diff --git a/src/framework/cl/cl_image.h b/src/framework/cl/cl_image.h
index 9bad4bb6124a2102646c273036ee0d8b86a06191..f7d86ec8532b8557bb51d088bdae10c92dfe77fe 100644
--- a/src/framework/cl/cl_image.h
+++ b/src/framework/cl/cl_image.h
@@ -50,7 +50,11 @@ class CLImage {
     if (tensor_data_ == nullptr) {
       PADDLE_MOBILE_THROW_EXCEPTION(" need call SetTensorData first");
     }
-    InitCLImage(context, tensor_data_, tensor_dims_);
+    if (tensor_dims_.size() <= 2) {
+      InitCLImage2C(context, tensor_data_, tensor_dims_);
+    } else {
+      InitCLImage(context, tensor_data_, tensor_dims_);
+    }
     delete[](tensor_data_);
     tensor_data_ = nullptr;
     initialized_ = true;
@@ -118,6 +122,58 @@ class CLImage {
   const DDim &dims() const { return tensor_dims_; }
 
  private:
+  void InitCLImage2C(cl_context context, float *tensor_data, const DDim &dim) {
+    assert(dim.size() <= 2);
+    int tdim[2] = {1, 1};
+    if (dim.size() == 1) {
+      tdim[1] = dim[0];
+    } else {
+      tdim[0] = dim[0];
+      tdim[1] = dim[1];
+    }
+    int width = tdim[1] + 3 / 4;
+    int height = tdim[0];
+    std::unique_ptr<half_t[]> imageData{};
+    if (tensor_data) {
+      imageData.reset(new half_t[width * height * 4]);
+      for (int h = 0; h < tdim[0]; h++) {
+        for (int w = 0; w < tdim[1]; w++) {
+          imageData[(h * width + w / 4) * 4 + (w % 4)] = Float2Half(tensor_data[h * tdim[1] + w]);
+        }
+      }
+    }
+    InitCLImage(context, width, height, imageData.get());
+  }
+
+  void InitCLImage(cl_context context, int width, int height, void *data) {
+    cl_image_format cf = {.image_channel_order = CL_RGBA,
+                          .image_channel_data_type = CL_HALF_FLOAT};
+    cl_image_desc cid = {
+      .image_type = CL_MEM_OBJECT_IMAGE2D,
+      .image_width = width,
+      .image_height = height,
+      .image_depth = 1,
+      .image_array_size = 1,
+      .image_row_pitch = 0,
+      .image_slice_pitch = 0,
+      .num_mip_levels = 0,
+      .num_samples = 0,
+      // .buffer = nullptr
+    };
+    cid.buffer = nullptr;
+    cl_int err;
+    cl_image_ = clCreateImage(
+      context, CL_MEM_READ_WRITE | (data ? CL_MEM_COPY_HOST_PTR : 0),
+      &cf,   // const cl_image_format *image_format
+      &cid,  // const cl_image_desc *image_desc
+      data,  // void *host_ptr
+      &err
+    );
+    if (err != CL_SUCCESS) {
+      CL_CHECK_ERRORS(err);
+      PADDLE_MOBILE_THROW_EXCEPTION(" create image 2d error ");
+    }
+  }
   void InitCLImage(cl_context context, float *tensor_data, const DDim &dim) {
     DLOG << " tensor dim: " << dim;
     // NCHW -> [W * (C+3)/4, H * N]
@@ -160,17 +216,9 @@ class CLImage {
           for (int h = 0; h < H; h++) {
             size_t i2 = (i1 << 2) + c % 4;
             for (int w = 0; w < W; w++) {
-              if (i2 >= width * height * 4) {
-                printf("%d > %d ----> %d, %d, %d, %d --- %d, %d, %d\n", i2,
-                       width * height * 4, n, c, h, w, i0, i1, i2);
-              }
-              assert(i2 < width * height * 4);
-
               imageData[i2] = Float2Half(*p);
               i2 += 4;
               p++;
-              //              count++;
-              //              DLOG<<count;
             }
             i1 += width;
           }
@@ -178,36 +226,7 @@ class CLImage {
         i0 += width * H;
       }
     }
-    cl_int err;
-    DLOG << " image width: " << width;
-    DLOG << " image height: " << height;
-
-    cl_image_format cf = {.image_channel_order = CL_RGBA,
-                          .image_channel_data_type = CL_HALF_FLOAT};
-    cl_image_desc cid = {
-        .image_type = CL_MEM_OBJECT_IMAGE2D,
-        .image_width = width,
-        .image_height = height,
-        .image_depth = 1,
-        .image_array_size = 1,
-        .image_row_pitch = 0,
-        .image_slice_pitch = 0,
-        .num_mip_levels = 0,
-        .num_samples = 0,
-        // .buffer = nullptr
-    };
-    cid.buffer = nullptr;
-    cl_image_ = clCreateImage(
-        context, CL_MEM_READ_WRITE | (imageData ? CL_MEM_COPY_HOST_PTR : 0),
-        &cf,   // const cl_image_format *image_format
-        &cid,  // const cl_image_desc *image_desc
-        reinterpret_cast<void *>(imageData.get()),  // void *host_ptr
-        &err);
-
-    if (err != CL_SUCCESS) {
-      CL_CHECK_ERRORS(err);
-      PADDLE_MOBILE_THROW_EXCEPTION(" create image 2d error ");
-    }
+    InitCLImage(context, width, height, imageData.get());
   }
 
   bool initialized_ = false;
diff --git a/src/operators/kernel/cl/reshape_kernel.cpp b/src/operators/kernel/cl/reshape_kernel.cpp
index 877a325636a223913ebd10eb5724509719ac5717..210932337ce676bbeff3e04f1c2e46b3051bc123 100644
--- a/src/operators/kernel/cl/reshape_kernel.cpp
+++ b/src/operators/kernel/cl/reshape_kernel.cpp
@@ -34,8 +34,14 @@ void ReshapeKernel<GPU_CL, float>::Compute(const ReshapeParam<GPU_CL> &param) {
   clSetKernelArg(kernel, 1, sizeof(cl_mem), &outputImage);
   const auto &inputDim = input->dims();
   const auto &outputDim = output->dims();
-  int dims[4] = {inputDim[0], inputDim[1], inputDim[2], inputDim[3]};
-  int odims[4] = {outputDim[0], outputDim[1], outputDim[2], outputDim[3]};
+  int dims[4] = {1, 1, 1, 1};
+  int odims[4] = {1, 1, 1, 1};
+  for (int i = 0; i < inputDim.size(); i++) {
+    dims[4-inputDim.size()+i] = inputDim[i];
+  }
+  for (int i = 0; i < outputDim.size(); i++) {
+    odims[4-outputDim.size()+i] = outputDim[i];
+  }
   clSetKernelArg(kernel, 2, sizeof(int), dims);
   clSetKernelArg(kernel, 3, sizeof(int), dims + 1);
   clSetKernelArg(kernel, 4, sizeof(int), dims + 2);