!9499 [MS][LITE][GPU]check op tensor size

From: @chenzupeng
Reviewed-by: @ddwsky,@zhanghaibo5
Signed-off-by: @zhanghaibo5

mindspore/lite/src/runtime/kernel/opencl/kernel/activation.cc

@@ -43,6 +43,10 @@ using mindspore::schema::PrimitiveType_Activation;
 namespace mindspore::kernel {
 
 int ActivationOpenClKernel::Init() {
+  if (in_tensors_.size() != 1 || out_tensors_.size() != 1) {
+    MS_LOG(ERROR) << "Invalid input size: " << in_tensors_.size() << ", output size: " << out_tensors_.size();
+    return RET_ERROR;
+  }
   std::map<int, std::string> kernel_names{
     {ActivationType_LEAKY_RELU, "LeakyRelu"}, {ActivationType_RELU, "Relu"}, {ActivationType_SIGMOID, "Sigmoid"},
     {ActivationType_RELU6, "Relu6"},          {ActivationType_TANH, "Tanh"}, {ActivationType_SWISH, "Swish"},

mindspore/lite/src/runtime/kernel/opencl/kernel/arithmetic.cc

@@ -165,6 +165,10 @@ int ArithmeticOpenCLKernel::SetArgs() {
 }
 
 int ArithmeticOpenCLKernel::Init() {
+  if (in_tensors_.size() != 2 || out_tensors_.size() != 1) {
+    MS_LOG(ERROR) << "Invalid input size: " << in_tensors_.size() << ", output size: " << out_tensors_.size();
+    return RET_ERROR;
+  }
   std::string kernel_name;
   auto *arithmetic_parameter = reinterpret_cast<const ArithmeticParameter *>(op_parameter_);
 

mindspore/lite/src/runtime/kernel/opencl/kernel/convolution.cc

@@ -39,6 +39,10 @@ constexpr size_t CI_TILE = C4NUM;
 constexpr size_t CO_TILE = C4NUM;
 
 int ConvolutionOpenCLKernel::Init() {
+  if ((in_tensors_.size() != 2 && in_tensors_.size() != 3) || out_tensors_.size() != 1) {
+    MS_LOG(ERROR) << "Invalid input size: " << in_tensors_.size() << ", output size: " << out_tensors_.size();
+    return RET_ERROR;
+  }
   use_fp16_ = ocl_runtime_->GetFp16Enable();
   sizeof_FLT_ = use_fp16_ ? sizeof(float16_t) : sizeof(float);
 

mindspore/lite/src/runtime/kernel/opencl/kernel/depthwise_conv2d.cc

@@ -42,6 +42,10 @@ using mindspore::schema::PrimitiveType_DepthwiseConv2D;
 namespace mindspore::kernel {
 
 int DepthwiseConv2dOpenCLKernel::Init() {
+  if ((in_tensors_.size() != 2 && in_tensors_.size() != 3) || out_tensors_.size() != 1) {
+    MS_LOG(ERROR) << "Invalid input size: " << in_tensors_.size() << ", output size: " << out_tensors_.size();
+    return RET_ERROR;
+  }
   std::string kernel_name = "DepthwiseConv2d";
   if (out_mem_type_ == OpenCLMemType::BUF) {
     kernel_name += "_BUF";

mindspore/lite/src/runtime/kernel/opencl/kernel/fullconnection.cc

@@ -34,6 +34,10 @@ using mindspore::schema::PrimitiveType_FullConnection;
 namespace mindspore::kernel {
 
 int FullConnectionOpenCLKernel::Init() {
+  if ((in_tensors_.size() != 2 && in_tensors_.size() != 3) || out_tensors_.size() != 1) {
+    MS_LOG(ERROR) << "Invalid input size: " << in_tensors_.size() << ", output size: " << out_tensors_.size();
+    return RET_ERROR;
+  }
   std::string kernel_name = "FullConnection_NHWC4";
   auto param = reinterpret_cast<MatMulParameter *>(op_parameter_);
   transposeA = param->a_transpose_;

mindspore/lite/src/runtime/kernel/opencl/kernel/pooling2d.cc

@@ -37,6 +37,10 @@ using mindspore::schema::PrimitiveType_Pooling;
 namespace mindspore {
 namespace kernel {
 int PoolingOpenCLKernel::Init() {
+  if (in_tensors_.size() != 1 || out_tensors_.size() != 1) {
+    MS_LOG(ERROR) << "Invalid input size: " << in_tensors_.size() << ", output size: " << out_tensors_.size();
+    return RET_ERROR;
+  }
   std::string kernel_name;
 #ifndef PROGRAM_WITH_IL
   std::string source;

mindspore/lite/src/runtime/kernel/opencl/kernel/reshape.cc

@@ -31,6 +31,10 @@ using mindspore::schema::PrimitiveType_Squeeze;
 namespace mindspore::kernel {
 
 int ReshapeOpenCLKernel::Init() {
+  if ((in_tensors_.size() != 1 && in_tensors_.size() != 2) || out_tensors_.size() != 1) {
+    MS_LOG(ERROR) << "Invalid input size: " << in_tensors_.size() << ", output size: " << out_tensors_.size();
+    return RET_ERROR;
+  }
   std::string kernel_name = "reshape_NHWC4";
   if (out_tensors_[0]->shape().size() != 2 && out_tensors_[0]->shape().size() != 4) {
     MS_LOG(ERROR) << "Reshape output size should in 2,4";

mindspore/lite/src/runtime/kernel/opencl/kernel/softmax.cc

@@ -78,6 +78,10 @@ int SoftmaxOpenCLKernel::SetWorkGroupSize1x1() {
 }
 
 int SoftmaxOpenCLKernel::Init() {
+  if (in_tensors_.size() != 1 || out_tensors_.size() != 1) {
+    MS_LOG(ERROR) << "Invalid input size: " << in_tensors_.size() << ", output size: " << out_tensors_.size();
+    return RET_ERROR;
+  }
   std::string kernel_name = "SoftMax";
   std::string program_name = "SoftMax";
   auto softmax_param = reinterpret_cast<SoftmaxParameter *>(op_parameter_);

mindspore/lite/src/runtime/kernel/opencl/kernel/transpose.cc

@@ -34,6 +34,10 @@ using mindspore::schema::PrimitiveType_Transpose;
 namespace mindspore::kernel {
 
 int TransposeOpenCLKernel::Init() {
+  if ((in_tensors_.size() != 1 && in_tensors_.size() != 2) || out_tensors_.size() != 1) {
+    MS_LOG(ERROR) << "Invalid input size: " << in_tensors_.size() << ", output size: " << out_tensors_.size();
+    return RET_ERROR;
+  }
   std::string kernel_name = "transpose";
   enable_fp16_ = ocl_runtime_->GetFp16Enable();
   auto param = reinterpret_cast<TransposeParameter *>(op_parameter_);