Github user ijokarumawak commented on a diff in the pull request:
https://github.com/apache/nifi/pull/2686#discussion_r193651707
--- Diff:
nifi-nar-bundles/nifi-deeplearning4j-bundle/nifi-deeplearning4j-processors/src/main/java/org/apache/nifi/processors/deeplearning4j/DeepLearning4JPredictor.java
---
@@ -0,0 +1,218 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.nifi.processors.deeplearning4j;
+import org.apache.nifi.annotation.behavior.EventDriven;
+import org.apache.nifi.annotation.behavior.InputRequirement;
+import org.apache.nifi.annotation.behavior.InputRequirement.Requirement;
+import org.apache.nifi.annotation.behavior.SupportsBatching;
+import org.apache.nifi.annotation.behavior.WritesAttribute;
+import org.apache.nifi.annotation.behavior.WritesAttributes;
+import org.apache.nifi.annotation.documentation.CapabilityDescription;
+import org.apache.nifi.annotation.documentation.Tags;
+import org.apache.nifi.components.PropertyDescriptor;
+import org.apache.nifi.flowfile.FlowFile;
+import org.apache.nifi.processor.ProcessContext;
+import org.apache.nifi.processor.ProcessSession;
+import org.apache.nifi.processor.Relationship;
+import org.apache.nifi.processor.exception.ProcessException;
+import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
+import org.nd4j.linalg.api.ndarray.INDArray;
+import org.nd4j.linalg.factory.Nd4j;
+import com.google.gson.Gson;
+import java.io.ByteArrayInputStream;
+import java.io.ByteArrayOutputStream;
+import java.io.IOException;
+import java.nio.charset.Charset;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+import java.util.stream.Collectors;
+
+@EventDriven
+@SupportsBatching
+@InputRequirement(Requirement.INPUT_REQUIRED)
+@Tags({"deeplearning4j", "dl4j", "predict", "classification",
"regression", "deep", "learning"})
+@CapabilityDescription("The DeepLearning4JPredictor predicts one or more
value(s) based on provided deeplearning4j (https://github.com/deeplearning4j)
model and the content of a FlowFile. "
+ + "The processor supports both classification and regression by
extracting the record from the FlowFile body and applying the model. "
+ + "The processor supports batch by allowing multiple records to be
passed in the FlowFile body with each record separated by the 'Record
Separator' property. "
+ + "Each record can contain multiple fields with each field separated
by the 'Field Separator' property."
+ )
+@WritesAttributes({
+ @WritesAttribute(attribute =
AbstractDeepLearning4JProcessor.DEEPLEARNING4J_ERROR_MESSAGE, description =
"Deeplearning4J error message"),
+ @WritesAttribute(attribute =
AbstractDeepLearning4JProcessor.DEEPLEARNING4J_OUTPUT_SHAPE, description =
"Deeplearning4J output shape"),
+ })
+public class DeepLearning4JPredictor extends
AbstractDeepLearning4JProcessor {
--- End diff --
I'm fairly new to DL4J so I can be totally wrong. But DL4J seems having two
distinct model types, MultiLayerNetwork and ComputationGraph. If we are going
to add ComputationGraph version in the future, which can be more complex,
having multiple input arrays ... etc, then it may be a chance to add another
processor.
Based on that, I think following names may sound good, too:
- ApplyDL4JMultiLayerNetwork
- ApplyDL4JComputationGraph
It seems whether classification or regression does not matter in this
processor's point of view.
---
