[LITE][OPENCL]use shared_ptr with cl::kernel , init cl::event when use ,test=develop

lite/backends/opencl/cl_context.cc

@@ -68,16 +68,16 @@ void CLContext::AddKernel(const std::string &kernel_name,
   kernel_offset_[kernel_key.str()] = kernels_.size() - 1;
 }
 
-cl::Kernel &CLContext::GetKernel(const int index) {
+std::shared_ptr<cl::Kernel> &CLContext::GetKernel(const int index) {
   VLOG(3) << " --- kernel count: " << kernels_.size() << " --- ";
   CHECK(static_cast<size_t>(index) < kernels_.size())
       << "The index must be less than the size of kernels.";
   CHECK(kernels_[index] != nullptr)
       << "The target kernel pointer cannot be null.";
-  return *(kernels_[index]);
+  return kernels_[index];
 }
 
-cl::Kernel &CLContext::GetKernel(const std::string &name) {
+std::shared_ptr<cl::Kernel> &CLContext::GetKernel(const std::string &name) {
   auto it = kernel_offset_.find(name);
   CHECK(it != kernel_offset_.end()) << "Cannot find the kernel function: "
                                     << name;

lite/backends/opencl/cl_context.h

@@ -54,9 +54,9 @@ class CLContext {
                  const std::string &options = "",
                  const std::string &time_stamp = "");
 
-  cl::Kernel &GetKernel(const int index);
+  std::shared_ptr<cl::Kernel> &GetKernel(const int index);
 
-  cl::Kernel &GetKernel(const std::string &name);
+  std::shared_ptr<cl::Kernel> &GetKernel(const std::string &name);
 
   cl::NDRange DefaultWorkSize(const CLImage &image);
 

lite/kernels/opencl/activation_buffer_compute.cc

@@ -54,16 +54,16 @@ class ReluCompute
     VLOG(4) << TargetToStr(param.Out->target());
 
     int arg_idx = 0;
-    cl_int status = kernel.setArg(arg_idx, *x_buf);
+    cl_int status = kernel->setArg(arg_idx, *x_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, (const int)count);
+    status = kernel->setArg(++arg_idx, (const int)count);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *out_buf);
+    status = kernel->setArg(++arg_idx, *out_buf);
     CL_CHECK_FATAL(status);
 
     auto global_work_size = cl::NDRange{count};
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,
@@ -112,16 +112,16 @@ class SigmoidCompute
     VLOG(4) << TargetToStr(param.Out->target());
 
     int arg_idx = 0;
-    cl_int status = kernel.setArg(arg_idx, *x_buf);
+    cl_int status = kernel->setArg(arg_idx, *x_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, (const int)count);
+    status = kernel->setArg(++arg_idx, (const int)count);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *out_buf);
+    status = kernel->setArg(++arg_idx, *out_buf);
     CL_CHECK_FATAL(status);
 
     auto global_work_size = cl::NDRange{count};
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/activation_image_compute.cc

@@ -84,7 +84,7 @@ class ActivationComputeImageDefault
 
     STL::stringstream kernel_key;
     kernel_key << kernel_func_name_ << build_options_ << time_stamp_;
-    kernel_ = context.cl_context()->GetKernel(kernel_key.str());
+    auto kernel = context.cl_context()->GetKernel(kernel_key.str());
   }
 
   void ReInitWhenNeeded() override {
@@ -117,16 +117,20 @@ class ActivationComputeImageDefault
     auto* x_img = act_param_->X->data<half_t, cl::Image2D>();
     auto* out_img = act_param_->Out->mutable_data<half_t, cl::Image2D>(
         out_img_shape_[0], out_img_shape_[1]);
-
-    auto kernel = kernel_;
+    auto& context = ctx_->As<OpenCLContext>();
+    CHECK(context.cl_context() != nullptr);
+    std::stringstream kernel_key;
+    kernel_key << kernel_func_name_ << build_options_ << time_stamp_;
+    auto kernel = context.cl_context()->GetKernel(kernel_key.str());
+    ;
     cl_int status;
-    status = kernel.setArg(0, *x_img);
+    status = kernel->setArg(0, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(1, *out_img);
+    status = kernel->setArg(1, *out_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(2, threshold_);
+    status = kernel->setArg(2, threshold_);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(3, scale_);
+    status = kernel->setArg(3, scale_);
     CL_CHECK_FATAL(status);
 
 #ifndef LITE_SHUTDOWN_LOG
@@ -145,10 +149,8 @@ class ActivationComputeImageDefault
     VLOG(4) << "kernel func name:" << kernel_func_name_;
 #endif
 
-    auto& context = ctx_->As<OpenCLContext>();
-    CHECK(context.cl_context() != nullptr);
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size_,
         cl::NullRange,
@@ -168,7 +170,7 @@ class ActivationComputeImageDefault
   std::string kernel_func_name_{};
   float threshold_{6.f};
   float scale_{1.f};
-  cl::Kernel kernel_;
+  cl::Kernel kernel;
   bool first_epoch_for_reinit_{true};
   cl::NDRange global_work_size_ = cl::NDRange{
       static_cast<size_t>(1), static_cast<size_t>(1), static_cast<size_t>(1)};

lite/kernels/opencl/bilinear_interp_image_compute.cc

@@ -118,23 +118,23 @@ class BilinearInterpImageCompute
     VLOG(4) << "default_work_size: " << default_work_size[0] << ", "
             << default_work_size[1] << ", " << default_work_size[2];
 #endif
-    cl_int status = kernel.setArg(arg_idx++, *x_img);
+    cl_int status = kernel->setArg(arg_idx++, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, *out_img);
+    status = kernel->setArg(arg_idx++, *out_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, scale_h);
+    status = kernel->setArg(arg_idx++, scale_h);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, scale_w);
+    status = kernel->setArg(arg_idx++, scale_w);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, align_delta);
+    status = kernel->setArg(arg_idx++, align_delta);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, in_h);
+    status = kernel->setArg(arg_idx++, in_h);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, in_w);
+    status = kernel->setArg(arg_idx++, in_w);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, out_h);
+    status = kernel->setArg(arg_idx++, out_h);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, out_w);
+    status = kernel->setArg(arg_idx++, out_w);
     CL_CHECK_FATAL(status);
 
     auto global_work_size =
@@ -143,7 +143,7 @@ class BilinearInterpImageCompute
                     static_cast<cl::size_type>(default_work_size[2])};
 
