fix gpu load memory leak,test=develop (#2027)

mobile/src/operators/kernel/cl/density_prior_box_kernel.cpp

@@ -25,6 +25,35 @@ bool DensityPriorBoxKernel<GPU_CL, float>::Init(
         *param) {
   this->cl_helper_.AddKernel("density_prior_box",
                              "density_prior_box_kernel.cl");
+  vector<float> fixed_sizes = param->FixedSizes();
+  vector<float> fixed_ratios = param->FixedRatios();
+  vector<int> densities = param->Densities();
+  vector<float> variances = param->Variances();
+  int fix_ratio_size = fixed_ratios.size();
+  int total_size = densities.size() + fixed_sizes.size() + fix_ratio_size;
+  float *densities_data = new float[total_size];
+  for (int i = 0; i < densities.size(); ++i) {
+    float density = densities[i];
+    densities_data[i] = density;
+  }
+
+  for (int k = 0; k < fixed_sizes.size(); ++k) {
+    densities_data[k + densities.size()] = fixed_sizes[k];
+  }
+
+  for (int j = 0; j < fixed_ratios.size(); ++j) {
+    float sqrt_ratios = sqrt(fixed_ratios[j]);
+    densities_data[j + densities.size() + fixed_sizes.size()] = sqrt_ratios;
+  }
+
+  framework::CLImage *new_density = new framework::CLImage();
+  new_density->SetTensorData(densities_data, {1, 1, 1, total_size});
+  new_density->InitCLImage(this->cl_helper_.CLContext(),
+                           this->cl_helper_.CLCommandQueue());
+  param->setNewDensity(new_density);
+
+  delete[](densities_data);
+
   return true;
 }
 
@@ -39,6 +68,7 @@ void DensityPriorBoxKernel<GPU_CL, float>::Compute(
 
   auto output_boxes = param.OutputBoxes()->GetCLImage();
   auto output_var = param.OutputVariances()->GetCLImage();
+  auto new_deensity = param.getNewDensity()->GetCLImage();
 
   float step_w = param.StepW();
   float step_h = param.StepH();
@@ -73,43 +103,17 @@ void DensityPriorBoxKernel<GPU_CL, float>::Compute(
 
   auto default_work = this->cl_helper_.DefaultWorkSize(*param.OutputBoxes());
 
-  float *densities_data[densities.size() + fixed_sizes.size() + fix_ratio_size];
-
-  int status;
-
-  for (int i = 0; i < densities.size(); ++i) {
-    float density = densities[i];
-    densities_data[i] = &density;
-  }
-
-  for (int k = 0; k < fixed_sizes.size(); ++k) {
-    densities_data[k + densities.size()] = &fixed_sizes[k];
-  }
-
-  for (int j = 0; j < fixed_ratios.size(); ++j) {
-    float sqrt_ratios = sqrt(fixed_ratios[j]);
-    densities_data[j + densities.size() + fixed_sizes.size()] = &sqrt_ratios;
-  }
-
-  cl_mem densities_memobj = clCreateBuffer(
-      this->cl_helper_.CLContext(), CL_MEM_READ_WRITE,
-      sizeof(float) * (densities.size() * 2 + fix_ratio_size), NULL, &status);
-  status = clEnqueueWriteBuffer(
-      this->cl_helper_.CLCommandQueue(), densities_memobj, CL_FALSE, 0,
-      (densities.size() * 2 + fix_ratio_size) * sizeof(float), densities_data,
-      0, NULL, NULL);
-  CL_CHECK_ERRORS(status);
-
   float variances0 = variances[0];
   float variances1 = variances[1];
   float variances2 = variances[2];
   float variances3 = variances[3];
 
+  cl_int status;
   status = clSetKernelArg(kernel, 0, sizeof(cl_mem), &output_boxes);
   CL_CHECK_ERRORS(status);
   status = clSetKernelArg(kernel, 1, sizeof(cl_mem), &output_var);
   CL_CHECK_ERRORS(status);
-  status = clSetKernelArg(kernel, 2, sizeof(cl_mem), &densities_memobj);
+  status = clSetKernelArg(kernel, 2, sizeof(cl_mem), &new_deensity);
   CL_CHECK_ERRORS(status);
   status = clSetKernelArg(kernel, 3, sizeof(float), &step_h);
   CL_CHECK_ERRORS(status);

