complete recurrent.

Signed-off-by: Robert Altena <[email protected]>

Author: RobAltena

dl4j-examples/src/main/java/org/deeplearning4j/examples/recurrent/word2vecsentiment/SentimentExampleIterator.java

@@ -32,6 +32,7 @@
 
 import java.io.File;
 import java.io.IOException;
+import java.nio.charset.Charset;
 import java.util.ArrayList;
 import java.util.Arrays;
 import java.util.List;
@@ -100,13 +101,13 @@ private DataSet nextDataSet(int num) throws IOException {
             if(cursor % 2 == 0){
                 //Load positive review
                 int posReviewNumber = cursor / 2;
-                String review = FileUtils.readFileToString(positiveFiles[posReviewNumber]);
+                String review = FileUtils.readFileToString(positiveFiles[posReviewNumber], (Charset)null);
                 reviews.add(review);
                 positive[i] = true;
             } else {
                 //Load negative review
                 int negReviewNumber = cursor / 2;
-                String review = FileUtils.readFileToString(negativeFiles[negReviewNumber]);
+                String review = FileUtils.readFileToString(negativeFiles[negReviewNumber], (Charset)null);
                 reviews.add(review);
                 positive[i] = false;
             }
@@ -253,7 +254,7 @@ public boolean isPositiveReview(int index){
      * @throws IOException If file cannot be read
      */
     public INDArray loadFeaturesFromFile(File file, int maxLength) throws IOException {
-        String review = FileUtils.readFileToString(file);
+        String review = FileUtils.readFileToString(file, (Charset)null);
         return loadFeaturesFromString(review, maxLength);
     }
 

dl4j-examples/src/main/java/org/deeplearning4j/examples/recurrent/word2vecsentiment/Word2VecSentimentRNN.java

@@ -1,4 +1,4 @@
-/*******************************************************************************
+/* *****************************************************************************
  * Copyright (c) 2015-2019 Skymind, Inc.
  *
  * This program and the accompanying materials are made available under the
@@ -40,6 +40,7 @@
 
 import java.io.File;
 import java.net.URL;
+import java.nio.charset.Charset;
 
 /**Example: Given a movie review (raw text), classify that movie review as either positive or negative based on the words it contains.
  * This is done by combining Word2Vec vectors and a recurrent neural network model. Each word in a review is vectorized
@@ -118,7 +119,7 @@ public static void main(String[] args) throws Exception {
 
         //After training: load a single example and generate predictions
         File shortNegativeReviewFile = new File(FilenameUtils.concat(DATA_PATH, "aclImdb/test/neg/12100_1.txt"));
-        String shortNegativeReview = FileUtils.readFileToString(shortNegativeReviewFile);
+        String shortNegativeReview = FileUtils.readFileToString(shortNegativeReviewFile, (Charset)null);
 
         INDArray features = test.loadFeaturesFromString(shortNegativeReview, truncateReviewsToLength);
         INDArray networkOutput = net.output(features);