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/box_coder_image_compute.cc

@@ -104,24 +104,24 @@ class BoxCoderComputeImage : public KernelLite<TARGET(kOpenCL),
               << default_work_size[1] << ", " << default_work_size[2];
 #endif
       int arg_idx = 0;
-      cl_int status = kernel.setArg(arg_idx++, *prior_box_image);
+      cl_int status = kernel->setArg(arg_idx++, *prior_box_image);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(arg_idx++, *prior_box_var_image);
+      status = kernel->setArg(arg_idx++, *prior_box_var_image);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(arg_idx++, *target_box_image);
+      status = kernel->setArg(arg_idx++, *target_box_image);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(arg_idx++, *out_buf);
+      status = kernel->setArg(arg_idx++, *out_buf);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(arg_idx++, out_C);
+      status = kernel->setArg(arg_idx++, out_C);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(arg_idx++, out_H);
+      status = kernel->setArg(arg_idx++, out_H);
       CL_CHECK_FATAL(status);
       auto global_work_size =
           cl::NDRange{static_cast<cl::size_type>(default_work_size[0]),
                       static_cast<cl::size_type>(default_work_size[2])};
 
       status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-          kernel,
+          *kernel.get(),
           cl::NullRange,
           global_work_size,
           cl::NullRange,

lite/kernels/opencl/concat_buffer_compute.cc

@@ -103,28 +103,28 @@ class ConcatCompute : public KernelLite<TARGET(kOpenCL),
       auto axis0 = inputs[0]->dims()[axis_];
       int total0 = axis0 * post_size_;
       int total1 = (axis_size_ - axis0) * post_size_;
-      cl_int status = kernel.setArg(arg_idx, *x_buf0);
+      cl_int status = kernel->setArg(arg_idx, *x_buf0);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, *x_buf1);
+      status = kernel->setArg(++arg_idx, *x_buf1);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, *out_buf);
+      status = kernel->setArg(++arg_idx, *out_buf);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, static_cast<int>(axis0));
+      status = kernel->setArg(++arg_idx, static_cast<int>(axis0));
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, axis_size_);
+      status = kernel->setArg(++arg_idx, axis_size_);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, pre_size_);
+      status = kernel->setArg(++arg_idx, pre_size_);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, post_size_);
+      status = kernel->setArg(++arg_idx, post_size_);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, total);
+      status = kernel->setArg(++arg_idx, total);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, total0);
+      status = kernel->setArg(++arg_idx, total0);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, total1);
+      status = kernel->setArg(++arg_idx, total1);
       CL_CHECK_FATAL(status);
       status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-          kernel,
+          *kernel.get(),
           cl::NullRange,
           global_work_size,
           cl::NullRange,
@@ -140,24 +140,24 @@ class ConcatCompute : public KernelLite<TARGET(kOpenCL),
         auto* x_buf = inputs[i]->data<float, cl::Buffer>();
         global_work_size = cl::NDRange{static_cast<size_t>(size)};
         int total0 = size * post_size_;
-        cl_int status = kernel.setArg(arg_idx, *x_buf);
+        cl_int status = kernel->setArg(arg_idx, *x_buf);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, *out_buf);
+        status = kernel->setArg(++arg_idx, *out_buf);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, static_cast<int>(size));
+        status = kernel->setArg(++arg_idx, static_cast<int>(size));
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, pre_size_);
+        status = kernel->setArg(++arg_idx, pre_size_);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, post_size_);
+        status = kernel->setArg(++arg_idx, post_size_);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, start);
+        status = kernel->setArg(++arg_idx, start);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, total);
+        status = kernel->setArg(++arg_idx, total);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, total0);
+        status = kernel->setArg(++arg_idx, total0);
         CL_CHECK_FATAL(status);
         status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-            kernel,
+            *kernel.get(),
             cl::NullRange,
             global_work_size,
             cl::NullRange,

lite/kernels/opencl/concat_image_compute.cc

@@ -170,25 +170,25 @@ class ConcatComputeImage : public KernelLite<TARGET(kOpenCL),
     if (inputs.size() == 2) {
       auto* x_buf0 = inputs[0]->data<half_t, cl::Image2D>();
       auto* x_buf1 = inputs[1]->data<half_t, cl::Image2D>();
-      cl_int status = kernel.setArg(arg_idx, *x_buf0);
+      cl_int status = kernel->setArg(arg_idx, *x_buf0);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, *x_buf1);
+      status = kernel->setArg(++arg_idx, *x_buf1);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, *out_buf);
+      status = kernel->setArg(++arg_idx, *out_buf);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, flag_);
+      status = kernel->setArg(++arg_idx, flag_);
       CL_CHECK_FATAL(status);
       status =
-          kernel.setArg(++arg_idx, static_cast<int>(inputs[0]->dims()[axis_]));
+          kernel->setArg(++arg_idx, static_cast<int>(inputs[0]->dims()[axis_]));
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, out_c);
+      status = kernel->setArg(++arg_idx, out_c);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, out_w);
+      status = kernel->setArg(++arg_idx, out_w);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, width_);
+      status = kernel->setArg(++arg_idx, width_);
       CL_CHECK_FATAL(status);
       status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-          kernel,
+          *kernel.get(),
           cl::NullRange,
           global_work_size,
           cl::NullRange,
@@ -213,25 +213,25 @@ class ConcatComputeImage : public KernelLite<TARGET(kOpenCL),
                         static_cast<cl::size_type>(image_shape["width"] /
                                                    in_dims[in_dims.size() - 1]),
                         static_cast<cl::size_type>(image_shape["height"])};
-        cl_int status = kernel.setArg(arg_idx, *x_buf);
+        cl_int status = kernel->setArg(arg_idx, *x_buf);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, *out_buf);
+        status = kernel->setArg(++arg_idx, *out_buf);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, flag_);
+        status = kernel->setArg(++arg_idx, flag_);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, start);
+        status = kernel->setArg(++arg_idx, start);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, out_c);
+        status = kernel->setArg(++arg_idx, out_c);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, out_w);
+        status = kernel->setArg(++arg_idx, out_w);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, in_w);
+        status = kernel->setArg(++arg_idx, in_w);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(++arg_idx, width_);
+        status = kernel->setArg(++arg_idx, width_);
         CL_CHECK_FATAL(status);
         CL_CHECK_FATAL(status);
         status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-            kernel,
+            *kernel.get(),
             cl::NullRange,
             global_work_size,
             cl::NullRange,

