add cxx java api

mindspore/lite/java/src/main/java/com/mindspore/Graph.java

@@ -0,0 +1,64 @@
+/*
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed 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 com.mindspore;
+
+public class Graph {
+    static {
+        System.loadLibrary("mindspore-lite-jni");
+    }
+
+    private long graphPtr;
+
+    /**
+     * Construct function.
+     */
+    public Graph() {
+        this.graphPtr = 0;
+    }
+
+    /**
+     * Load file.
+     *
+     * @param file model file.
+     * @return load status.
+     */
+    public boolean Load(String file) {
+        this.graphPtr = load(file);
+        return this.graphPtr != 0L;
+    }
+
+    /**
+     * Get graph pointer.
+     *
+     * @return graph pointer.
+     */
+    public long getGraphPtr() {
+        return this.graphPtr;
+    }
+
+    /**
+     * Fre graph pointer.
+     */
+    public void free() {
+        this.free(graphPtr);
+        graphPtr = 0;
+    }
+
+    private native long load(String file);
+
+    private native boolean free(long graphPtr);
+}

mindspore/lite/java/src/main/java/com/mindspore/MSTensor.java

@@ -0,0 +1,192 @@
+/*
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed 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 com.mindspore;
+
+import java.nio.ByteBuffer;
+
+public class MSTensor {
+    static {
+        System.loadLibrary("mindspore-lite-jni");
+    }
+    private long tensorPtr;
+
+    /**
+     * MSTensor construct function.
+     */
+    public MSTensor() {
+        this.tensorPtr = 0;
+    }
+
+    /**
+     * MSTensor construct function.
+     *
+     * @param tensorPtr tensor pointer.
+     */
+    public MSTensor(long tensorPtr) {
+        this.tensorPtr = tensorPtr;
+    }
+
+    /**
+     * MSTensor construct function.
+     *
+     * @param tensorName tensor name
+     * @param buffer     tensor buffer
+     */
+    public MSTensor(String tensorName, ByteBuffer buffer) {
+        this.tensorPtr = createTensor(tensorName, buffer);
+    }
+
+    /**
+     * Get the shape of the MindSpore MSTensor.
+     *
+     * @return A array of int as the shape of the MindSpore MSTensor.
+     */
+    public int[] getShape() {
+        return this.getShape(this.tensorPtr);
+    }
+
+    /**
+     * DataType is defined in com.mindspore.DataType.
+     *
+     * @return The MindSpore data type of the MindSpore MSTensor class.
+     */
+    public int getDataType() {
+        return this.getDataType(this.tensorPtr);
+    }
+
+    /**
+     * Get output data of MSTensor, the data type is byte.
+     *
+     * @return The byte array containing all MSTensor output data.
+     */
+    public byte[] getByteData() {
+        return this.getByteData(this.tensorPtr);
+    }
+
+    /**
+     * Get output data of MSTensor, the data type is float.
+     *
+     * @return The float array containing all MSTensor output data.
+     */
+    public float[] getFloatData() {
+        return this.getFloatData(this.tensorPtr);
+    }
+
+    /**
+     * Get output data of MSTensor, the data type is int.
+     *
+     * @return The int array containing all MSTensor output data.
+     */
+    public int[] getIntData() {
+        return this.getIntData(this.tensorPtr);
+    }
+
+    /**
+     * Get output data of MSTensor, the data type is long.
+     *
+     * @return The long array containing all MSTensor output data.
+     */
+    public long[] getLongData() {
+        return this.getLongData(this.tensorPtr);
+    }
+
+    /**
+     * Set the input data of MSTensor.
+     *
+     * @param data Input data of byte[] type.
+     * @return whether set data success.
+     */
+    public boolean setData(byte[] data) {
+        return this.setData(this.tensorPtr, data, data.length);
+    }
+
+    /**
+     * Set the input data of MSTensor.
+     *
+     * @param data data Input data of ByteBuffer type
+     * @return whether set data success.
+     */
+    public boolean setData(ByteBuffer data) {
+        return this.setByteBufferData(this.tensorPtr, data);
+    }
+
+    /**
+     * Get the size of the data in MSTensor in bytes.
+     *
+     * @return The size of the data in MSTensor in bytes.
+     */
+    public long size() {
+        return this.size(this.tensorPtr);
+    }
+
+    /**
+     * Get the number of elements in MSTensor.
+     *
+     * @return The number of elements in MSTensor.
+     */
+    public int elementsNum() {
+        return this.elementsNum(this.tensorPtr);
+    }
+
+    /**
+     * Free all temporary memory in MindSpore MSTensor.
+     */
+    public void free() {
+        this.free(this.tensorPtr);
+        this.tensorPtr = 0;
+    }
+
+    /**
+     * @return Get tensor name
+     */
+    public String tensorName() {
+        return this.tensorName(this.tensorPtr);
+    }
+
+    /**
+     * @return MSTensor pointer
+     */
+    public long getMSTensorPtr() {
+        return tensorPtr;
+    }
+
+    private native long createTensor(String tensorName, ByteBuffer buffer);
+
+    private native int[] getShape(long tensorPtr);
+
+    private native int getDataType(long tensorPtr);
+
+    private native byte[] getByteData(long tensorPtr);
+
+    private native long[] getLongData(long tensorPtr);
+
+    private native int[] getIntData(long tensorPtr);
+
+    private native float[] getFloatData(long tensorPtr);
+
+    private native boolean setData(long tensorPtr, byte[] data, long dataLen);
+
+    private native boolean setByteBufferData(long tensorPtr, ByteBuffer buffer);
+
+    private native long size(long tensorPtr);
+
+    private native int elementsNum(long tensorPtr);
+
+    private native void free(long tensorPtr);
+
+    private native String tensorName(long tensorPtr);
+}

