Merge remote-tracking branch 'eclipse/master'

deeplearning4j/deeplearning4j-core/src/main/java/org/deeplearning4j/util/ModelGuesser.java

@@ -54,7 +54,11 @@ public class ModelGuesser {
      * @return the loaded normalizer
      */
     public static Normalizer<?> loadNormalizer(String path) {
-        return ModelSerializer.restoreNormalizerFromFile(new File(path));
+        try {
+            return ModelSerializer.restoreNormalizerFromFile(new File(path));
+        } catch (IOException e){
+            throw new RuntimeException(e);
+        }
     }
 
 

deeplearning4j/deeplearning4j-nn/src/main/java/org/deeplearning4j/util/ModelSerializer.java

@@ -16,6 +16,7 @@
 
 package org.deeplearning4j.util;
 
+import org.apache.commons.io.input.CloseShieldInputStream;
 import org.nd4j.shade.guava.io.Files;
 import lombok.NonNull;
 import lombok.extern.slf4j.Slf4j;
@@ -43,9 +44,12 @@ import org.nd4j.linalg.primitives.Pair;
 import java.io.*;
 import java.util.ArrayList;
 import java.util.Enumeration;
+import java.util.HashMap;
 import java.util.List;
+import java.util.Map;
 import java.util.zip.ZipEntry;
 import java.util.zip.ZipFile;
+import java.util.zip.ZipInputStream;
 import java.util.zip.ZipOutputStream;
 
 /**
@@ -215,7 +219,31 @@ public class ModelSerializer {
      */
     public static MultiLayerNetwork restoreMultiLayerNetwork(@NonNull File file, boolean loadUpdater)
             throws IOException {
-        ZipFile zipFile = new ZipFile(file);
+        try(InputStream is = new BufferedInputStream(new FileInputStream(file))){
+            return restoreMultiLayerNetwork(is, loadUpdater);
+        }
+    }
+
+
+    /**
+     * Load a MultiLayerNetwork from InputStream from an input stream<br>
+     * Note: the input stream is read fully and closed by this method. Consequently, the input stream cannot be re-used.
+     *
+     * @param is the inputstream to load from
+     * @return the loaded multi layer network
+     * @throws IOException
+     * @see #restoreMultiLayerNetworkAndNormalizer(InputStream, boolean)
+     */
+    public static MultiLayerNetwork restoreMultiLayerNetwork(@NonNull InputStream is, boolean loadUpdater)
+            throws IOException {
+        return restoreMultiLayerNetworkHelper(is, loadUpdater).getFirst();
+    }
+
+    private static Pair<MultiLayerNetwork, Map<String,byte[]>> restoreMultiLayerNetworkHelper(@NonNull InputStream is, boolean loadUpdater)
+            throws IOException {
+        checkInputStream(is);
+
+        Map<String, byte[]> zipFile = loadZipData(is);
 
         boolean gotConfig = false;
         boolean gotCoefficients = false;
@@ -229,11 +257,11 @@ public class ModelSerializer {
         DataSetPreProcessor preProcessor = null;
 
 
-        ZipEntry config = zipFile.getEntry(CONFIGURATION_JSON);
+        byte[] config = zipFile.get(CONFIGURATION_JSON);
         if (config != null) {
             //restoring configuration
 
-            InputStream stream = zipFile.getInputStream(config);
+            InputStream stream = new ByteArrayInputStream(config);
             BufferedReader reader = new BufferedReader(new InputStreamReader(stream));
             String line = "";
             StringBuilder js = new StringBuilder();
@@ -248,25 +276,25 @@ public class ModelSerializer {
         }
 
 
-        ZipEntry coefficients = zipFile.getEntry(COEFFICIENTS_BIN);
+        byte[] coefficients = zipFile.get(COEFFICIENTS_BIN);
         if (coefficients != null ) {
-            if(coefficients.getSize() > 0) {
+            if(coefficients.length > 0) {
-                InputStream stream = zipFile.getInputStream(coefficients);
+                InputStream stream = new ByteArrayInputStream(coefficients);
                 DataInputStream dis = new DataInputStream(new BufferedInputStream(stream));
                 params = Nd4j.read(dis);
 
                 dis.close();
                 gotCoefficients = true;
             } else {
-                ZipEntry noParamsMarker = zipFile.getEntry(NO_PARAMS_MARKER);
+                byte[] noParamsMarker = zipFile.get(NO_PARAMS_MARKER);
                 gotCoefficients = (noParamsMarker != null);
             }
         }
 
         if (loadUpdater) {
-            ZipEntry updaterStateEntry = zipFile.getEntry(UPDATER_BIN);
+        	byte[] updaterStateEntry = zipFile.get(UPDATER_BIN);
             if (updaterStateEntry != null) {
-                InputStream stream = zipFile.getInputStream(updaterStateEntry);
+                InputStream stream = new ByteArrayInputStream(updaterStateEntry);
                 DataInputStream dis = new DataInputStream(new BufferedInputStream(stream));
                 updaterState = Nd4j.read(dis);
 