lite/kernels/opencl/conv_buffer_compute.cc

@@ -283,25 +283,25 @@ void ConvCompute::GemmBatched(cl::Kernel& kernel,
   auto& context = ctx_->As<OpenCLContext>();
   cl_int status;
   int arg_idx = 0;
-  status = kernel.setArg(arg_idx, *filter_d);
+  status = kernel->setArg(arg_idx, *filter_d);
   CL_CHECK_FATAL(status);
-  status = kernel.setArg(++arg_idx, *x_d);
+  status = kernel->setArg(++arg_idx, *x_d);
   CL_CHECK_FATAL(status);
-  status = kernel.setArg(++arg_idx, *bias_d);
+  status = kernel->setArg(++arg_idx, *bias_d);
   CL_CHECK_FATAL(status);
-  status = kernel.setArg(++arg_idx, *output_d);
+  status = kernel->setArg(++arg_idx, *output_d);
   CL_CHECK_FATAL(status);
-  status = kernel.setArg(++arg_idx, m);
+  status = kernel->setArg(++arg_idx, m);
   CL_CHECK_FATAL(status);
-  status = kernel.setArg(++arg_idx, n);
+  status = kernel->setArg(++arg_idx, n);
   CL_CHECK_FATAL(status);
-  status = kernel.setArg(++arg_idx, k);
+  status = kernel->setArg(++arg_idx, k);
   CL_CHECK_FATAL(status);
-  status = kernel.setArg(++arg_idx, batch_size);
+  status = kernel->setArg(++arg_idx, batch_size);
   CL_CHECK_FATAL(status);
 
   status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-      kernel,
+      *kernel.get(),
       cl::NullRange,
       global_work_size,
       local_work_size,

lite/kernels/opencl/conv_image_compute.h

@@ -71,7 +71,6 @@ class ConvImageCompute : public KernelLite<TARGET(kOpenCL),
   int default_w_blk_ = 1;
   int default_nh_blk_ = 1;
 
-  cl::Kernel kernel_;
   cl::NDRange local_work_size_ = cl::NDRange{
       static_cast<size_t>(1), static_cast<size_t>(1), static_cast<size_t>(1)};
   bool use_lws_{true};

lite/kernels/opencl/depthwise_conv2d_buffer_compute.cc

@@ -75,41 +75,41 @@ class DepthwiseConv2dCompute
     cl_int status;
     auto numel = output_dims.production();
     int arg_idx = 0;
-    status = kernel.setArg(arg_idx, static_cast<const int>(numel));
+    status = kernel->setArg(arg_idx, static_cast<const int>(numel));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *input_buf);
+    status = kernel->setArg(++arg_idx, *input_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(x_dims[2]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(x_dims[2]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(x_dims[3]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(x_dims[3]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(output_dims[1]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(output_dims[1]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(output_dims[2]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(output_dims[2]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(output_dims[3]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(output_dims[3]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(filter_dims[2]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(filter_dims[2]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(filter_dims[3]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(filter_dims[3]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(strides[0]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(strides[0]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(strides[1]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(strides[1]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(paddings[0]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(paddings[0]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(paddings[1]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(paddings[1]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *output_buf);
+    status = kernel->setArg(++arg_idx, *output_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *filter_buf);
+    status = kernel->setArg(++arg_idx, *filter_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *bias_buf);
+    status = kernel->setArg(++arg_idx, *bias_buf);
     CL_CHECK_FATAL(status);
     auto global_work_size = cl::NDRange(static_cast<size_t>(numel));
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/dropout_image_compute.cc

@@ -70,13 +70,13 @@ class DropoutComputeImage2D : public KernelLite<TARGET(kOpenCL),
     cl_int status;
 
     int arg_idx = 0;
-    status = kernel.setArg(arg_idx, *x_img);
+    status = kernel->setArg(arg_idx, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *out_img);
+    status = kernel->setArg(++arg_idx, *out_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, out_w);
+    status = kernel->setArg(++arg_idx, out_w);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, dropout_prob);
+    status = kernel->setArg(++arg_idx, dropout_prob);
     CL_CHECK_FATAL(status);
 
     const std::vector<size_t>& default_work_size =
@@ -90,7 +90,7 @@ class DropoutComputeImage2D : public KernelLite<TARGET(kOpenCL),
                     static_cast<cl::size_type>(default_work_size.data()[2])};
 
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/elementwise_add_buffer_compute.cc

@@ -49,22 +49,22 @@ void ElementwiseAddCompute::Run() {
   VLOG(4) << TargetToStr(ele_param_->Out->target());
 #endif
   int arg_idx = 0;
-  cl_int status = kernel.setArg(arg_idx, *x_buf);
+  cl_int status = kernel->setArg(arg_idx, *x_buf);
   CL_CHECK_FATAL(status);
-  status = kernel.setArg(++arg_idx, *y_buf);
+  status = kernel->setArg(++arg_idx, *y_buf);
   CL_CHECK_FATAL(status);
-  status = kernel.setArg(++arg_idx, *out_buf);
+  status = kernel->setArg(++arg_idx, *out_buf);
   CL_CHECK_FATAL(status);
-  status = kernel.setArg(++arg_idx, (const int)batch_);
+  status = kernel->setArg(++arg_idx, (const int)batch_);
   CL_CHECK_FATAL(status);
-  status = kernel.setArg(++arg_idx, (const int)channels_);
+  status = kernel->setArg(++arg_idx, (const int)channels_);
   CL_CHECK_FATAL(status);
-  status = kernel.setArg(++arg_idx, (const int)num_);
+  status = kernel->setArg(++arg_idx, (const int)num_);
   CL_CHECK_FATAL(status);
 
   auto global_work_size = cl::NDRange{channels_, batch_};
   status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-      kernel,
+      *kernel.get(),
       cl::NullRange,
       global_work_size,
       cl::NullRange,

lite/kernels/opencl/elementwise_add_image_compute.cc

@@ -66,7 +66,7 @@ void ElementwiseAddImageCompute::ReInitWhenNeeded() {
 
     STL::stringstream kernel_key;
     kernel_key << kernel_func_name_ << build_options_ << time_stamp_;
-    kernel_ = context.cl_context()->GetKernel(kernel_key.str());
+    auto kernel = context.cl_context()->GetKernel(kernel_key.str());
 