mindspore/lite/java/src/main/java/com/mindspore/Model.java

@@ -0,0 +1,277 @@
+/*
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed 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 com.mindspore;
+
+import com.mindspore.config.ModelType;
+import com.mindspore.config.MSContext;
+import com.mindspore.config.TrainCfg;
+
+import java.nio.MappedByteBuffer;
+import java.util.ArrayList;
+import java.util.List;
+
+public class Model {
+    static {
+        System.loadLibrary("mindspore-lite-jni");
+    }
+
+    private long modelPtr = 0;
+
+    /**
+     * Construct function.
+     */
+    public Model() {
+        this.modelPtr = 0;
+    }
+
+    /**
+     * Build model by graph.
+     *
+     * @param graph   graph contains the buffer.
+     * @param context model build context.
+     * @param cfg     model build train config.used for train.
+     * @return build status.
+     */
+    public boolean build(Graph graph, MSContext context, TrainCfg cfg) {
+        modelPtr = this.buildByGraph(graph.getGraphPtr(), context.getMSContextPtr(), cfg.getTrainCfgPtr());
+        return modelPtr != 0;
+    }
+
+    /**
+     * Build model.
+     *
+     * @param buffer    model buffer.
+     * @param modelType model type.
+     * @param context   model build context.
+     * @param dec_key   define the key used to decrypt the ciphertext model. The key length is 16, 24, or 32.
+     * @param dec_mode  define the decryption mode. Options: AES-GCM, AES-CBC.
+     * @return model build status.
+     */
+    public boolean build(final MappedByteBuffer buffer, int modelType, MSContext context, char[] dec_key,
+                         String dec_mode) {
+        modelPtr = this.buildByBuffer(buffer, modelType, context.getMSContextPtr(), dec_key, dec_mode);
+        return modelPtr != 0;
+    }
+
+    /**
+     * Build model.
+     *
+     * @param buffer    model buffer.
+     * @param modelType model type.
+     * @param context   model build context.
+     * @return model build status.
+     */
+    public boolean build(final MappedByteBuffer buffer, int modelType, MSContext context) {
+        modelPtr = this.buildByBuffer(buffer, modelType, context.getMSContextPtr(), null, "");
+        return modelPtr != 0;
+    }
+
+
+    /**
+     * Build model.
+     *
+     * @param modelPath model path.
+     * @param modelType model type.
+     * @param context   model build context.
+     * @param dec_key   define the key used to decrypt the ciphertext model. The key length is 16, 24, or 32.
+     * @param dec_mode  define the decryption mode. Options: AES-GCM, AES-CBC.
+     * @return model build status.
+     */
+    public boolean build(String modelPath, int modelType, MSContext context, char[] dec_key, String dec_mode) {
+        modelPtr = this.buildByPath(modelPath, modelType, context.getMSContextPtr(), dec_key, dec_mode);
+        return modelPtr != 0;
+    }
+
+    /**
+     * Build model.
+     *
+     * @param modelPath model path.
+     * @param modelType model type.
+     * @param context   model build context.
+     * @return build status.
+     */
+    public boolean build(String modelPath, int modelType, MSContext context) {
+        modelPtr = this.buildByPath(modelPath, modelType, context.getMSContextPtr(), null, "");
+        return modelPtr != 0;
+    }
+
+    /**
+     * Resize inputs shape.
+     *
+     * @param inputs Model inputs.
+     * @param dims   Define the new inputs shape.
+     * @return Whether the resize is successful.
+     */
+    public boolean resize(List<MSTensor> inputs, int[][] dims) {
+        long[] inputsArray = new long[inputs.size()];
+        for (int i = 0; i < inputs.size(); i++) {
+            inputsArray[i] = inputs.get(i).getMSTensorPtr();
+        }
+        return this.resize(this.modelPtr, inputsArray, dims);
+    }
+
+    /**
+     * Get model inputs tensor.
+     *
+     * @return input tensors.
+     */
+    public List<MSTensor> getInputs() {
+        List<Long> ret = this.getInputs(this.modelPtr);
+        List<MSTensor> tensors = new ArrayList<>();
+        for (Long msTensorAddr : ret) {
+            MSTensor msTensor = new MSTensor(msTensorAddr);
+            tensors.add(msTensor);
+        }
+        return tensors;
+    }
+
+    /**
+     * Get model outputs.
+     *
+     * @return model outputs tensor.
+     */