@@ -275,9 +303,9 @@ public class ModelSerializer {
             }
         }
 
-        ZipEntry prep = zipFile.getEntry(PREPROCESSOR_BIN);
+        byte[] prep = zipFile.get(PREPROCESSOR_BIN);
         if (prep != null) {
-            InputStream stream = zipFile.getInputStream(prep);
+            InputStream stream = new ByteArrayInputStream(prep);
             ObjectInputStream ois = new ObjectInputStream(stream);
 
             try {
@@ -290,7 +318,6 @@ public class ModelSerializer {
         }
 
 
-        zipFile.close();
 
         if (gotConfig && gotCoefficients) {
             MultiLayerConfiguration confFromJson;
@@ -322,37 +349,12 @@ public class ModelSerializer {
             if (gotUpdaterState && updaterState != null) {
                 network.getUpdater().setStateViewArray(network, updaterState, false);
             }
-            return network;
+            return new Pair<>(network, zipFile);
         } else
             throw new IllegalStateException("Model wasnt found within file: gotConfig: [" + gotConfig
                     + "], gotCoefficients: [" + gotCoefficients + "], gotUpdater: [" + gotUpdaterState + "]");
     }
 
-
-    /**
-     * Load a MultiLayerNetwork from InputStream from an input stream<br>
-     * Note: the input stream is read fully and closed by this method. Consequently, the input stream cannot be re-used.
-     *
-     * @param is the inputstream to load from
-     * @return the loaded multi layer network
-     * @throws IOException
-     * @see #restoreMultiLayerNetworkAndNormalizer(InputStream, boolean)
-     */
-    public static MultiLayerNetwork restoreMultiLayerNetwork(@NonNull InputStream is, boolean loadUpdater)
-            throws IOException {
-        checkInputStream(is);
-
-        File tmpFile = null;
-        try{
-            tmpFile = tempFileFromStream(is);
-            return restoreMultiLayerNetwork(tmpFile, loadUpdater);
-        } finally {
-            if(tmpFile != null){
-                tmpFile.delete();
-            }
-        }
-    }
-
     /**
      * Restore a multi layer network from an input stream<br>
      * * Note: the input stream is read fully and closed by this method. Consequently, the input stream cannot be re-used.
@@ -403,16 +405,12 @@ public class ModelSerializer {
     public static Pair<MultiLayerNetwork, Normalizer> restoreMultiLayerNetworkAndNormalizer(
             @NonNull InputStream is, boolean loadUpdater) throws IOException {
         checkInputStream(is);
+        is = new CloseShieldInputStream(is);
 
-        File tmpFile = null;
+        Pair<MultiLayerNetwork,Map<String,byte[]>> p = restoreMultiLayerNetworkHelper(is, loadUpdater);
-        try {
+        MultiLayerNetwork net = p.getFirst();
-            tmpFile = tempFileFromStream(is);
+        Normalizer norm = restoreNormalizerFromMap(p.getSecond());
-            return restoreMultiLayerNetworkAndNormalizer(tmpFile, loadUpdater);
+        return new Pair<>(net, norm);
-        } finally {
-            if (tmpFile != null) {
-                tmpFile.delete();
-            }
-        }
     }
 
     /**
@@ -425,9 +423,9 @@ public class ModelSerializer {
      */
     public static Pair<MultiLayerNetwork, Normalizer> restoreMultiLayerNetworkAndNormalizer(@NonNull File file, boolean loadUpdater)
             throws IOException {
-        MultiLayerNetwork net = restoreMultiLayerNetwork(file, loadUpdater);
+        try(InputStream is = new BufferedInputStream(new FileInputStream(file))){
-        Normalizer norm = restoreNormalizerFromFile(file);
+            return restoreMultiLayerNetworkAndNormalizer(is, loadUpdater);
-        return new Pair<>(net, norm);
+        }
     }
 
