Github user markap14 commented on a diff in the pull request:
https://github.com/apache/nifi/pull/2686#discussion_r187350055
--- Diff:
nifi-nar-bundles/nifi-deeplearning4j-bundle/nifi-deeplearning4j-processors/src/main/java/org/apache/nifi/processors/deeplearning4j/AbstractDeepLearning4JProcessor.java
---
@@ -0,0 +1,106 @@
+/*
+ * 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 java.io.IOException;
+import org.apache.nifi.annotation.lifecycle.OnStopped;
+import org.apache.nifi.components.PropertyDescriptor;
+import org.apache.nifi.expression.ExpressionLanguageScope;
+import org.apache.nifi.processor.AbstractProcessor;
+import org.apache.nifi.processor.ProcessContext;
+import org.apache.nifi.processor.util.StandardValidators;
+import org.deeplearning4j.nn.multilayer.MultiLayerNetwork;
+import org.deeplearning4j.util.ModelSerializer;
+
+/**
+ * Base class for deeplearning4j processors
+ */
+public abstract class AbstractDeepLearning4JProcessor extends
AbstractProcessor {
+
+ public static final PropertyDescriptor CHARSET = new
PropertyDescriptor.Builder()
+ .name("deeplearning4j-charset")
+ .displayName("Character Set")
+ .description("Specifies the character set of the document
data.")
+ .required(true)
+ .defaultValue("UTF-8")
+
.expressionLanguageSupported(ExpressionLanguageScope.FLOWFILE_ATTRIBUTES)
+ .addValidator(StandardValidators.CHARACTER_SET_VALIDATOR)
+ .build();
+
+ public static final PropertyDescriptor FIELD_SEPARATOR = new
PropertyDescriptor.Builder()
+ .name("deeplearning4j-field-separator")
+ .displayName("Field Separator")
+ .description("Specifies the field separator in the records.
(default is comma)")
+ .required(true)
+ .defaultValue(",")
+
.expressionLanguageSupported(ExpressionLanguageScope.FLOWFILE_ATTRIBUTES)
+ .addValidator(StandardValidators.NON_EMPTY_VALIDATOR)
+ .build();
+
+ public static final PropertyDescriptor RECORD_SEPARATOR = new
PropertyDescriptor.Builder()
+ .name("deeplearning4j-record-separator")
+ .displayName("Record Separator")
+ .description("Specifies the records separator in the message
body. (defaults to new line)")
+ .required(true)
+ .defaultValue(System.lineSeparator())
+
.expressionLanguageSupported(ExpressionLanguageScope.FLOWFILE_ATTRIBUTES)
+ .addValidator(StandardValidators.NON_EMPTY_VALIDATOR)
+ .build();
+
+ public static final PropertyDescriptor MODEL_FILE = new
PropertyDescriptor.Builder()
+ .name("model-file")
+ .displayName("Model File")
+ .description("Location of the Deeplearning4J model zip file")
+ .required(true)
+
.expressionLanguageSupported(ExpressionLanguageScope.VARIABLE_REGISTRY)
+ .addValidator(StandardValidators.FILE_EXISTS_VALIDATOR)
+ .build();
+
+ public static final PropertyDescriptor RECORD_DIMENSIONS = new
PropertyDescriptor.Builder()
+ .name("deeplearning4j-record-dimension")
+ .displayName("Record dimensions separated by field separator")
+ .description("Dimension of array in each a record (eg: 2,4 - a
2x4 array)")
+ .required(true)
+
.expressionLanguageSupported(ExpressionLanguageScope.FLOWFILE_ATTRIBUTES)
+ .addValidator(StandardValidators.NON_EMPTY_VALIDATOR)
+ .build();
+
+ public static final String DEEPLEARNING4J_ERROR_MESSAGE =
"deeplearning4j.error.message";
+
+ public static final String DEEPLEARNING4J_OUTPUT_SHAPE =
"deeplearning4j.output.shape";
+
+ protected MultiLayerNetwork model = null;
--- End diff --
All member variables need to be protected / accessed in a thread-safe
manner.
---