+    public List<MSTensor> getOutputs() {
+        List<Long> ret = this.getOutputs(this.modelPtr);
+        List<MSTensor> tensors = new ArrayList<>();
+        for (Long msTensorAddr : ret) {
+            MSTensor msTensor = new MSTensor(msTensorAddr);
+            tensors.add(msTensor);
+        }
+        return tensors;
+    }
+
+    /**
+     * Get input tensor by tensor name.
+     *
+     * @param tensorName name.
+     * @return input tensor.
+     */
+    public MSTensor getInputByTensorName(String tensorName) {
+        long tensorAddr = this.getInputByTensorName(this.modelPtr, tensorName);
+        return new MSTensor(tensorAddr);
+    }
+
+    /**
+     * Get output tensor by tensor name.
+     *
+     * @param tensorName output tensor name
+     * @return output tensor
+     */
+    public MSTensor getOutputByTensorName(String tensorName) {
+        long tensorAddr = this.getOutputByTensorName(this.modelPtr, tensorName);
+        return new MSTensor(tensorAddr);
+    }
+
+    /**
+     * Export the model.
+     *
+     * @param fileName          Name Model file name.
+     * @param quantizationType  The quant type.0,no_quant,1,weight_quant,2,full_quant.
+     * @param isOnlyExportInfer if export only inferece.
+     * @param outputTensorNames tensor name used for export inference graph.
+     * @return Whether the export is successful.
+     */
+    public boolean export(String fileName, int quantizationType, boolean isOnlyExportInfer,
+                          List<String> outputTensorNames) {
+        return export(modelPtr, fileName, quantizationType, isOnlyExportInfer, outputTensorNames);
+    }
+
+    /**
+     * Get the FeatureMap.
+     *
+     * @return FeaturesMap Tensor list.
+     */
+    public List<MSTensor> getFeatureMaps() {
+        List<Long> ret = this.getFeatureMaps(this.modelPtr);
+        ArrayList<MSTensor> tensors = new ArrayList<>();
+        for (Long msTensorAddr : ret) {
+            MSTensor msTensor = new MSTensor(msTensorAddr);
+            tensors.add(msTensor);
+        }
+        return tensors;
+    }
+
+    /**
+     * Update model Features.
+     *
+     * @param features new FeatureMap Tensor List.
+     * @return Whether the model features is successfully update.
+     */
+    public boolean updateFeatureMaps(List<MSTensor> features) {
+        long[] inputsArray = new long[features.size()];
+        for (int i = 0; i < features.size(); i++) {
+            inputsArray[i] = features.get(i).getMSTensorPtr();
+        }
+        return this.updateFeatureMaps(modelPtr, inputsArray);
+    }
+
+    /**
+     * Set model work train mode
+     *
+     * @param isTrain is train mode.true work train mode.
+     * @return set status.
+     */
+    public boolean setTrainMode(boolean isTrain) {
+        return this.setTrainMode(modelPtr, isTrain);
+    }
+
+    /**
+     * Get train mode
+     *
+     * @return train mode.
+     */
+    public boolean getTrainMode() {
+        return this.getTrainMode(modelPtr);
+    }
+
+    /**
+     * Free model
+     */
+    public void free() {
+        this.free(modelPtr);
+    }
+
+    private native void free(long modelPtr);
+
+    private native long buildByGraph(long graphPtr, long contextPtr, long cfgPtr);
+
+    private native long buildByPath(String modelPath, int modelType, long contextPtr, char[] dec_key, String dec_mod);
+
+    private native long buildByBuffer(MappedByteBuffer buffer, int modelType, long contextPtr, char[] dec_key,
+                                      String dec_mod);
+
+    private native List<Long> getInputs(long modelPtr);
+
+    private native long getInputByTensorName(long modelPtr, String tensorName);
+
+    private native List<Long> getOutputs(long modelPtr);
+
+    private native long getOutputByTensorName(long modelPtr, String tensorName);
+
+    private native boolean setTrainMode(long modelPtr, boolean isTrain);
+
+    private native boolean getTrainMode(long modelPtr);
+
+    private native boolean resize(long modelPtr, long[] inputs, int[][] dims);
+
+    private native boolean export(long modelPtr, String fileName, int quantizationType, boolean isOnlyExportInfer,
+                                  List<String> outputTensorNames);
+
+    private native List<Long> getFeatureMaps(long modelPtr);
+
+    private native boolean updateFeatureMaps(long modelPtr, long[] newFeatures);
+}