     // compute image shape
     paddle::lite::CLImageConverterDefault default_convertor;
@@ -90,6 +90,8 @@ void ElementwiseAddImageCompute::GetGlobalWorkSize() {
 }
 
 void ElementwiseAddImageCompute::Run() {
+  auto& context = ctx_->As<OpenCLContext>();
+  CHECK(context.cl_context() != nullptr);
   auto* x = ele_param_->X;
   auto* y = ele_param_->Y;
   auto* out = ele_param_->Out;
@@ -118,13 +120,16 @@ void ElementwiseAddImageCompute::Run() {
 #endif
 
   cl_int status;
-  auto kernel = kernel_;
+  std::stringstream kernel_key;
+  kernel_key << kernel_func_name_ << build_options_ << time_stamp_;
+  auto kernel = context.cl_context()->GetKernel(kernel_key.str());
+
   if (y_dims.size() == 4) {
-    status = kernel.setArg(0, *x_img);
+    status = kernel->setArg(0, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(1, *y_img);
+    status = kernel->setArg(1, *y_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(2, *out_img);
+    status = kernel->setArg(2, *out_img);
     CL_CHECK_FATAL(status);
   } else if (y_dims.size() == 1) {
     if (axis == x_dims.size() - 1 || axis == x_dims.size() - 3) {
@@ -132,13 +137,13 @@ void ElementwiseAddImageCompute::Run() {
 #ifndef LITE_SHUTDOWN_LOG
       VLOG(4) << "tensor_w:" << tensor_w;
 #endif
-      status = kernel.setArg(0, *x_img);
+      status = kernel->setArg(0, *x_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(1, *y_img);
+      status = kernel->setArg(1, *y_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(2, *out_img);
+      status = kernel->setArg(2, *out_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(3, tensor_w);
+      status = kernel->setArg(3, tensor_w);
       CL_CHECK_FATAL(status);
     } else {
       LOG(FATAL) << "ElementwiseAddImage doesn't support axis:" << axis
@@ -151,10 +156,8 @@ void ElementwiseAddImageCompute::Run() {
                << ", y->dims.size():" << y_dims.size();
   }
 
-  auto& context = ctx_->As<OpenCLContext>();
-  CHECK(context.cl_context() != nullptr);
   status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-      kernel,
+      *kernel.get(),
       cl::NullRange,
       global_work_size_,
       cl::NullRange,

lite/kernels/opencl/elementwise_mul_compute.cc

@@ -96,51 +96,51 @@ void ElementwiseMulFloatImageCompute::Run() {
   auto x_dims = x->dims();
   if (y_dims == x_dims) {
     // kernel: elementwise_mul(channel_mul_d4)
-    cl_int status = kernel.setArg(arg_idx, *x_img);
+    cl_int status = kernel->setArg(arg_idx, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *y_img);
+    status = kernel->setArg(++arg_idx, *y_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *out_img);
+    status = kernel->setArg(++arg_idx, *out_img);
     CL_CHECK_FATAL(status);
   } else if (y_dims.size() == 1 || y_dims.size() == 4) {
     auto tensor_w = x_dims[x_dims.size() - 1];
     VLOG(4) << "tensor_w:" << tensor_w;
     // kernel: channel_mul_d1 / channel_mul_d4
-    cl_int status = kernel.setArg(arg_idx, *x_img);
+    cl_int status = kernel->setArg(arg_idx, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *y_img);
+    status = kernel->setArg(++arg_idx, *y_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *out_img);
+    status = kernel->setArg(++arg_idx, *out_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(tensor_w));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(tensor_w));
     CL_CHECK_FATAL(status);
   } else if (y_dims.size() == 2) {
     if (x_dims[0] == y_dims[0] && x_dims[1] == y_dims[1]) {
       auto tensor_w = x_dims[x_dims.size() - 1];
       VLOG(4) << "tensor_w:" << tensor_w;
       // kernel: channel_mul_d2_nc
-      cl_int status = kernel.setArg(arg_idx, *x_img);
+      cl_int status = kernel->setArg(arg_idx, *x_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, *y_img);
+      status = kernel->setArg(++arg_idx, *y_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, *out_img);
+      status = kernel->setArg(++arg_idx, *out_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, static_cast<const int>(tensor_w));
+      status = kernel->setArg(++arg_idx, static_cast<const int>(tensor_w));
       CL_CHECK_FATAL(status);
     } else {
       auto y_tensor_h = y->dims()[0];
       auto y_tensor_w = y->dims()[1];
       VLOG(4) << "y_tensor_w:" << y_tensor_w << " y_tensor_h:" << y_tensor_h;
       // kernel: channel_mul_d2_hw
-      cl_int status = kernel.setArg(arg_idx, *x_img);
+      cl_int status = kernel->setArg(arg_idx, *x_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, *y_img);
+      status = kernel->setArg(++arg_idx, *y_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, *out_img);
+      status = kernel->setArg(++arg_idx, *out_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, static_cast<const int>(y_tensor_w));
+      status = kernel->setArg(++arg_idx, static_cast<const int>(y_tensor_w));
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, static_cast<const int>(y_tensor_h));
+      status = kernel->setArg(++arg_idx, static_cast<const int>(y_tensor_h));
       CL_CHECK_FATAL(status);
     }
   } else {
@@ -151,7 +151,7 @@ void ElementwiseMulFloatImageCompute::Run() {
   auto global_work_size = cl::NDRange{static_cast<cl::size_type>(x_img_width),
                                       static_cast<cl::size_type>(x_img_height)};
   auto status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-      kernel,
+      *kernel.get(),
       cl::NullRange,
       global_work_size,
       cl::NullRange,

