!7161 [MS][LITE][GPU]fix bug in op arithmetic

Merge pull request !7161 from chenzupeng/master-lite

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

@@ -50,6 +50,12 @@ std::vector<size_t> ArithmeticOpenCLKernel::InitGlobalSize() const {
 
 void ArithmeticOpenCLKernel::Image2dGetWorkGroupSize() {
   local_size_ = {16, 16};
+  if (out_tensors_[0]->shape().size() == 2) {
+    size_t H = out_tensors_[0]->shape()[0];
+    size_t W = UP_DIV(out_tensors_[0]->shape()[1], C4NUM);
+    global_size_ = {W, H};
+    return;
+  }
   if (out_tensors_[0]->GetFormat() == schema::Format_NC4HW4) {
     size_t H = out_tensors_[0]->Batch() * out_tensors_[0]->Height() * UP_DIV(out_tensors_[0]->Channel(), C4NUM);
     size_t W = out_tensors_[0]->Width();
@@ -74,6 +80,10 @@ void ArithmeticOpenCLKernel::BufferGetWorkGroupSize() {
 
 int ArithmeticOpenCLKernel::GetImageSize(size_t idx, std::vector<size_t> *img_size) {
   size_t im_dst_x, im_dst_y;
+  if (out_tensors_[0]->shape().size() == 2) {
+    im_dst_x = UP_DIV(out_tensors_[0]->shape()[1], C4NUM);
+    im_dst_y = out_tensors_[0]->shape()[0];
+  } else {
     if (out_tensors_[0]->GetFormat() == schema::Format_NC4HW4) {
       im_dst_x = out_tensors_[0]->Width();
       im_dst_y = out_tensors_[0]->Batch() * out_tensors_[0]->Height() * UP_DIV(out_tensors_[0]->Channel(), C4NUM);
@@ -87,6 +97,7 @@ int ArithmeticOpenCLKernel::GetImageSize(size_t idx, std::vector<size_t> *img_si
       MS_LOG(ERROR) << "Unsupport data format " << out_tensors_[0]->GetFormat();
       return RET_ERROR;
     }
+  }
 
   size_t img_dtype = CL_FLOAT;
   if (in_tensors_[0]->data_type() == kNumberTypeFloat16) {
@@ -335,22 +346,7 @@ int ArithmeticOpenCLKernel::Run() {
   }
   ocl_runtime_->SetKernelArg(kernel_, arg_idx++, out_tensors_[0]->data_c());
 
-  int H = 0;
-  int W = 0;
-  if (out_tensors_[0]->GetFormat() == schema::Format_NC4HW4) {
-    H = out_tensors_[0]->Batch() * out_tensors_[0]->Height() * UP_DIV(out_tensors_[0]->Channel(), C4NUM);
-    W = out_tensors_[0]->Width();
-  } else if (out_tensors_[0]->GetFormat() == schema::Format_NHWC4) {
-    H = out_tensors_[0]->Batch() * out_tensors_[0]->Height();
-    W = out_tensors_[0]->Width() * UP_DIV(out_tensors_[0]->Channel(), C4NUM);
-  } else if (out_tensors_[0]->GetFormat() == schema::Format_NC4) {
-    H = out_tensors_[0]->Batch();
-    W = UP_DIV(out_tensors_[0]->Channel(), C4NUM);
-  } else {
-    MS_LOG(ERROR) << "Error output type " << out_tensors_[0]->GetFormat();
-    return RET_ERROR;
-  }
-  cl_int2 output_shape{W, H};
+  cl_int2 output_shape{static_cast<int>(global_size_[0]), static_cast<int>(global_size_[1])};
   ocl_runtime_->SetKernelArg(kernel_, arg_idx++, output_shape);
   ocl_runtime_->RunKernel(kernel_, global_size_, local_size_, nullptr);
   return RET_OK;

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

@@ -162,4 +162,5 @@ kernel::LiteKernel *OpenCLBiasAddKernelCreator(const std::vector<lite::Tensor *>
 }
 
 REG_KERNEL(kGPU, kNumberTypeFloat32, PrimitiveType_BiasAdd, OpenCLBiasAddKernelCreator)
+REG_KERNEL(kGPU, kNumberTypeFloat16, PrimitiveType_BiasAdd, OpenCLBiasAddKernelCreator)
 }  // namespace mindspore::kernel

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

@@ -172,4 +172,5 @@ kernel::LiteKernel *OpenCLPReluKernelCreator(const std::vector<lite::Tensor *> &
 }
 
 REG_KERNEL(kGPU, kNumberTypeFloat32, PrimitiveType_PReLU, OpenCLPReluKernelCreator)
+REG_KERNEL(kGPU, kNumberTypeFloat16, PrimitiveType_PReLU, OpenCLPReluKernelCreator)
 }  // namespace mindspore::kernel