.git
at b19c4a05389 CAMEL-17537: camel-djl - Upgrade to 0.16.0
This branch includes the following new commits:
new b19c4a05389 CAMEL-17537: camel-djl - Upgrade to 0.16.0
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[camel] 01/01: CAMEL-17537: camel-djl - Upgrade to 0.16.0
Posted by nf...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
nfilotto pushed a commit to branch CAMEL-17537/upgrade-djl-to-0.16
in repository https://gitbox.apache.org/repos/asf/camel.git
commit b19c4a05389ce1f1b55202982192c24465855680
Author: Nicolas Filotto <nf...@talend.com>
AuthorDate: Thu Apr 28 11:07:42 2022 +0200
CAMEL-17537: camel-djl - Upgrade to 0.16.0
---
camel-dependencies/pom.xml | 2 +-
.../org/apache/camel/component/djl/training/MnistTraining.java | 9 +++------
parent/pom.xml | 2 +-
3 files changed, 5 insertions(+), 8 deletions(-)
diff --git a/camel-dependencies/pom.xml b/camel-dependencies/pom.xml
index 016d429f7ad..46f700ca9c1 100644
--- a/camel-dependencies/pom.xml
+++ b/camel-dependencies/pom.xml
@@ -176,7 +176,7 @@
<djl-mxnet-native-version>1.8.0</djl-mxnet-native-version>
<djl-pytorch-native-version>1.8.1</djl-pytorch-native-version>
<djl-tensorflow-native-version>2.4.1</djl-tensorflow-native-version>
- <djl-version>0.11.0</djl-version>
+ <djl-version>0.16.0</djl-version>
<dnsjava-version>3.5.0</dnsjava-version>
<docker-java-version>3.2.13</docker-java-version>
<dozer-version>6.5.2</dozer-version>
diff --git a/components/camel-djl/src/test/java/org/apache/camel/component/djl/training/MnistTraining.java b/components/camel-djl/src/test/java/org/apache/camel/component/djl/training/MnistTraining.java
index af54b713183..ef665aaca04 100644
--- a/components/camel-djl/src/test/java/org/apache/camel/component/djl/training/MnistTraining.java
+++ b/components/camel-djl/src/test/java/org/apache/camel/component/djl/training/MnistTraining.java
@@ -20,10 +20,10 @@ package org.apache.camel.component.djl.training;
import java.io.IOException;
import java.nio.file.Paths;
-import ai.djl.Device;
import ai.djl.Model;
import ai.djl.basicdataset.cv.classification.Mnist;
import ai.djl.basicmodelzoo.basic.Mlp;
+import ai.djl.engine.Engine;
import ai.djl.metric.Metrics;
import ai.djl.ndarray.types.Shape;
import ai.djl.nn.Block;
@@ -37,13 +37,9 @@ import ai.djl.training.listener.TrainingListener;
import ai.djl.training.loss.Loss;
import ai.djl.training.util.ProgressBar;
import ai.djl.translate.TranslateException;
-import org.slf4j.Logger;
-import org.slf4j.LoggerFactory;
// Helper to train mnist model for tests
public final class MnistTraining {
- private static final Logger LOG = LoggerFactory.getLogger(MnistTraining.class);
-
private static final String MODEL_DIR = "src/test/resources/models/mnist";
private static final String MODEL_NAME = "mlp";
@@ -62,9 +58,10 @@ public final class MnistTraining {
RandomAccessDataset trainingSet = prepareDataset(Dataset.Usage.TRAIN, 64, Long.MAX_VALUE);
RandomAccessDataset validateSet = prepareDataset(Dataset.Usage.TEST, 64, Long.MAX_VALUE);
+ final Engine engine = Engine.getInstance();
// setup training configuration
DefaultTrainingConfig config = new DefaultTrainingConfig(Loss.softmaxCrossEntropyLoss())
- .addEvaluator(new Accuracy()).optDevices(Device.getDevices(Device.getGpuCount()))
+ .addEvaluator(new Accuracy()).optDevices(engine.getDevices(engine.getGpuCount()))
.addTrainingListeners(TrainingListener.Defaults.logging());
try (Trainer trainer = model.newTrainer(config)) {
diff --git a/parent/pom.xml b/parent/pom.xml
index 24b75185f7a..71975638427 100644
--- a/parent/pom.xml
+++ b/parent/pom.xml
@@ -154,7 +154,7 @@
<directory-watcher-version>0.15.1</directory-watcher-version>
<disruptor-version>3.4.4</disruptor-version>
<dnsjava-version>3.5.0</dnsjava-version>
- <djl-version>0.11.0</djl-version>
+ <djl-version>0.16.0</djl-version>
<djl-mxnet-native-version>1.8.0</djl-mxnet-native-version>
<djl-pytorch-native-version>1.8.1</djl-pytorch-native-version>
<djl-tensorflow-native-version>2.4.1</djl-tensorflow-native-version>