#6366 RecordReaderMultiDataSetIterator: better validation/errors; 5D …

…(3D CNN) NDArrayWritable support
deeplearning4j · Sep 6, 2018 · 6ee913b · 6ee913b
1 parent 813e409
commit 6ee913b
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Showing 3 changed files with 146 additions and 2 deletions.
diff --git a/...c/test/java/org/deeplearning4j/datasets/datavec/RecordReaderMultiDataSetIteratorTest.java b/...c/test/java/org/deeplearning4j/datasets/datavec/RecordReaderMultiDataSetIteratorTest.java
@@ -21,16 +21,21 @@
 import org.apache.commons.compress.utils.IOUtils;
 import org.apache.commons.io.FileUtils;
 import org.apache.commons.io.FilenameUtils;
+import org.datavec.api.conf.Configuration;
 import org.datavec.api.io.labels.ParentPathLabelGenerator;
+import org.datavec.api.records.Record;
 import org.datavec.api.records.metadata.RecordMetaData;
+import org.datavec.api.records.reader.BaseRecordReader;
 import org.datavec.api.records.reader.RecordReader;
 import org.datavec.api.records.reader.SequenceRecordReader;
 import org.datavec.api.records.reader.impl.collection.CollectionSequenceRecordReader;
 import org.datavec.api.records.reader.impl.csv.CSVRecordReader;
 import org.datavec.api.records.reader.impl.csv.CSVSequenceRecordReader;
 import org.datavec.api.split.CollectionInputSplit;
 import org.datavec.api.split.FileSplit;
+import org.datavec.api.split.InputSplit;
 import org.datavec.api.split.NumberedFileInputSplit;
+import org.datavec.api.util.ndarray.RecordConverter;
 import org.datavec.api.writable.DoubleWritable;
 import org.datavec.api.writable.IntWritable;
 import org.datavec.api.writable.Writable;
@@ -55,6 +60,7 @@
 
 import static org.junit.Assert.*;
 import static org.nd4j.linalg.indexing.NDArrayIndex.all;
+import static org.nd4j.linalg.indexing.NDArrayIndex.interval;
 import static org.nd4j.linalg.indexing.NDArrayIndex.point;
 
 public class RecordReaderMultiDataSetIteratorTest extends BaseDL4JTest {
@@ -792,8 +798,131 @@ public void testExcludeStringColCSV() throws Exception {
 
         assertEquals(expFeatures, mds.getFeatures(0));
         assertEquals(expLabels, mds.getLabels(0));
+    }
+
+
+    private static final int nX = 32;
+    private static final int nY = 32;
+    private static final int nZ = 28;
+
+
+    @Test
+    public void testRRMDSI5D() {
+        int batchSize = 5;
+
+        CustomRecordReader recordReader = new CustomRecordReader();
+        DataSetIterator dataIter = new RecordReaderDataSetIterator(recordReader, batchSize,
+                1, /* Index of label in records */
+                2 /* number of different labels */);
+
+        int count = 0;
+        while(dataIter.hasNext()){
+            DataSet ds = dataIter.next();
+
+            int offset = 5*count;
+            for( int i=0; i<5; i++ ){
+                INDArray act = ds.getFeatures().get(interval(i,i,true), all(), all(), all(), all());
+                INDArray exp = Nd4j.valueArrayOf(new int[]{1, 1, nZ, nX, nY}, i + offset );
+                assertEquals(exp, act);
+            }
+            count++;
+        }
 
+        assertEquals(2, count);
+    }
+
+
+    static class CustomRecordReader extends BaseRecordReader {
+
+        int n = 0;
+
+        CustomRecordReader() { }
+
+        @Override
+        public boolean batchesSupported() {
+            return false;
+        }
+
+        @Override
+        public List<List<Writable>> next(int num) {
+            throw new RuntimeException("Not implemented");
+        }
 
+        @Override
+        public List<Writable> next() {
+            INDArray nd = Nd4j.create(new float[nZ*nY*nX], new int[] {1, 1, nZ, nY, nX }, 'C').assign(n);
+            final List<Writable>res = RecordConverter.toRecord(nd);
+            res.add(new IntWritable(0));
+            n++;
+            return res;
+        }
+
+        @Override
+        public boolean hasNext() {
+            return n<10;
+        }
 
