diff --git a/src/framework/cl/cl_helper.h b/src/framework/cl/cl_helper.h
index 8ebbcc911a558e3acbc5f54914300ca8226f0b0a..e1fdd54d6a1a506b817a6f6e464e951d082c6f9a 100644
--- a/src/framework/cl/cl_helper.h
+++ b/src/framework/cl/cl_helper.h
@@ -64,6 +64,17 @@ class CLHelper {
 
       auto work_size_2 = n * h;
 
+      return {work_size_0, work_size_1, work_size_2};
+    }else if(image_dim.size()==2){
+
+      auto image_width = image.ImageWidth();
+
+      auto work_size_0 = image_width / image_dim[1];
+
+      auto work_size_1 = image_dim[1];
+
+      auto work_size_2 = image_dim[0];
+
       return {work_size_0, work_size_1, work_size_2};
     }
     PADDLE_MOBILE_THROW_EXCEPTION("not support this dim, need imp");
diff --git a/src/framework/executor.cpp b/src/framework/executor.cpp
index 8b1a2cd8ec05c98321dfdc0366e01d1abca9e206..43725f6b2cb3f055844f3d2d9521f838cf9a36d4 100644
--- a/src/framework/executor.cpp
+++ b/src/framework/executor.cpp
@@ -37,7 +37,7 @@ limitations under the License. */
 #include "framework/cl/cl_image.h"
 #endif
 
-int debug_to = 4;
+int debug_to = 115;
 
 namespace paddle_mobile {
 namespace framework {
diff --git a/src/operators/kernel/cl/relu_kernel.cpp b/src/operators/kernel/cl/relu_kernel.cpp
index 71304b9c307f36f7a3db754a7a41958e206f77cd..ae40e8ae6adc307c405e3f5f65febbff174232c6 100644
--- a/src/operators/kernel/cl/relu_kernel.cpp
+++ b/src/operators/kernel/cl/relu_kernel.cpp
@@ -20,23 +20,23 @@ namespace operators {
 
 template <>
 bool ReluKernel<GPU_CL, float>::Init(ReluParam<GPU_CL>* param) {
-  this->cl_helper_.AddKernel("relu", "relu.cl");
+//  this->cl_helper_.AddKernel("relu", "relu.cl");
   return true;
 }
 
 template <>
 void ReluKernel<GPU_CL, float>::Compute(const ReluParam<GPU_CL>& param) {
-  auto kernel = this->cl_helper_.KernelAt(0);
-  const auto* input = param.InputX();
-  auto* output = param.Out();
-  auto default_work_size = this->cl_helper_.DefaultWorkSize(*output);
-  auto inputImage = input->GetCLImage();
-  auto outputImage = output->GetCLImage();
-  clSetKernelArg(kernel, 0, sizeof(cl_mem), &inputImage);
-  clSetKernelArg(kernel, 1, sizeof(cl_mem), &outputImage);
-  const size_t work_size[2] = {input->ImageWidth(), input->ImageHeight()};
-  clEnqueueNDRangeKernel(this->cl_helper_.CLCommandQueue(), kernel, 3, NULL,
-                         work_size, NULL, 0, NULL, NULL);
+//  auto kernel = this->cl_helper_.KernelAt(0);
+//  const auto* input = param.InputX();
+//  auto* output = param.Out();
+//  auto default_work_size = this->cl_helper_.DefaultWorkSize(*output);
+//  auto inputImage = input->GetCLImage();
+//  auto outputImage = output->GetCLImage();
+//  clSetKernelArg(kernel, 0, sizeof(cl_mem), &inputImage);
+//  clSetKernelArg(kernel, 1, sizeof(cl_mem), &outputImage);
+//  const size_t work_size[2] = {input->ImageWidth(), input->ImageHeight()};
+//  clEnqueueNDRangeKernel(this->cl_helper_.CLCommandQueue(), kernel, 3, NULL,
+//                         work_size, NULL, 0, NULL, NULL);
 }
 
 template class ReluKernel<GPU_CL, float>;
diff --git a/src/operators/kernel/cl/softmax_kernel.cpp b/src/operators/kernel/cl/softmax_kernel.cpp
index 1404ea40c703c8da2db09551fc6da440771f7366..304c716c6e5c2e3a5cfaef328d7df1535b335ff2 100644
--- a/src/operators/kernel/cl/softmax_kernel.cpp
+++ b/src/operators/kernel/cl/softmax_kernel.cpp
@@ -36,11 +36,14 @@ void SoftmaxKernel<GPU_CL, float>::Compute(const SoftmaxParam<GPU_CL> &param) {
   clSetKernelArg(kernel, 0, sizeof(cl_mem), &inputImage);
   clSetKernelArg(kernel, 1, sizeof(cl_mem), &outputImage);
   const auto &inputDim = input->dims();
-  int dims[4] = {inputDim[0], inputDim[1], inputDim[2], inputDim[3]};
-  clSetKernelArg(kernel, 2, sizeof(int), dims);
-  clSetKernelArg(kernel, 3, sizeof(int), dims + 1);
-  clSetKernelArg(kernel, 4, sizeof(int), dims + 2);
-  clSetKernelArg(kernel, 5, sizeof(int), dims + 3);
+  int dims[4] = {1, 1, 1, 1};
+  for (int i = 0; i < inputDim.size(); i++) {
+    dims[4-inputDim.size()+i] = inputDim[i];
+  }
+  clSetKernelArg(kernel, 2, sizeof(int), &dims);
+  clSetKernelArg(kernel, 3, sizeof(int), &dims[1]);
+  clSetKernelArg(kernel, 4, sizeof(int), &dims[2]);
+  clSetKernelArg(kernel, 5, sizeof(int), &dims[3]);
 
   clEnqueueNDRangeKernel(this->cl_helper_.CLCommandQueue(), kernel, 3, NULL,
                          default_work_size.data(), NULL, 0, NULL, NULL);