     /**
@@ -463,17 +461,126 @@ public class ModelSerializer {
      */
     public static ComputationGraph restoreComputationGraph(@NonNull InputStream is, boolean loadUpdater)
             throws IOException {
+        return restoreComputationGraphHelper(is, loadUpdater).getFirst();
+    }
+
+    private static Pair<ComputationGraph,Map<String,byte[]>> restoreComputationGraphHelper(@NonNull InputStream is, boolean loadUpdater)
+            throws IOException {
         checkInputStream(is);
 
-        File tmpFile = null;
+        Map<String, byte[]> files = loadZipData(is);
-        try{
+
-            tmpFile = tempFileFromStream(is);
+        boolean gotConfig = false;
-            return restoreComputationGraph(tmpFile, loadUpdater);
+        boolean gotCoefficients = false;
-        } finally {
+        boolean gotUpdaterState = false;
-            if(tmpFile != null){
+        boolean gotPreProcessor = false;
-                tmpFile.delete();
+
+        String json = "";
+        INDArray params = null;
+        INDArray updaterState = null;
+        DataSetPreProcessor preProcessor = null;
+
+
+        byte[] config = files.get(CONFIGURATION_JSON);
+        if (config != null) {
+            //restoring configuration
+
+            InputStream stream = new ByteArrayInputStream(config);
+            BufferedReader reader = new BufferedReader(new InputStreamReader(stream));
+            String line = "";
+            StringBuilder js = new StringBuilder();
+            while ((line = reader.readLine()) != null) {
+                js.append(line).append("\n");
+            }
+            json = js.toString();
+
+            reader.close();
+            stream.close();
+            gotConfig = true;
+        }
+
+
+        byte[] coefficients = files.get(COEFFICIENTS_BIN);
+        if (coefficients != null) {
+            if(coefficients.length > 0) {
+                InputStream stream = new ByteArrayInputStream(coefficients);
+                DataInputStream dis = new DataInputStream(stream);
+                params = Nd4j.read(dis);
+
+                dis.close();
+                gotCoefficients = true;
+            } else {
+                byte[] noParamsMarker = files.get(NO_PARAMS_MARKER);
+                gotCoefficients = (noParamsMarker != null);
             }
         }
+
+
+        if (loadUpdater) {
+            byte[] updaterStateEntry = files.get(UPDATER_BIN);
+            if (updaterStateEntry != null) {
+                InputStream stream = new ByteArrayInputStream(updaterStateEntry);
+                DataInputStream dis = new DataInputStream(stream);
+                updaterState = Nd4j.read(dis);
+
+                dis.close();
+                gotUpdaterState = true;
+            }
+        }
+
+        byte[] prep = files.get(PREPROCESSOR_BIN);
+        if (prep != null) {
+            InputStream stream = new ByteArrayInputStream(prep);
+            ObjectInputStream ois = new ObjectInputStream(stream);
+
+            try {
+                preProcessor = (DataSetPreProcessor) ois.readObject();
+            } catch (ClassNotFoundException e) {
+                throw new RuntimeException(e);
+            }
+
+            gotPreProcessor = true;
+        }
+
+
+        if (gotConfig && gotCoefficients) {
+            ComputationGraphConfiguration confFromJson;
+            try{
+                confFromJson = ComputationGraphConfiguration.fromJson(json);
+                if(confFromJson.getNetworkInputs() == null && (confFromJson.getVertices() == null || confFromJson.getVertices().size() == 0)){
+                    //May be deserialized correctly, but mostly with null fields
+                    throw new RuntimeException("Invalid JSON - not a ComputationGraphConfiguration");
+                }
+            } catch (Exception e){
+                if(e.getMessage() != null && e.getMessage().contains("registerLegacyCustomClassesForJSON")){
+                    throw e;
+                }
+                try{
+                    MultiLayerConfiguration.fromJson(json);
+                } catch (Exception e2){
+                    //Invalid, and not a compgraph
+                    throw new RuntimeException("Error deserializing JSON ComputationGraphConfiguration. Saved model JSON is" +
+                            " not a valid ComputationGraphConfiguration", e);
+                }
+                throw new RuntimeException("Error deserializing JSON ComputationGraphConfiguration. Saved model appears to be " +
+                        "a MultiLayerNetwork - use ModelSerializer.restoreMultiLayerNetwork instead");
+            }
+
+            //Handle legacy config - no network DataType in config, in beta3 or earlier
+            if(params != null)
+                confFromJson.setDataType(params.dataType());
+
+            ComputationGraph cg = new ComputationGraph(confFromJson);
+            cg.init(params, false);
+
+
+            if (gotUpdaterState && updaterState != null) {
+                cg.getUpdater().setStateViewArray(updaterState);
+            }
+            return new Pair<>(cg, files);
+        } else
+            throw new IllegalStateException("Model wasnt found within file: gotConfig: [" + gotConfig
+                    + "], gotCoefficients: [" + gotCoefficients + "], gotUpdater: [" + gotUpdaterState + "]");
     }
 