lite/kernels/opencl/elementwise_mul_image_compute.cc

@@ -124,57 +124,57 @@ class ElementwiseMulImageCompute
 
     if (bias_dims == x_dims) {
       // kernel_func_name_ = "elementwise_mul";
-      cl_int status = kernel.setArg(0, *x_img);
+      cl_int status = kernel->setArg(0, *x_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(1, *y_img);
+      status = kernel->setArg(1, *y_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(2, *out_img);
+      status = kernel->setArg(2, *out_img);
       CL_CHECK_FATAL(status);
     } else {
       const int bias_dim_size = bias_dims.size();
       if (bias_dim_size == 1) {
         // kernel_func_name_ = "channel_mul_d1";
         const int tensor_w = x_dims[x_dims.size() - 1];
-        cl_int status = kernel.setArg(0, *x_img);
+        cl_int status = kernel->setArg(0, *x_img);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(1, *y_img);
+        status = kernel->setArg(1, *y_img);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(2, *out_img);
+        status = kernel->setArg(2, *out_img);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(3, tensor_w);
+        status = kernel->setArg(3, tensor_w);
         CL_CHECK_FATAL(status);
       } else if (bias_dim_size == 2) {
         // kernel_func_name_ = "channel_mul_d2";
         const int tensor_w = x_dims[x_dims.size() - 1];
-        cl_int status = kernel.setArg(0, *x_img);
+        cl_int status = kernel->setArg(0, *x_img);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(1, *y_img);
+        status = kernel->setArg(1, *y_img);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(2, *out_img);
+        status = kernel->setArg(2, *out_img);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(3, tensor_w);
+        status = kernel->setArg(3, tensor_w);
         CL_CHECK_FATAL(status);
       } else if (bias_dim_size == 3) {
         // kernel_func_name_ = "channel_mul_d3";
         const int tensor_w = x_dims[x_dims.size() - 1];
-        cl_int status = kernel.setArg(0, *x_img);
+        cl_int status = kernel->setArg(0, *x_img);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(1, *y_img);
+        status = kernel->setArg(1, *y_img);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(2, *out_img);
+        status = kernel->setArg(2, *out_img);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(3, tensor_w);
+        status = kernel->setArg(3, tensor_w);
         CL_CHECK_FATAL(status);
       } else if (bias_dim_size == 4) {
         // kernel_func_name_ = "channel_mul_d4";
         const int tensor_w = x_dims[x_dims.size() - 1];
-        cl_int status = kernel.setArg(0, *x_img);
+        cl_int status = kernel->setArg(0, *x_img);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(1, *y_img);
+        status = kernel->setArg(1, *y_img);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(2, *out_img);
+        status = kernel->setArg(2, *out_img);
         CL_CHECK_FATAL(status);
-        status = kernel.setArg(3, tensor_w);
+        status = kernel->setArg(3, tensor_w);
         CL_CHECK_FATAL(status);
       } else {
         LOG(FATAL) << "Unsupported ElementwiseMul with x_dims:" << x_dims
@@ -186,7 +186,7 @@ class ElementwiseMulImageCompute
         cl::NDRange{static_cast<cl::size_type>(x_img_width),
                     static_cast<cl::size_type>(x_img_height)};
     auto status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/elementwise_sub_image_compute.cc

@@ -101,11 +101,11 @@ void ElementwiseSubImageCompute::Run() {
   int arg_idx = 0;
   auto y_dims = y->dims();
   if (y_dims.size() == 4) {
-    cl_int status = kernel.setArg(arg_idx, *x_img);
+    cl_int status = kernel->setArg(arg_idx, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *y_img);
+    status = kernel->setArg(++arg_idx, *y_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *out_img);
+    status = kernel->setArg(++arg_idx, *out_img);
     CL_CHECK_FATAL(status);
   } else if (y_dims.size() == 1) {
     if (axis == x->dims().size() - 1 || axis == x->dims().size() - 3) {
@@ -113,13 +113,13 @@ void ElementwiseSubImageCompute::Run() {
 #ifndef LITE_SHUTDOWN_LOG
       VLOG(4) << "tensor_w:" << tensor_w;
 #endif
-      cl_int status = kernel.setArg(arg_idx, *x_img);
+      cl_int status = kernel->setArg(arg_idx, *x_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, *y_img);
+      status = kernel->setArg(++arg_idx, *y_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, *out_img);
+      status = kernel->setArg(++arg_idx, *out_img);
       CL_CHECK_FATAL(status);
-      status = kernel.setArg(++arg_idx, static_cast<const int>(tensor_w));
+      status = kernel->setArg(++arg_idx, static_cast<const int>(tensor_w));
       CL_CHECK_FATAL(status);
     } else {
       LOG(FATAL) << "ElementwiseSubImage doesn't support axis:" << axis
@@ -139,7 +139,7 @@ void ElementwiseSubImageCompute::Run() {
 #endif
 
   auto status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-      kernel,
+      *kernel.get(),
       cl::NullRange,
       global_work_size,
       cl::NullRange,

lite/kernels/opencl/fc_buffer_compute.cc

@@ -81,7 +81,7 @@ class FcCompute
                                       time_stamp_);
       STL::stringstream kernel_key;
       kernel_key << kernel_func_name_ << build_options_ << time_stamp_;
-      kernel_ = context.cl_context()->GetKernel(kernel_key.str());
+      auto kernel = context.cl_context()->GetKernel(kernel_key.str());
 
       // compute global work size
       GetGlobalWorkSize();
@@ -103,28 +103,30 @@ class FcCompute
     auto* bias_buf = fc_param_->bias->data<float, cl::Buffer>();
     auto* out_buf =
         fc_param_->output->mutable_data<float, cl::Buffer>(TARGET(kOpenCL));
-
-    auto kernel = kernel_;
+    auto& context = ctx_->As<OpenCLContext>();
+    CHECK(context.cl_context() != nullptr);
+    std::stringstream kernel_key;
+    kernel_key << kernel_func_name_ << build_options_ << time_stamp_;
+    auto kernel = context.cl_context()->GetKernel(kernel_key.str());
+    ;
     cl_int status;
-    status = kernel.setArg(0, *x_buf);
+    status = kernel->setArg(0, *x_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(1, *w_buf);
+    status = kernel->setArg(1, *w_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(2, *bias_buf);
+    status = kernel->setArg(2, *bias_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(3, *out_buf);
+    status = kernel->setArg(3, *out_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(4, static_cast<const int>(m_));
+    status = kernel->setArg(4, static_cast<const int>(m_));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(5, static_cast<const int>(n_));
+    status = kernel->setArg(5, static_cast<const int>(n_));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(6, static_cast<const int>(k_));
+    status = kernel->setArg(6, static_cast<const int>(k_));
     CL_CHECK_FATAL(status);
 
