fix java static check

mindspore/lite/java/java/app/src/main/java/com/mindspore/lite/LiteSession.java

@@ -59,19 +59,19 @@ public class LiteSession {
     public List<MSTensor> getInputs() {
         List<Long> ret = this.getInputs(this.sessionPtr);
         ArrayList<MSTensor> tensors = new ArrayList<MSTensor>();
-        for (Long ms_tensor_addr : ret) {
-            MSTensor msTensor = new MSTensor(ms_tensor_addr);
+        for (Long msTensorAddr : ret) {
+            MSTensor msTensor = new MSTensor(msTensorAddr);
             tensors.add(msTensor);
         }
         return tensors;
     }
 
     public MSTensor getInputsByTensorName(String tensorName) {
-        Long tensor_addr = this.getInputsByTensorName(this.sessionPtr, tensorName);
-        if(tensor_addr == null){
+        Long tensorAddr = this.getInputsByTensorName(this.sessionPtr, tensorName);
+        if (tensorAddr == null) {
             return null;
         }
-        MSTensor msTensor = new MSTensor(tensor_addr);
+        MSTensor msTensor = new MSTensor(tensorAddr);
         return msTensor;
     }
 
@@ -102,11 +102,11 @@ public class LiteSession {
     }
 
     public MSTensor getOutputByTensorName(String tensorName) {
-        Long tensor_addr = getOutputByTensorName(this.sessionPtr, tensorName);
-        if(tensor_addr == null){
+        Long tensorAddr = getOutputByTensorName(this.sessionPtr, tensorName);
+        if (tensorAddr == null) {
             return null;
         }
-        return new MSTensor(tensor_addr);
+        return new MSTensor(tensorAddr);
     }
 
     public void free() {
@@ -115,11 +115,11 @@ public class LiteSession {
     }
 
     public boolean resize(List<MSTensor> inputs, int[][] dims) {
-        long[] inputs_array = new long[inputs.size()];
+        long[] inputsArray = new long[inputs.size()];
         for (int i = 0; i < inputs.size(); i++) {
-            inputs_array[i] = inputs.get(i).getMSTensorPtr();
+            inputsArray[i] = inputs.get(i).getMSTensorPtr();
         }
-        return this.resize(this.sessionPtr, inputs_array, dims);
+        return this.resize(this.sessionPtr, inputsArray, dims);
     }
 
     private native long createSession(long msConfigPtr);

mindspore/lite/java/java/app/src/main/java/com/mindspore/lite/config/MSConfig.java

@@ -29,7 +29,7 @@ public class MSConfig {
     }
 
     public boolean init(int deviceType, int threadNum, int cpuBindMode) {
-        this.msConfigPtr = createMSConfig(deviceType, threadNum, cpuBindMode ,false);
+        this.msConfigPtr = createMSConfig(deviceType, threadNum, cpuBindMode, false);
         return this.msConfigPtr != 0;
     }
 

mindspore/lite/src/runtime/kernel/npu/cast_npu.cc

@@ -50,4 +50,5 @@ CastNPUKernel::~CastNPUKernel() {
 }
 
 REG_KERNEL(kNPU, kNumberTypeFloat32, PrimitiveType_Cast, NPUKernelCreator<CastNPUKernel>)
+REG_KERNEL(kNPU, kNumberTypeInt32, PrimitiveType_Cast, NPUKernelCreator<CastNPUKernel>)
 }  // namespace mindspore::kernel

mindspore/lite/src/runtime/kernel/npu/gather_npu.cc

@@ -53,5 +53,6 @@ GatherNPUKernel::~GatherNPUKernel() {
     op_ = nullptr;
   }
 }
+// NPU input index 0 datatype not support: 3(int32).
 REG_KERNEL(kNPU, kNumberTypeFloat32, PrimitiveType_Gather, NPUKernelCreator<GatherNPUKernel>)
 }  // namespace mindspore::kernel

mindspore/lite/src/runtime/kernel/npu/shape_npu.cc

@@ -24,7 +24,7 @@ using mindspore::schema::PrimitiveType_Shape;
 namespace mindspore::kernel {
 int ShapeNPUKernel::IsSupport(const std::vector<lite::Tensor *> &inputs, const std::vector<lite::Tensor *> &outputs,
                               OpParameter *opParameter) {
-  return RET_OK;
+  return RET_ERROR;
 }
 
 int ShapeNPUKernel::SetNPUInputs(const std::vector<lite::Tensor *> &inputs, const std::vector<lite::Tensor *> &outputs,

mindspore/lite/src/runtime/kernel/npu/strided_slice_npu.cc

@@ -27,9 +27,9 @@ int StridedSliceNPUKernel::IsSupport(const std::vector<lite::Tensor *> &inputs,
   // Only onnx StridedSlice has 5 inputs, of which the 4th input is axes and the 5th input is strides.
   if (inputs.size() == 5) {
     vector<int> axes;
-    size_t size = inputs[4]->shape()[0];
+    size_t size = inputs[3]->shape()[0];
     axes.resize(size);
-    memcpy(axes.data(), inputs[4]->data_c(), sizeof(int) * size);
+    memcpy(axes.data(), inputs[3]->data_c(), sizeof(int) * size);
     for (int i = 0; i < axes.size(); ++i) {
       if (i != axes[i]) {
         MS_LOG(ERROR) << "Does not support setting axis, so the axis must be continuous.";
@@ -77,4 +77,5 @@ StridedSliceNPUKernel::~StridedSliceNPUKernel() {
 }
 
 REG_KERNEL(kNPU, kNumberTypeFloat32, PrimitiveType_StridedSlice, NPUKernelCreator<StridedSliceNPUKernel>)
+REG_KERNEL(kNPU, kNumberTypeInt32, PrimitiveType_StridedSlice, NPUKernelCreator<StridedSliceNPUKernel>)
 }  // namespace mindspore::kernel