mobile/src/operators/kernel/cl/transpose2_kernel.cpp

@@ -184,6 +184,8 @@ void Transpose2Compute(const Transpose2Param<GPU_CL> &param, cl_context context,
   output->InitEmptyImage(context, commandQueue, output_tensor->dims());
   framework::TensorToCLImage(output_tensor, output, context, commandQueue,
                              kernel1);
+  delete (input_tensor);
+  delete (output_tensor);
 }
 
 template <>

mobile/src/operators/kernel/prior_box_kernel.h

@@ -77,6 +77,12 @@ class DensityPriorBoxParam : public OpParam {
     densities_ = GetAttr<vector<int>>("densities", attrs);
   }
 
+  ~DensityPriorBoxParam() {
+    if (new_density) {
+      delete new_density;
+    }
+  }
+
   const GType *Input() const { return input_; }
   const GType *InputImage() const { return input_image_; }
   GType *OutputBoxes() const { return output_boxes_; }
@@ -90,6 +96,8 @@ class DensityPriorBoxParam : public OpParam {
   const vector<float> &FixedRatios() const { return fixed_ratios_; }
   const vector<int> &Densities() const { return densities_; }
   const vector<float> &Variances() const { return variances_; }
+  GType *getNewDensity() const { return new_density; }
+  void setNewDensity(GType *newDensity) { new_density = newDensity; }
 
  public:
   GType *input_;
@@ -105,6 +113,7 @@ class DensityPriorBoxParam : public OpParam {
   vector<float> fixed_ratios_;
   vector<int> densities_;
   vector<float> variances_;
+  GType *new_density;
 };
 
 DECLARE_KERNEL(DensityPriorBox, DensityPriorBoxParam);

mobile/src/operators/op_param.h

@@ -850,6 +850,15 @@ class BatchNormParam : public OpParam {
     //    is_test_ = GetAttr<bool>("is_test", attrs);
   }
 
+  ~BatchNormParam() {
+    if (new_bias_) {
+      delete new_bias_;
+    }
+    if (new_scale_) {
+      delete new_scale_;
+    }
+  }
+
   const GType *InputX() const { return input_x_; }
 
   GType *OutputY() const { return output_y_; }
@@ -2076,6 +2085,16 @@ class FusionConvAddBNReluParam : public ConvParam<Dtype> {
     momentum_ = OpParam::GetAttr<float>("momentum", attrs);
     this->output_ = OpParam::OutFrom<GType>(outputs, *scope);
   }
+
+  ~FusionConvAddBNReluParam() {
+    if (new_bias_) {
+      delete new_bias_;
+    }
+    if (new_scale_) {
+      delete new_scale_;
+    }
+  }
+
   GType *Bias() const { return bias_; }
 
   const int &Axis() const { return axis_; }
@@ -2143,6 +2162,15 @@ class FusionConvBNAddReluParam : public ConvParam<Dtype> {
     }
     this->output_ = OpParam::OutFrom<GType>(outputs, *scope);
   }
+
+  ~FusionConvBNAddReluParam() {
+    if (new_bias_) {
+      delete new_bias_;
+    }
+    if (new_scale_) {
+      delete new_scale_;
+    }
+  }
   GType *Bias() const { return bias_; }
 
   const int &Axis() const { return axis_; }
@@ -2315,6 +2343,15 @@ class FusionDWConvBNReluParam : public ConvParam<Dtype> {
     this->output_ = OpParam::OutFrom<GType>(outputs, *scope);
   }
 
+  ~FusionDWConvBNReluParam() {
+    if (new_bias_) {
+      delete new_bias_;
+    }
+    if (new_scale_) {
+      delete new_scale_;
+    }
+  }
+
   const GType *InputBias() const { return input_bias_; }
 
   const GType *InputMean() const { return input_mean_; }
@@ -2384,6 +2421,15 @@ class FusionConvBNReluParam : public ConvParam<Dtype> {
     this->output_ = OpParam::OutFrom<GType>(outputs, *scope);
   }
 
+  ~FusionConvBNReluParam() {
+    if (new_bias_) {
+      delete new_bias_;
+    }
+    if (new_scale_) {
+      delete new_scale_;
+    }
+  }
+
   const GType *InputBias() const { return input_bias_; }
 
   const GType *InputMean() const { return input_mean_; }