mindspore/lite/java/src/main/java/com/mindspore/config/CpuBindMode.java

@@ -0,0 +1,28 @@
+/*
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed 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 com.mindspore.config;
+
+/**
+ * Define Cpu core bind mode
+ *
+ * @since v1.0
+ */
+public class CpuBindMode {
+    public static final int MID_CPU = 2;
+    public static final int HIGHER_CPU = 1;
+    public static final int NO_BIND = 0;
+}

mindspore/lite/java/src/main/java/com/mindspore/config/DataType.java

@@ -0,0 +1,39 @@
+/*
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed 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 com.mindspore.config;
+
+/**
+ * Define tensor data type.
+ *
+ * @since v1.0
+ */
+public class DataType {
+    public static final int kNumberTypeBool = 30;
+    public static final int kNumberTypeInt = 31;
+    public static final int kNumberTypeInt8 = 32;
+    public static final int kNumberTypeInt16 = 33;
+    public static final int kNumberTypeInt32 = 34;
+    public static final int kNumberTypeInt64 = 35;
+    public static final int kNumberTypeUInt = 36;
+    public static final int kNumberTypeUInt8 = 37;
+    public static final int kNumberTypeUInt16 = 38;
+    public static final int kNumberTypeUint32 = 39;
+    public static final int kNumberTypeUInt64 = 40;
+    public static final int kNumberTypeFloat = 41;
+    public static final int kNumberTypeFloat16 = 42;
+    public static final int kNumberTypeFloat32 = 43;
+    public static final int kNumberTypeFloat64 = 44;
+}

mindspore/lite/java/src/main/java/com/mindspore/config/DeviceType.java

@@ -0,0 +1,27 @@
+/*
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed 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 com.mindspore.config;
+
+/**
+ * define device type
+ *
+ * @since v1.0
+ */
+public class DeviceType {
+    public static final int DT_CPU = 0;
+    public static final int DT_GPU = 1;
+    public static final int DT_NPU = 2;
+}

mindspore/lite/java/src/main/java/com/mindspore/config/MSContext.java

@@ -0,0 +1,103 @@
+/*
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed 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 com.mindspore.config;
+
+public class MSContext {
+    static {
+        System.loadLibrary("mindspore-lite-jni");
+    }
+
+    private long msContextPtr;
+
+    /**
+     * Construct function.
+     */
+    public MSContext() {
+        this.msContextPtr = 0;
+    }
+
+    /**
+     * Add device info to context.
+     *
+     * @param deviceType support cpu,npu and gpu.
+     * @param isEnableFloat16  whether to use float16 operator for priority.
+     * @param npuFreq npu frequency used for npu device.
+     * @return add status.
+     */
+    public boolean addDeviceInfo(int deviceType, boolean isEnableFloat16, int npuFreq) {
+        return addDeviceInfo(msContextPtr, deviceType, isEnableFloat16, npuFreq);
+    }
+
+    /**
+     * Add device info to context.
+     *
+     * @param deviceType support cpu,npu and gpu.
+     * @param isEnableFloat16  whether to use float16 operator for priority.
+     * @return add status.
+     */
+    public boolean addDeviceInfo(int deviceType, boolean isEnableFloat16) {
+        return addDeviceInfo(msContextPtr, deviceType, isEnableFloat16, 3);
+    }
+
+    /**
+     * Init Context.
+     *
+     * @param threadNum thread nums.
+     * @param cpuBindMode support bind high,mid cpu.0,no bind.1,bind mid cpu.2. bind high cpu.
+     * @return init status.
+     */
+    public boolean init(int threadNum, int cpuBindMode) {
+        this.msContextPtr = createMSContext(threadNum, cpuBindMode, false);
+        return this.msContextPtr != 0;
+    }
+
+    /**
+     * Init Context.
+     *
+     * @param threadNum thread nums.
+     * @param cpuBindMode support bind high,mid cpu.0,no bind.1,bind mid cpu.2. bind high cpu.
+     * @param isEnableParallel enable parallel in multi devices.
+     * @return init status.
+     */
+    public boolean init(int threadNum, int cpuBindMode, boolean isEnableParallel) {
+        this.msContextPtr = createMSContext(threadNum, cpuBindMode, isEnableParallel);
+        return this.msContextPtr != 0;
+    }
+
+    /**
+     * Free context.
+     */
+    public void free() {
+        this.free(this.msContextPtr);
+        this.msContextPtr = 0;
+    }
+
+    /**
+     * Get context pointer.
+     *
+     * @return context pointer.
+     */
+    public long getMSContextPtr() {
+        return msContextPtr;
+    }
+
+    private native long createMSContext(int threadNum, int cpuBindMode, boolean enableParallel);
+
+    private native boolean addDeviceInfo(long msContextPtr, int deviceType, boolean isEnableFloat16, int npuFrequency);
+
+    private native void free(long msContextPtr);
+}

