depthwise_conv op kernel for gpu

src/framework/cl/cl_image.h

@@ -106,6 +106,14 @@ class CLImage {
     InitCLImage(context, command_queue, folder_converter);
     PADDLE_MOBILE_ENFORCE(tensor_dims_.size() == 4, " tensor dim is not 4");
   }
+  void InitDWImage(cl_context context, cl_command_queue command_queue) {
+    if (tensor_data_ == nullptr) {
+      PADDLE_MOBILE_THROW_EXCEPTION(" need call SetTensorData first");
+    }
+    CLImageConverterDWBlock *dw_converter = new CLImageConverterDWBlock();
+    InitCLImage(context, command_queue, dw_converter);
+    PADDLE_MOBILE_ENFORCE(tensor_dims_.size() == 4, " tensor dim is not 4");
+  }
 
   void InitEmptyImage(cl_context context, cl_command_queue command_queue,
                       const DDim &dim) {

src/framework/cl/cl_image_converter.cpp

@@ -297,5 +297,97 @@ void CLImageConverterNWBlock::ImageToNCHW(half_t *image, float *tensor,
   DLOG << " init done";
 }
 
+const DDim &CLImageConverterDWBlock::InitImageDimInfoWith(
+    const DDim &tensor_dim) {
+  PADDLE_MOBILE_ENFORCE(tensor_dim.size() == 4, " tensor dim is not 4");
+  size_t N, C, H, W;
+  N = tensor_dim[0];
+  C = tensor_dim[1];
+  H = tensor_dim[2];
+  W = tensor_dim[3];
+  size_t width = W * ((N + 3) / 4);
+  size_t height = C * H;
+  return make_ddim({width, height});
+}
+
+void CLImageConverterDWBlock::NCHWToImage(float *tensor, half_t *image,
+                                          const DDim &tensor_dim) {
+  size_t new_dims[] = {1, 1, 1, 1};
+  for (int j = 0; j < tensor_dim.size(); ++j) {
+    new_dims[4 - tensor_dim.size() + j] = tensor_dim[j];
+  }
+
+  size_t N, C, H, W;
+  N = new_dims[1];
+  C = new_dims[0];
+  H = new_dims[2];
+  W = new_dims[3];
+
+  DDim in_image_dim = InitImageDimInfoWith(tensor_dim);
+
+  DLOG << " tensor dim " << tensor_dim;
+  DLOG << " image dim " << in_image_dim;
+
+  size_t width = in_image_dim[0];
+  size_t height = in_image_dim[1];
+
+  int w_block = width / W;
+
+  float *p = tensor;
+  size_t i0 = 0;
+  for (int n = 0; n < N; n++) {
+    for (int c = 0; c < w_block * 4; c++) {
+      size_t i1 = i0 + (c / 4) * W;
+      for (int h = 0; h < H; h++) {
+        size_t i2 = (i1 << 2) + c % 4;
+        for (int w = 0; w < W; w++) {
+          if (c < C) {
+            // int x = (n * width * H + h * width + (c / 4) * W + w) * 4 +
+            // (c % 4);
+            image[i2] = Float2Half(*p);
+            i2 += 4;
+            p++;
+          } else {
+            image[i2] = 0.0;
+            i2 += 4;
+          }
+        }
+        i1 += width;
+      }
+    }
+    i0 += width * H;
+  }
+}
+
+void CLImageConverterDWBlock::ImageToNCHW(half_t *image, float *tensor,
+                                          const DDim &image_dim,
+                                          const DDim &tensor_dim) {
+  PADDLE_MOBILE_ENFORCE(tensor_dim.size() == 4, " tensor dim is not 4");
+  float *p = tensor;
+  int N = tensor_dim[1];
+  int C = tensor_dim[0];
+  int H = tensor_dim[2];
+  int W = tensor_dim[3];
+  int width = image_dim[0];
+  int height = image_dim[0];
+
+  size_t i0 = 0;
+  for (int n = 0; n < N; n++) {
+    for (int c = 0; c < C; c++) {
+      size_t i1 = i0 + (c / 4) * W;
+      for (int h = 0; h < H; h++) {
+        size_t i2 = (i1 << 2) + c % 4;
+        for (int w = 0; w < W; w++) {
+          *p = Half2Float(image[i2]);
+          i2 += 4;
+          p++;
+        }
+        i1 += width;
+      }
+    }
+    i0 += width * H;
+  }
+}
+
 }  // namespace framework
 }  // namespace paddle_mobile

src/framework/cl/cl_image_converter.h

@@ -69,6 +69,12 @@ class CLImageConverterNWBlock : public CLImageConverterBase {
   void ImageToNCHW(half_t *image, float *tensor, const DDim &image_dim,
                    const DDim &tensor_dim);
 };
+class CLImageConverterDWBlock : public CLImageConverterBase {
+  const DDim &InitImageDimInfoWith(const DDim &tensor_dim);
+  void NCHWToImage(float *tensor, half_t *image, const DDim &tensor_dim);
+  void ImageToNCHW(half_t *image, float *tensor, const DDim &image_dim,
+                   const DDim &tensor_dim);
+};
 
 }  // namespace framework
 }  // namespace paddle_mobile

src/operators/kernel/cl/conv_add_bn_relu_kernel.cpp

@@ -29,15 +29,6 @@ bool ConvAddBNReluKernel<GPU_CL, float>::Init(
           param->Paddings()[0] == param->Paddings()[1],
       "need equal");
 
-  auto filter_ddim = param->Filter()->dims();
-
-  std::vector<int64_t> filter_shape(
-      {filter_ddim[1], filter_ddim[0], filter_ddim[2], filter_ddim[3]});
-  framework::DDim ddim = framework::make_ddim(filter_shape);
-  if (filter_ddim[1] == 1) {
-    param->Filter()->Resize(ddim);
-  }
-
   param->Bias()->InitCLImage(cl_helper_.CLContext(),
                              cl_helper_.CLCommandQueue());
 
@@ -140,10 +131,10 @@ bool ConvAddBNReluKernel<GPU_CL, float>::Init(
 
     this->cl_helper_.AddKernel("conv_1x1", "conv_add_bn_relu_kernel.cl");
     DLOG << " conv add bn relu conv 1x1";
-  } else if (param->Filter()->dims()[0] == 1 &&
+  } else if (param->Filter()->dims()[1] == 1 &&
              param->Input()->dims()[1] == param->Output()->dims()[1] &&
              param->Filter()->dims()[2] == 3) {
-    param->Filter()->InitCLImage(cl_helper_.CLContext(),
+    param->Filter()->InitDWImage(cl_helper_.CLContext(),
                                  cl_helper_.CLCommandQueue());
     this->cl_helper_.AddKernel("depth_conv_3x3", "conv_add_bn_relu_kernel.cl");
     DLOG << " conv add bn relu depth_conv_3x3";