     /**
@@ -511,15 +618,11 @@ public class ModelSerializer {
             @NonNull InputStream is, boolean loadUpdater) throws IOException {
         checkInputStream(is);
 
-        File tmpFile = null;
+
-        try {
+        Pair<ComputationGraph,Map<String,byte[]>> p = restoreComputationGraphHelper(is, loadUpdater);
-            tmpFile = tempFileFromStream(is);
+        ComputationGraph net = p.getFirst();
-            return restoreComputationGraphAndNormalizer(tmpFile, loadUpdater);
+        Normalizer norm = restoreNormalizerFromMap(p.getSecond());
-        } finally {
+        return new Pair<>(net, norm);
-            if (tmpFile != null) {
-                tmpFile.delete();
-            }
-        }
     }
 
     /**
@@ -532,9 +635,7 @@ public class ModelSerializer {
      */
     public static Pair<ComputationGraph, Normalizer> restoreComputationGraphAndNormalizer(@NonNull File file, boolean loadUpdater)
             throws IOException {
-        ComputationGraph net = restoreComputationGraph(file, loadUpdater);
+    	return restoreComputationGraphAndNormalizer(new FileInputStream(file), loadUpdater);
-        Normalizer norm = restoreNormalizerFromFile(file);
-        return new Pair<>(net, norm);
     }
 
     /**
@@ -545,121 +646,7 @@ public class ModelSerializer {
      * @throws IOException
      */
     public static ComputationGraph restoreComputationGraph(@NonNull File file, boolean loadUpdater) throws IOException {
-        ZipFile zipFile = new ZipFile(file);
+    	return restoreComputationGraph(new FileInputStream(file), loadUpdater);
-
-        boolean gotConfig = false;
-        boolean gotCoefficients = false;
-        boolean gotUpdaterState = false;
-        boolean gotPreProcessor = false;
-
-        String json = "";
-        INDArray params = null;
-        INDArray updaterState = null;
-        DataSetPreProcessor preProcessor = null;
-
-
-        ZipEntry config = zipFile.getEntry(CONFIGURATION_JSON);
-        if (config != null) {
-            //restoring configuration
-
-            InputStream stream = zipFile.getInputStream(config);
-            BufferedReader reader = new BufferedReader(new InputStreamReader(stream));
-            String line = "";
-            StringBuilder js = new StringBuilder();
-            while ((line = reader.readLine()) != null) {
-                js.append(line).append("\n");
-            }
-            json = js.toString();
-
-            reader.close();
-            stream.close();
-            gotConfig = true;
-        }
-
-
-        ZipEntry coefficients = zipFile.getEntry(COEFFICIENTS_BIN);
-        if (coefficients != null) {
-            if(coefficients.getSize() > 0) {
-                InputStream stream = zipFile.getInputStream(coefficients);
-                DataInputStream dis = new DataInputStream(new BufferedInputStream(stream));
-                params = Nd4j.read(dis);
-
-                dis.close();
-                gotCoefficients = true;
-            } else {
-                ZipEntry noParamsMarker = zipFile.getEntry(NO_PARAMS_MARKER);
-                gotCoefficients = (noParamsMarker != null);
-            }
-        }
-
-
-        if (loadUpdater) {
-            ZipEntry updaterStateEntry = zipFile.getEntry(UPDATER_BIN);
-            if (updaterStateEntry != null) {
-                InputStream stream = zipFile.getInputStream(updaterStateEntry);
-                DataInputStream dis = new DataInputStream(new BufferedInputStream(stream));
-                updaterState = Nd4j.read(dis);
-
-                dis.close();
-                gotUpdaterState = true;
-            }
-        }
-
-        ZipEntry prep = zipFile.getEntry(PREPROCESSOR_BIN);
-        if (prep != null) {
-            InputStream stream = zipFile.getInputStream(prep);
-            ObjectInputStream ois = new ObjectInputStream(stream);
-
-            try {
-                preProcessor = (DataSetPreProcessor) ois.readObject();
-            } catch (ClassNotFoundException e) {
-                throw new RuntimeException(e);
-            }
-
-            gotPreProcessor = true;
-        }
-
-
-        zipFile.close();
-
-        if (gotConfig && gotCoefficients) {
-            ComputationGraphConfiguration confFromJson;
-            try{
-                confFromJson = ComputationGraphConfiguration.fromJson(json);
-                if(confFromJson.getNetworkInputs() == null && (confFromJson.getVertices() == null || confFromJson.getVertices().size() == 0)){
-                    //May be deserialized correctly, but mostly with null fields
-                    throw new RuntimeException("Invalid JSON - not a ComputationGraphConfiguration");
-                }
-            } catch (Exception e){
-                if(e.getMessage() != null && e.getMessage().contains("registerLegacyCustomClassesForJSON")){
-                    throw e;
-                }
-                try{
-                    MultiLayerConfiguration.fromJson(json);
-                } catch (Exception e2){
-                    //Invalid, and not a compgraph
-                    throw new RuntimeException("Error deserializing JSON ComputationGraphConfiguration. Saved model JSON is" +
-                            " not a valid ComputationGraphConfiguration", e);
-                }
-                throw new RuntimeException("Error deserializing JSON ComputationGraphConfiguration. Saved model appears to be " +
-                        "a MultiLayerNetwork - use ModelSerializer.restoreMultiLayerNetwork instead");
-            }
-
-            //Handle legacy config - no network DataType in config, in beta3 or earlier
-            if(params != null)
-                confFromJson.setDataType(params.dataType());
-
-            ComputationGraph cg = new ComputationGraph(confFromJson);
-            cg.init(params, false);
-
-
-            if (gotUpdaterState && updaterState != null) {
-                cg.getUpdater().setStateViewArray(updaterState);
-            }
-            return cg;
-        } else
-            throw new IllegalStateException("Model wasnt found within file: gotConfig: [" + gotConfig
-                    + "], gotCoefficients: [" + gotCoefficients + "], gotUpdater: [" + gotUpdaterState + "]");
     }
 
