fix tests compile errors

build.sh

@@ -510,8 +510,12 @@ gene_ocl_program() {
 
 build_opencl() {
     cd ${BASEPATH}
-    git submodule update --init third_party/OpenCL-Headers
-    git submodule update --init third_party/OpenCL-CLHPP
+    if [[ ! -d "third_party/OpenCL-Headers" ]]; then
+      git submodule update --init third_party/OpenCL-Headers
+    fi
+    if [[ ! -d "third_party/OpenCL-CLHPP" ]]; then
+      git submodule update --init third_party/OpenCL-CLHPP
+    fi
     if [[ "${OPENCL_OFFLINE_COMPILE}" == "on" ]]; then
         gene_ocl_program
     else
@@ -524,6 +528,7 @@ build_lite()
     echo "start build mindspore lite project"
 
     if [[ "${ENABLE_GPU}" == "on" ]]; then
+      echo "start build opencl"
       build_opencl
     fi
     if [[ "${LITE_PLATFORM}" == "x86_64" ]]; then

mindspore/lite/CMakeLists.txt

@@ -49,7 +49,6 @@ endif ()
 if (SUPPORT_GPU)
     add_definitions(-DUSE_OPENCL_WRAPPER)
     add_definitions(-DMS_OPENCL_PROFILE=false)
-    add_definitions(-DCL_HPP_TARGET_OPENCL_VERSION=200)
     add_compile_definitions(SUPPORT_GPU)
     if(OFFLINE_COMPILE)
         add_compile_definitions(PROGRAM_WITH_IL)

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

@@ -19,7 +19,7 @@
 #include "src/kernel_registry.h"
 #include "src/runtime/opencl/opencl_runtime.h"
 #include "src/runtime/kernel/opencl/kernel/concat.h"
-#include "src/backend/opencl/cl/fp32/concat.cl.inc"
+#include "src/runtime/kernel/opencl/cl/fp32/concat.cl.inc"
 
 using mindspore::kernel::KERNEL_ARCH::kGPU;
 using mindspore::lite::KernelRegistrar;
@@ -115,12 +115,16 @@ int GetBiggestDividerWithPriority(int number, int max_divider) {
   return 1;
 }
 
-void ConcatGetWorkGroup(const std::vector<size_t> &global, const std::vector<size_t> &local, int max_size) {
+void ConcatGetWorkGroup(const std::vector<size_t> &global, std::vector<size_t> *local, int max_size) {
   int x = std::min(GetBiggestDividerWithPriority(global[0], 8), 4);
   int yz = max_size / x;
   int y = std::min(std::min(GetBiggestDividerWithPriority(global[1], 8), yz), 8);
   int z = std::min(yz / y, DivideRoundUp(global[2], 2));
-  local = {static_cast<unsigned int>(x), static_cast<unsigned int>(y), static_cast<unsigned int>(z)};
+
+  local->clear();
+  local->push_back(x);
+  local->push_back(y);
+  local->push_back(z);
 }
 int ConcatOpenCLKernel::Run() {
   auto param = reinterpret_cast<ConcatParameter *>(this->opParameter);
@@ -144,7 +148,7 @@ int ConcatOpenCLKernel::Run() {
     uint32_t OW = output_shape[2];
     uint32_t OC = output_shape[3];
     global = {OH, OW, OC};  // HWC
-    ConcatGetWorkGroup(global, local, 384);
+    ConcatGetWorkGroup(global, &local, 384);
     std::cout << "local size=:" << std::endl;
     for (int i = 0; i < local.size(); i++) {
       std::cout << local[i] << "    ";
@@ -174,7 +178,7 @@ int ConcatOpenCLKernel::Run() {
     uint32_t OW = output_shape[2];
     uint32_t OC = output_shape[3];
     global = {OH, OW, OC};  // HWC
-    ConcatGetWorkGroup(global, local, 384);
+    ConcatGetWorkGroup(global, &local, 384);
     std::cout << "local size=:" << std::endl;
     for (int i = 0; i < local.size(); i++) {
       std::cout << local[i] << "    ";
@@ -196,8 +200,9 @@ int ConcatOpenCLKernel::Run() {
   return 0;
 }
 