-    auto& context = ctx_->As<OpenCLContext>();
-    CHECK(context.cl_context() != nullptr);
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size_,
         cl::NullRange,
@@ -143,7 +145,7 @@ class FcCompute
   bool first_epoch_for_reinit_{true};
   DDim last_x_dims_;
   cl::NDRange global_work_size_;
-  cl::Kernel kernel_;
+  cl::Kernel kernel;
   std::shared_ptr<cl::Event> event_{new cl::Event};
 };
 

lite/kernels/opencl/grid_sampler_image_compute.cc

@@ -48,7 +48,7 @@ class GridSamplerImageCompute : public KernelLite<TARGET(kOpenCL),
 
     STL::stringstream kernel_key;
     kernel_key << kernel_func_name_ << build_options_ << time_stamp_;
-    kernel_ = context.cl_context()->GetKernel(kernel_key.str());
+    auto kernel = context.cl_context()->GetKernel(kernel_key.str());
     VLOG(4) << "kernel_key: " << kernel_key.str();
   }
 
@@ -116,22 +116,24 @@ class GridSamplerImageCompute : public KernelLite<TARGET(kOpenCL),
 #endif
 
     cl_int status;
-    auto kernel = kernel_;
-    status = kernel.setArg(0, *x_img);
+    auto& context = ctx_->As<OpenCLContext>();
+    CHECK(context.cl_context() != nullptr);
+    std::stringstream kernel_key;
+    kernel_key << kernel_func_name_ << build_options_ << time_stamp_;
+    auto kernel = context.cl_context()->GetKernel(kernel_key.str());
+    status = kernel->setArg(0, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(1, *grid_img);
+    status = kernel->setArg(1, *grid_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(2, *out_img);
+    status = kernel->setArg(2, *out_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(3, out_height);
+    status = kernel->setArg(3, out_height);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(4, out_width);
+    status = kernel->setArg(4, out_width);
     CL_CHECK_FATAL(status);
 
-    auto& context = ctx_->As<OpenCLContext>();
-    CHECK(context.cl_context() != nullptr);
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size_,
         cl::NullRange,
@@ -148,7 +150,6 @@ class GridSamplerImageCompute : public KernelLite<TARGET(kOpenCL),
   DDim out_img_shape_ = DDim(std::vector<DDim::value_type>(
       {static_cast<DDim::value_type>(1), static_cast<DDim::value_type>(1)}));
   std::string kernel_func_name_{"grid_sampler"};
-  cl::Kernel kernel_;
   cl::NDRange global_work_size_ = cl::NDRange{
       static_cast<size_t>(1), static_cast<size_t>(1), static_cast<size_t>(1)};
   std::string build_options_{"-DCL_DTYPE_half"};

lite/kernels/opencl/instance_norm_image_compute.cc

@@ -120,25 +120,25 @@ class InstanceNormImageCompute : public KernelLite<TARGET(kOpenCL),
     kernel_key << kernel_func_name_ << build_options_ << time_stamp_;
     auto kernel = context.cl_context()->GetKernel(kernel_key.str());
 
-    cl_int status = kernel.setArg(0, out_w);
+    cl_int status = kernel->setArg(0, out_w);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(1, out_h);
+    status = kernel->setArg(1, out_h);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(2, out_c_group);
+    status = kernel->setArg(2, out_c_group);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(3, lws1);
+    status = kernel->setArg(3, lws1);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(4, lws2);
+    status = kernel->setArg(4, lws2);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(5, epsilon);
+    status = kernel->setArg(5, epsilon);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(6, *x_img);
+    status = kernel->setArg(6, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(7, *out_img);
+    status = kernel->setArg(7, *out_img);
     CL_CHECK_FATAL(status);
 
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         local_work_size,
@@ -244,23 +244,23 @@ class InstanceNormImageCompute : public KernelLite<TARGET(kOpenCL),
     auto* bias_img = bias_image_.data<half_t, cl::Image2D>();
     float epsilon = instance_norm_param_->epsilon;
 
-    cl_int status = kernel.setArg(arg_idx++, *x_img);
+    cl_int status = kernel->setArg(arg_idx++, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, *out_img);
+    status = kernel->setArg(arg_idx++, *out_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, *scale_img);
+    status = kernel->setArg(arg_idx++, *scale_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, *bias_img);
+    status = kernel->setArg(arg_idx++, *bias_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, epsilon);
+    status = kernel->setArg(arg_idx++, epsilon);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, in_h);
+    status = kernel->setArg(arg_idx++, in_h);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, in_w);
+    status = kernel->setArg(arg_idx++, in_w);
     CL_CHECK_FATAL(status);
 
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         local_work_size,

lite/kernels/opencl/layout_image_compute.cc

@@ -99,21 +99,21 @@ class LayoutComputeBufferChwToImageDefault
     auto kernel = context.cl_context()->GetKernel(kernel_key.str());
 
     int arg_idx = 0;
-    cl_int status = kernel.setArg(arg_idx, *x_data);
+    cl_int status = kernel->setArg(arg_idx, *x_data);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *y_data);
+    status = kernel->setArg(++arg_idx, *y_data);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(out_H));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(out_H));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(out_W));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(out_W));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(out_C));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(out_C));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(Stride0));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(Stride0));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(Stride1));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(Stride1));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(Stride2));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(Stride2));
     CL_CHECK_FATAL(status);
 
     VLOG(2) << "gws:[3D]" << ((new_dims[1] + 3) / 4) << " " << new_dims[3]
@@ -123,7 +123,7 @@ class LayoutComputeBufferChwToImageDefault
                     static_cast<cl::size_type>(new_dims[3]),
                     static_cast<cl::size_type>(new_dims[0] * new_dims[2])};
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,
@@ -205,21 +205,21 @@ class LayoutComputeImageDefaultToBufferChw
     auto kernel = context.cl_context()->GetKernel(kernel_key.str());
 
     int arg_idx = 0;
-    cl_int status = kernel.setArg(arg_idx, *x_data);
+    cl_int status = kernel->setArg(arg_idx, *x_data);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(in_width));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(in_width));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(in_height));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(in_height));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *y_data);
+    status = kernel->setArg(++arg_idx, *y_data);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(size_ch));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(size_ch));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(size_block));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(size_block));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(size_batch));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(size_batch));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(C));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(C));
     CL_CHECK_FATAL(status);
 #ifndef LITE_SHUTDOWN_LOG
     VLOG(2) << "gws:[3D]" << ((new_dims[1] + 3) / 4) << " " << new_dims[3]
@@ -230,7 +230,7 @@ class LayoutComputeImageDefaultToBufferChw
                     static_cast<cl::size_type>(new_dims[3]),
                     static_cast<cl::size_type>(new_dims[0] * new_dims[2])};
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,
@@ -300,21 +300,21 @@ class LayoutComputeBufferChwToImage2DNw
     auto kernel = context.cl_context()->GetKernel(kernel_key.str());
 