     /**
@@ -811,15 +798,16 @@ public class ModelSerializer {
                 }
 
                 //Add new object:
-                ZipEntry entry = new ZipEntry("objects/" + key);
-                writeFile.putNextEntry(entry);
 
                 try(ByteArrayOutputStream baos = new ByteArrayOutputStream(); ObjectOutputStream oos = new ObjectOutputStream(baos)){
                     oos.writeObject(o);
                     byte[] bytes = baos.toByteArray();
+                    ZipEntry entry = new ZipEntry("objects/" + key);
+                    entry.setSize(bytes.length);
+                    writeFile.putNextEntry(entry);
                     writeFile.write(bytes);
+                    writeFile.closeEntry();
                 }
-                writeFile.closeEntry();
 
                 writeFile.close();
                 zipFile.close();
@@ -904,18 +892,12 @@ public class ModelSerializer {
      * @param file
      * @return
      */
-    public static <T extends Normalizer> T restoreNormalizerFromFile(File file) {
+    public static <T extends Normalizer> T restoreNormalizerFromFile(File file) throws IOException {
-        try (ZipFile zipFile = new ZipFile(file)) {
+        try (InputStream is = new BufferedInputStream(new FileInputStream(file))) {
-            ZipEntry norm = zipFile.getEntry(NORMALIZER_BIN);
+        	return restoreNormalizerFromInputStream(is);
-
-            // checking for file existence
-            if (norm == null)
-                return null;
-
-            return NormalizerSerializer.getDefault().restore(zipFile.getInputStream(norm));
         } catch (Exception e) {
             log.warn("Error while restoring normalizer, trying to restore assuming deprecated format...");
-            DataNormalization restoredDeprecated = restoreNormalizerFromFileDeprecated(file);
+            DataNormalization restoredDeprecated = restoreNormalizerFromInputStreamDeprecated(new FileInputStream(file));
 
             log.warn("Recovered using deprecated method. Will now re-save the normalizer to fix this issue.");
             addNormalizerToModel(file, restoredDeprecated);
@@ -933,16 +915,22 @@ public class ModelSerializer {
      */
     public static <T extends Normalizer> T restoreNormalizerFromInputStream(InputStream is) throws IOException {
         checkInputStream(is);
+        Map<String, byte[]> files = loadZipData(is);
+        return restoreNormalizerFromMap(files);
+    }
 
