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.
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