     int arg_idx = 0;
-    cl_int status = kernel.setArg(arg_idx, *x_data);
+    cl_int status = kernel->setArg(arg_idx, *x_data);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *y_data);
+    status = kernel->setArg(++arg_idx, *y_data);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(out_H));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(out_H));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(out_W));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(out_W));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(out_N));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(out_N));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(Stride0));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(Stride0));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(Stride1));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(Stride1));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(Stride2));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(Stride2));
     CL_CHECK_FATAL(status);
 
     VLOG(2) << "gws:[3D]" << ((out_N + 3) / 4) << " " << out_W << " "
@@ -324,7 +324,7 @@ class LayoutComputeBufferChwToImage2DNw
                     static_cast<cl::size_type>(out_W),            // w
                     static_cast<cl::size_type>(out_C * out_H)};   // ch
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/lrn_image_compute.cc

@@ -106,21 +106,21 @@ class LrnImageCompute : public KernelLite<TARGET(kOpenCL),
     VLOG(4) << "default_work_size: " << default_work_size[0] << ", "
             << default_work_size[1] << ", " << default_work_size[3];
 #endif
-    cl_int status = kernel.setArg(arg_idx++, *x_img);
+    cl_int status = kernel->setArg(arg_idx++, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, *out_img);
+    status = kernel->setArg(arg_idx++, *out_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, out_channel);
+    status = kernel->setArg(arg_idx++, out_channel);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, out_width);
+    status = kernel->setArg(arg_idx++, out_width);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, n_);
+    status = kernel->setArg(arg_idx++, n_);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, k_);
+    status = kernel->setArg(arg_idx++, k_);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, alpha_);
+    status = kernel->setArg(arg_idx++, alpha_);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, beta_);
+    status = kernel->setArg(arg_idx++, beta_);
     CL_CHECK_FATAL(status);
 
     auto global_work_size =
@@ -129,7 +129,7 @@ class LrnImageCompute : public KernelLite<TARGET(kOpenCL),
                     static_cast<cl::size_type>(default_work_size[2])};
 
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/mul_buffer_compute.cc

@@ -76,23 +76,23 @@ class MulCompute
 
     cl_int status;
     int arg_idx = 0;
-    status = kernel.setArg(arg_idx, *x_buf);
+    status = kernel->setArg(arg_idx, *x_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *y_buf);
+    status = kernel->setArg(++arg_idx, *y_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *out_buf);
+    status = kernel->setArg(++arg_idx, *out_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, m_);
+    status = kernel->setArg(++arg_idx, m_);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, n_);
+    status = kernel->setArg(++arg_idx, n_);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, k_);
+    status = kernel->setArg(++arg_idx, k_);
     CL_CHECK_FATAL(status);
 
     auto global_work_size = cl::NDRange{static_cast<size_t>((m_ + 3) / 4),
                                         static_cast<size_t>((n_ + 3) / 4)};
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/nearest_interp_image_compute.cc

@@ -72,21 +72,21 @@ class NearestInterpComputeImageDefault
     auto kernel = context.cl_context()->GetKernel(kernel_key.str());
 
     int arg_idx = 0;
-    cl_int status = kernel.setArg(arg_idx, *x_img);
+    cl_int status = kernel->setArg(arg_idx, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *out_img);
+    status = kernel->setArg(++arg_idx, *out_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const float>(scale_h));
+    status = kernel->setArg(++arg_idx, static_cast<const float>(scale_h));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const float>(scale_w));
+    status = kernel->setArg(++arg_idx, static_cast<const float>(scale_w));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(in_dims_h));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(in_dims_h));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(out_dims_h));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(out_dims_h));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(in_dims_w));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(in_dims_w));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(out_dims_w));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(out_dims_w));
     CL_CHECK_FATAL(status);
 
 #ifndef LITE_SHUTDOWN_LOG
@@ -110,7 +110,7 @@ class NearestInterpComputeImageDefault
                     static_cast<cl::size_type>(default_work_size.data()[1]),
                     static_cast<cl::size_type>(default_work_size.data()[2])};
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/pad2d_image_compute.cc

@@ -114,27 +114,27 @@ class Pad2dCompute : public KernelLite<TARGET(kOpenCL),
     int pad_w1 = pad2d_param_->paddings[3];
     float pad_value = pad2d_param_->pad_value;
 
-    cl_int status = kernel.setArg(arg_idx++, *x_img);
+    cl_int status = kernel->setArg(arg_idx++, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, *out_img);
+    status = kernel->setArg(arg_idx++, *out_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, in_h);
+    status = kernel->setArg(arg_idx++, in_h);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, in_w);
+    status = kernel->setArg(arg_idx++, in_w);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, out_h);
+    status = kernel->setArg(arg_idx++, out_h);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, out_w);
+    status = kernel->setArg(arg_idx++, out_w);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, pad_h0);
+    status = kernel->setArg(arg_idx++, pad_h0);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, pad_h1);
+    status = kernel->setArg(arg_idx++, pad_h1);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, pad_w0);
+    status = kernel->setArg(arg_idx++, pad_w0);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, pad_w1);
+    status = kernel->setArg(arg_idx++, pad_w1);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(arg_idx++, pad_value);
+    status = kernel->setArg(arg_idx++, pad_value);
     CL_CHECK_FATAL(status);
 
     auto global_work_size =
@@ -143,7 +143,7 @@ class Pad2dCompute : public KernelLite<TARGET(kOpenCL),
                     static_cast<cl::size_type>(default_work_size[2])};
 