-        File tmpFile = null;
+    private static <T extends Normalizer> T restoreNormalizerFromMap(Map<String, byte[]> files) throws IOException {
+        byte[] norm = files.get(NORMALIZER_BIN);
+
+        // checking for file existence
+        if (norm == null)
+            return null;
         try {
-            tmpFile = tempFileFromStream(is);
+        	return NormalizerSerializer.getDefault().restore(new ByteArrayInputStream(norm));
-            return restoreNormalizerFromFile(tmpFile);
-        } finally {
-            if(tmpFile != null){
-                tmpFile.delete();
-            }
         }
+        catch (Exception e) {
+        	throw new IOException("Error loading normalizer", e);
+		}
     }
 
     /**
@@ -950,20 +938,10 @@ public class ModelSerializer {
      *
      * This method restores normalizer from a given persisted model file serialized with Java object serialization
      *
-     * @param file
-     * @return
      */
-    private static DataNormalization restoreNormalizerFromFileDeprecated(File file) {
+    private static DataNormalization restoreNormalizerFromInputStreamDeprecated(InputStream stream) {
-        try (ZipFile zipFile = new ZipFile(file)) {
+    	try {
-            ZipEntry norm = zipFile.getEntry(NORMALIZER_BIN);
-
-            // checking for file existence
-            if (norm == null)
-                return null;
-
-            InputStream stream = zipFile.getInputStream(norm);
             ObjectInputStream ois = new ObjectInputStream(stream);
-
             try {
                 DataNormalization normalizer = (DataNormalization) ois.readObject();
                 return normalizer;
@@ -977,8 +955,6 @@ public class ModelSerializer {
 
 
     private static void checkInputStream(InputStream inputStream) throws IOException {
-
-        /*
         //available method can return 0 in some cases: https://github.com/deeplearning4j/deeplearning4j/issues/4887
         int available;
         try{
@@ -993,34 +969,32 @@ public class ModelSerializer {
             throw new IOException("Cannot read from stream: stream may have been closed or is attempting to be read from" +
                     "multiple times?");
         }
-        */
     }
 
-    private static void checkTempFileFromInputStream(File f) throws IOException {
+    private static Map<String, byte[]> loadZipData(InputStream is) throws IOException {
-        if (f.length() <= 0) {
+    	Map<String, byte[]> result = new HashMap<>();
-            throw new IOException("Error reading from input stream: temporary file is empty after copying entire stream." +
+		try (final ZipInputStream zis = new ZipInputStream(is)) {
-                    " Stream may have been closed before reading, is attempting to be used multiple times, or does not" +
+			while (true) {
-                    " point to a model file?");
+				final ZipEntry zipEntry = zis.getNextEntry();
-        }
+				if (zipEntry == null)
+					break;
+				if(zipEntry.isDirectory() || zipEntry.getSize() > Integer.MAX_VALUE)
+					throw new IllegalArgumentException();
+
+				final int size = (int) (zipEntry.getSize());
+				final byte[] data;
+				if (size >= 0) { // known size
+					data = IOUtils.readFully(zis, size);
+				}
+				else { // unknown size
+					final ByteArrayOutputStream bout = new ByteArrayOutputStream();
+					IOUtils.copy(zis, bout);
+					data = bout.toByteArray();
+				}
+                                result.put(zipEntry.getName(), data);
+			}
+		}
+		return result;
     }
 
-    private static File tempFileFromStream(InputStream is) throws IOException{
-        checkInputStream(is);
-        String p = System.getProperty(DL4JSystemProperties.DL4J_TEMP_DIR_PROPERTY);
-        File tmpFile = DL4JFileUtils.createTempFile("dl4jModelSerializer", "bin");
-        try {
-            tmpFile.deleteOnExit();
-            BufferedOutputStream bufferedOutputStream = new BufferedOutputStream(new FileOutputStream(tmpFile));
-            IOUtils.copy(is, bufferedOutputStream);
-            bufferedOutputStream.flush();
-            IOUtils.closeQuietly(bufferedOutputStream);
-            checkTempFileFromInputStream(tmpFile);
-            return tmpFile;
-        } catch (IOException e){
-            if(tmpFile != null){
-                tmpFile.delete();
-            }
-            throw e;
-        }
-    }
 }