fix bug in arithmetic

mindspore/lite/src/runtime/kernel/opencl/cl/arithmetic.cl

@@ -15,6 +15,19 @@ __kernel void ElementAdd_IMG(__read_only image2d_t input_a, __read_only image2d_
   WRITE_IMAGE(output, (int2)(X, Y), a + b);
 }
 
+__kernel void ElementAddReLU_IMG(__read_only image2d_t input_a, __read_only image2d_t input_b,
+                             __write_only image2d_t output, const int2 output_shape) {
+  int X = get_global_id(0);
+  int Y = get_global_id(1);
+  if (X >= output_shape.x || Y >= output_shape.y) {
+    return;
+  }
+
+  FLT4 a = READ_IMAGE(input_a, smp_none, (int2)(X, Y));
+  FLT4 b = READ_IMAGE(input_b, smp_none, (int2)(X, Y));
+  WRITE_IMAGE(output, (int2)(X, Y), max(a + b, (FLT4)(0.f)));
+}
+
 __kernel void ElementSub_IMG(__read_only image2d_t input_a, __read_only image2d_t input_b,
                              __write_only image2d_t output, const int2 output_shape) {
   int X = get_global_id(0);

mindspore/lite/src/runtime/kernel/opencl/kernel/arithmetic.cc

@@ -262,6 +262,22 @@ int ArithmeticOpenCLKernel::Init() {
       return RET_ERROR;
   }
 
+  switch (arithmetic_parameter->activation_type_) {
+    case schema::ActivationType_NO_ACTIVATION:
+      break;
+    case schema::ActivationType_RELU:
+      if (op_parameter_->type_ == PrimitiveType_Add && element_flag_) {
+        kernel_name += "ReLU";
+      } else {
+        MS_LOG(ERROR) << "Only support ElementAdd + ReLU";
+        return RET_ERROR;
+      }
+      break;
+    default:
+      MS_LOG(ERROR) << "Error activation type " << arithmetic_parameter->activation_type_;
+      return RET_ERROR;
+  }
+
   lite::STATUS error_code = RET_OK;
 #ifdef PROGRAM_WITH_IL
   kernel_ = ocl_runtime_->GetKernelFromBinary(kernel_name);

mindspore/lite/src/runtime/kernel/opencl/kernel/scale.cc

@@ -115,8 +115,8 @@ int ScaleOpenCLKernel::InitBuffer() {
     std::vector<size_t> img_size;
     GetImageSize(0, &img_size);
     if (in_tensors_[1]->shape().size() == 1 && axis_ == 3) {
-      img_size[0] = 1;
-      img_size[1] = UP_DIV(in_tensors_[1]->shape()[0], C4NUM);
+      img_size[1] = 1;
+      img_size[0] = UP_DIV(in_tensors_[1]->shape()[0], C4NUM);
       scale_ptr_ = allocator->CreateImageFromHost(in_tensors_[1]->data_c(), in_tensors_[1]->ElementsNum(), img_size);
       offset_ptr_ = allocator->CreateImageFromHost(in_tensors_[2]->data_c(), in_tensors_[2]->ElementsNum(), img_size);
       return RET_OK;