+        final static ArrayList<String> labels = new ArrayList<>(2);
+        static {
+            labels.add("lbl0");
+            labels.add("lbl1");
+        }
+        @Override
+        public List<String> getLabels() {
+            return labels;
+        }
+
+        @Override
+        public void reset() {
+            n = 0;
+        }
+
+        @Override
+        public boolean resetSupported() {
+            return true;
+        }
+
+        @Override
+        public List<Writable> record(URI uri, DataInputStream dataInputStream) {
+            return next();
+        }
+
+        @Override
+        public Record nextRecord() {
+            List<Writable> r = next();
+            return new org.datavec.api.records.impl.Record(r, null);
+        }
+
+        @Override
+        public Record loadFromMetaData(RecordMetaData recordMetaData) throws IOException {
+            throw new RuntimeException("Not implemented");
+        }
+
+        @Override
+        public List<Record> loadFromMetaData(List<RecordMetaData> recordMetaDatas) {
+            throw new RuntimeException("Not implemented");
+        }
+
+        @Override
+        public void close() {
+        }
+
+        @Override
+        public void setConf(Configuration conf) {
+        }
+
+        @Override
+        public Configuration getConf() {
+            return null;
+        }
+
+        @Override
+        public void initialize(InputSplit split) {
+            n = 0;
+        }
+        @Override
+        public void initialize(Configuration conf, InputSplit split) {
+            n = 0;
+        }
     }
 }
diff --git a/...s/src/main/java/org/deeplearning4j/datasets/datavec/RecordReaderMultiDataSetIterator.java b/...s/src/main/java/org/deeplearning4j/datasets/datavec/RecordReaderMultiDataSetIterator.java
@@ -33,6 +33,7 @@
 import org.datavec.api.writable.Writable;
 import org.datavec.api.writable.batch.NDArrayRecordBatch;
 import org.deeplearning4j.datasets.datavec.exception.ZeroLengthSequenceException;
+import org.nd4j.base.Preconditions;
 import org.nd4j.linalg.api.ndarray.INDArray;
 import org.nd4j.linalg.dataset.api.MultiDataSet;
 import org.nd4j.linalg.dataset.api.MultiDataSetPreProcessor;
@@ -540,6 +541,15 @@ private INDArray convertWritablesHelper(List<List<Writable>> list, int minValues
     }
 
     private void putExample(INDArray arr, INDArray singleExample, int exampleIdx) {
+        Preconditions.checkState(singleExample.size(0) == 1 && singleExample.rank() == arr.rank(), "Cannot put array: array should have leading dimension of 1 " +
+                "and equal rank to output array. Attempting to put array of shape %s into output array of shape %s", singleExample.shape(), arr.shape());
+
+        long[] arrShape = arr.shape();
+        long[] singleShape = singleExample.shape();
+        for( int i=1; i<arr.rank(); i++ ){
+            Preconditions.checkState(arrShape[i] == singleShape[i], "Single example array and output arrays differ at position %s:" +
+                    "single example shape %s, output array shape %s", i, singleShape, arrShape);
+        }
         switch (arr.rank()) {
             case 2:
                 arr.put(new INDArrayIndex[] {NDArrayIndex.point(exampleIdx), NDArrayIndex.all()}, singleExample);
@@ -552,8 +562,12 @@ private void putExample(INDArray arr, INDArray singleExample, int exampleIdx) {
                 arr.put(new INDArrayIndex[] {NDArrayIndex.point(exampleIdx), NDArrayIndex.all(), NDArrayIndex.all(),
                                 NDArrayIndex.all()}, singleExample);
                 break;
+            case 5:
+                arr.put(new INDArrayIndex[] {NDArrayIndex.point(exampleIdx), NDArrayIndex.all(), NDArrayIndex.all(),
+                        NDArrayIndex.all(), NDArrayIndex.all()}, singleExample);
+                break;
             default:
-                throw new RuntimeException("Unexpected rank: " + arr.rank());
+                throw new RuntimeException("Unexpected array rank: " + arr.rank() + " with shape " + Arrays.toString(arr.shape()) + " input arrays should be rank 2 to 5 inclusive");
         }
     }
 

diff --git a/.../java/org/deeplearning4j/nn/modelimport/keras/preprocessing/text/TokenizerImportTest.java b/.../java/org/deeplearning4j/nn/modelimport/keras/preprocessing/text/TokenizerImportTest.java
@@ -24,6 +24,7 @@
 
 import static org.junit.Assert.assertEquals;
 import static org.junit.Assert.assertFalse;
+import static org.junit.Assert.assertTrue;
 
 /**
  * Import Keras Tokenizer
@@ -44,7 +45,7 @@ public void importTest() throws IOException, InvalidKerasConfigurationException
         KerasTokenizer tokenizer = KerasTokenizer.fromJson(configResource.getFile().getAbsolutePath());
 
         assertEquals(100, tokenizer.getNumWords().intValue());
-        assertEquals(tokenizer.isLower();
+        assertTrue(tokenizer.isLower());
         assertEquals(" ", tokenizer.getSplit());
         assertFalse(tokenizer.isCharLevel());
         assertEquals(0, tokenizer.getDocumentCount().intValue());