mindspore/lite/java/src/main/java/com/mindspore/config/ModelType.java

@@ -0,0 +1,29 @@
+/*
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed 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 com.mindspore.config;
+
+/**
+ * define model type
+ *
+ * @since v1.0
+ */
+public class ModelType {
+    public static final int MT_MINDIR = 0;
+    public static final int MT_AIR = 1;
+    public static final int MT_OM = 2;
+    public static final int MT_ONNX = 3;
+    public static final int MT_MINDIR_OPT = 4;
+}

mindspore/lite/java/src/main/java/com/mindspore/config/TrainCfg.java

@@ -0,0 +1,89 @@
+/*
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed 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 com.mindspore.config;
+
+public class TrainCfg {
+    static {
+        System.loadLibrary("mindspore-lite-train-jni");
+    }
+
+    private long trainCfgPtr;
+
+    /**
+     *  Construct function.
+     */
+    public TrainCfg() {
+        this.trainCfgPtr = 0;
+    }
+
+    /**
+     * Init train config.
+     *
+     * @return init status.
+     */
+    public boolean init() {
+        this.trainCfgPtr = createTrainCfg(null, 0, false);
+        return this.trainCfgPtr != 0;
+    }
+
+    /**
+     * Init train config specified loss name.
+     *
+     * @param loss_name loss name used for split inference and train part.
+     * @return init status.
+     */
+    public boolean init(String loss_name) {
+        this.trainCfgPtr = createTrainCfg(loss_name, 0, false);
+        return this.trainCfgPtr != 0;
+    }
+
+    /**
+     * Free train config.
+     */
+    public void free() {
+        this.free(this.trainCfgPtr);
+        this.trainCfgPtr = 0;
+    }
+
+    /**
+     * Add mix precision config to train config.
+     *
+     * @param dynamicLossScale if dynamic or fix loss scale factor.
+     * @param lossScale loss scale factor.
+     * @param thresholdIterNum a threshold for modifying loss scale when dynamic loss scale is enabled.
+     * @return add status.
+     */
+    public boolean addMixPrecisionCfg(boolean dynamicLossScale, float lossScale, int thresholdIterNum) {
+        return addMixPrecisionCfg(trainCfgPtr, dynamicLossScale, lossScale, thresholdIterNum);
+    }
+
+    /**
+     * Get train config pointer.
+     *
+     * @return train config pointer.
+     */
+    public long getTrainCfgPtr() {
+        return trainCfgPtr;
+    }
+
+    private native long createTrainCfg(String lossName, int optimizationLevel, boolean accmulateGrads);
+
+    private native boolean addMixPrecisionCfg(long trainCfgPtr, boolean dynamicLossScale, float lossScale,
+                                              int thresholdIterNum);
+
+    private native void free(long trainCfgPtr);
+}

mindspore/lite/java/src/main/java/com/mindspore/config/Version.java

@@ -0,0 +1,35 @@
+/*
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed 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 com.mindspore.config;
+
+/**
+ * Define mindspore version info.
+ *
+ * @since v1.0
+ */
+public class Version {
+    static {
+        System.loadLibrary("mindspore-lite-jni");
+    }
+
+    /**
+     * Get MindSpore Lite version info.
+     *
+     * @return MindSpore Lite version info.
+     */
+    public static native String version();
+}