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/pool_buffer_compute.cc

@@ -76,37 +76,37 @@ class PoolCompute
     cl_int status;
     auto numel = out_dims.production();
     int arg_idx = 0;
-    status = kernel.setArg(arg_idx, static_cast<const int>(numel));
+    status = kernel->setArg(arg_idx, static_cast<const int>(numel));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *input_buf);
+    status = kernel->setArg(++arg_idx, *input_buf);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(in_dims[1]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(in_dims[1]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(in_dims[2]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(in_dims[2]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(in_dims[3]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(in_dims[3]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(out_dims[2]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(out_dims[2]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(out_dims[3]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(out_dims[3]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(ksize[0]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(ksize[0]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(ksize[1]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(ksize[1]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(strides[0]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(strides[0]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(strides[1]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(strides[1]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(paddings[0]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(paddings[0]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(paddings[2]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(paddings[2]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *output_buf);
+    status = kernel->setArg(++arg_idx, *output_buf);
     CL_CHECK_FATAL(status);
     auto global_work_size = cl::NDRange(static_cast<size_t>(numel));
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/pool_image_compute.cc

@@ -125,33 +125,33 @@ class PoolComputeImage2D : public KernelLite<TARGET(kOpenCL),
 #endif
     cl_int status;
     int arg_idx = 0;
-    status = kernel.setArg(arg_idx, *x_img);
+    status = kernel->setArg(arg_idx, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *out_img);
+    status = kernel->setArg(++arg_idx, *out_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(in_dims[2]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(in_dims[2]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(in_dims[3]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(in_dims[3]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(out_dims[2]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(out_dims[2]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(out_dims[3]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(out_dims[3]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(ksize[0]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(ksize[0]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(ksize[1]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(ksize[1]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(strides[0]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(strides[0]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(strides[1]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(strides[1]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(paddings[2]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(paddings[2]));
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, static_cast<const int>(paddings[0]));
+    status = kernel->setArg(++arg_idx, static_cast<const int>(paddings[0]));
     CL_CHECK_FATAL(status);
 
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/reshape_image_compute.cc

@@ -122,31 +122,31 @@ class ReshapeComputeFloatImage : public KernelLite<TARGET(kOpenCL),
 
     int arg_idx = 0;
     cl_int status;
-    status = kernel.setArg(arg_idx, *x_image);
+    status = kernel->setArg(arg_idx, *x_image);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *out_image);
+    status = kernel->setArg(++arg_idx, *out_image);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, out_C);
+    status = kernel->setArg(++arg_idx, out_C);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, out_H);
+    status = kernel->setArg(++arg_idx, out_H);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, out_W);
+    status = kernel->setArg(++arg_idx, out_W);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, in_W);
+    status = kernel->setArg(++arg_idx, in_W);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, in_H);
+    status = kernel->setArg(++arg_idx, in_H);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, in_Stride0);
+    status = kernel->setArg(++arg_idx, in_Stride0);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, in_Stride1);
+    status = kernel->setArg(++arg_idx, in_Stride1);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, in_Stride2);
+    status = kernel->setArg(++arg_idx, in_Stride2);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, out_Stride0);
+    status = kernel->setArg(++arg_idx, out_Stride0);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, out_Stride1);
+    status = kernel->setArg(++arg_idx, out_Stride1);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, out_Stride2);
+    status = kernel->setArg(++arg_idx, out_Stride2);
     CL_CHECK_FATAL(status);
 
     auto global_work_size =
@@ -155,7 +155,7 @@ class ReshapeComputeFloatImage : public KernelLite<TARGET(kOpenCL),
                     static_cast<size_t>(default_work_size.data()[2])};
 
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,

lite/kernels/opencl/scale_image_compute.cc

@@ -45,7 +45,7 @@ class ScaleComputeImage2D : public KernelLite<TARGET(kOpenCL),
 
     STL::stringstream kernel_key;
     kernel_key << kernel_func_name_ << build_options_ << time_stamp_;
-    kernel_ = context.cl_context()->GetKernel(kernel_key.str());
+    auto kernel = context.cl_context()->GetKernel(kernel_key.str());
   }
 
   void ReInitWhenNeeded() override {
@@ -82,19 +82,22 @@ class ScaleComputeImage2D : public KernelLite<TARGET(kOpenCL),
     auto& context = ctx_->As<OpenCLContext>();
     CHECK(context.cl_context() != nullptr);
 
-    auto kernel = kernel_;
+    std::stringstream kernel_key;
+    kernel_key << kernel_func_name_ << build_options_ << time_stamp_;
+    auto kernel = context.cl_context()->GetKernel(kernel_key.str());
+    ;
     cl_int status;
-    status = kernel.setArg(0, *x_img);
+    status = kernel->setArg(0, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(1, *out_img);
+    status = kernel->setArg(1, *out_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(2, scale);
+    status = kernel->setArg(2, scale);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(3, bias);
+    status = kernel->setArg(3, bias);
     CL_CHECK_FATAL(status);
 
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size_,
         cl::NullRange,
@@ -111,7 +114,7 @@ class ScaleComputeImage2D : public KernelLite<TARGET(kOpenCL),
   std::shared_ptr<cl::Event> event_{new cl::Event};
 
   param_t* scale_param_{nullptr};
-  cl::Kernel kernel_;
+  cl::Kernel kernel;
   bool first_epoch_for_reinit_{true};
   DDim last_x_dims_;
   DDim out_img_shape_ = DDim(std::vector<DDim::value_type>(

lite/kernels/opencl/slice_image_compute.cc

@@ -75,15 +75,15 @@ class SliceComputeImage2D : public KernelLite<TARGET(kOpenCL),
 
     cl_int status;
     int arg_idx = 0;
-    status = kernel.setArg(arg_idx, *x_img);
+    status = kernel->setArg(arg_idx, *x_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, *out_img);
+    status = kernel->setArg(++arg_idx, *out_img);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, start);
+    status = kernel->setArg(++arg_idx, start);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, end);
+    status = kernel->setArg(++arg_idx, end);
     CL_CHECK_FATAL(status);
-    status = kernel.setArg(++arg_idx, dim_w);
+    status = kernel->setArg(++arg_idx, dim_w);
     CL_CHECK_FATAL(status);
 
     const std::vector<size_t>& default_work_size =
@@ -97,7 +97,7 @@ class SliceComputeImage2D : public KernelLite<TARGET(kOpenCL),
                     static_cast<cl::size_type>(default_work_size.data()[2])};
 
     status = context.cl_context()->GetCommandQueue().enqueueNDRangeKernel(
-        kernel,
+        *kernel.get(),
         cl::NullRange,
         global_work_size,
         cl::NullRange,