-kernel::LiteKernel *OpenCLConcatKernelCreator(const std::vector<tensor::Tensor *> &inputs,
-                                              const std::vector<tensor::Tensor *> &outputs, OpParameter *opParameter,
+kernel::LiteKernel *OpenCLConcatKernelCreator(const std::vector<lite::tensor::Tensor *> &inputs,
+                                              const std::vector<lite::tensor::Tensor *> &outputs,
+                                              OpParameter *opParameter,
                                               const lite::Context *ctx, const kernel::KernelKey &desc) {
   auto *kernel = new ConcatOpenCLKernel(opParameter, inputs, outputs);
   auto ret = kernel->Init();

mindspore/lite/src/runtime/kernel/opencl/kernel/concat.h

@@ -20,24 +20,21 @@
 #include <vector>
 #include "ir/anf.h"
 #include "src/lite_kernel.h"
-#include "src/backend/arm/opclib/conv_parameter.h"
 #include "src/runtime/opencl/opencl_runtime.h"
-#include "src/backend/arm/opclib/concat.h"
+#include "src/runtime/kernel/arm/base/concat_base.h"
 
 namespace mindspore::kernel {
 
 class ConcatOpenCLKernel : public LiteKernel {
  public:
-  explicit ConcatOpenCLKernel(OpParameter *parameter, const std::vector<tensor::Tensor *> &inputs,
-                              const std::vector<tensor::Tensor *> &outputs)
+  explicit ConcatOpenCLKernel(OpParameter *parameter, const std::vector<lite::tensor::Tensor *> &inputs,
+                              const std::vector<lite::tensor::Tensor *> &outputs)
       : LiteKernel(parameter, inputs, outputs) {}
 
   ~ConcatOpenCLKernel() override{};
 
   int Init() override;
 
-  //  int InferShape() { return {}; };
-  int InferShape() {}
   int ReSize() override;
 
   int Run_axis0();

mindspore/lite/src/runtime/kernel/opencl/kernel/conv2d_transpose.h

@@ -39,7 +39,6 @@ class Conv2dTransposeOpenCLKernel : public LiteKernel {
   ~Conv2dTransposeOpenCLKernel() override {};
 
   int Init() override;
-  int InferShape() {}
   int ReSize() override;
   int Run() override;
   void PadWeight();

mindspore/lite/src/runtime/kernel/opencl/kernel/matmul.h

@@ -41,7 +41,6 @@ class MatMulOpenCLKernel : public LiteKernel {
   ~MatMulOpenCLKernel() override{};
 
   int Init() override;
-  int InferShape() {}
   int ReSize() override;
   int Run() override;
   void PadWeight();

mindspore/lite/test/CMakeLists.txt

@@ -265,10 +265,10 @@ endif()
 if (SUPPORT_GPU)
     set(TEST_SRC
             ${TEST_SRC}
-            ${TEST_DIR}/ut/stc/runtime/kernel/opencl/matmul_tests.cc
-            ${TEST_DIR}/ut/stc/runtime/kernel/opencl/depthwise_conv2d_tests.cc
-            ${TEST_DIR}/ut/stc/runtime/kernel/opencl/concat_tests.cc
-            ${TEST_DIR}/ut/stc/runtime/kernel/opencl/softmax_cl_tests.cc
+            ${TEST_DIR}/ut/src/runtime/kernel/opencl/matmul_tests.cc
+            ${TEST_DIR}/ut/src/runtime/kernel/opencl/depthwise_conv2d_tests.cc
+            ${TEST_DIR}/ut/src/runtime/kernel/opencl/concat_tests.cc
+            ${TEST_DIR}/ut/src/runtime/kernel/opencl/softmax_cl_tests.cc
             )
 endif()
 

mindspore/lite/test/ut/src/runtime/kernel/opencl/concat_test.cc → mindspore/lite/test/ut/src/runtime/kernel/opencl/concat_tests.cc

@@ -18,12 +18,10 @@
 #include "utils/log_adapter.h"
 #include "common/common_test.h"
 #include "mindspore/lite/src/runtime/opencl/opencl_runtime.h"
-#include "mindspore/lite/src/backend/opencl/subgraph_opencl_kernel.h"
-#include "mindspore/lite/src/backend/opencl/kernel/concat.h"
+#include "mindspore/lite/src/runtime/kernel/opencl/subgraph_opencl_kernel.h"
+#include "mindspore/lite/src/runtime/kernel/opencl/kernel/concat.h"
+
 
-using  mindspore::kernel;
-using  mindspore::lite;
-using  mindspore;
 int DivideRoundUp(int n, int div) {
   int q = n / div;
   return n % div == 0 ? q : q + 1;
@@ -96,7 +94,7 @@ void ConcatComputeByCPU_3input_dim4_axis3(float *input0, float *input1, float *i
 }
 
 namespace mindspore {
-class TestConcatOpenCL : public UT::Common {
+class TestConcatOpenCL : public mindspore::Common {
  public:
   TestConcatOpenCL(){}
 };
@@ -113,30 +111,31 @@ TEST_F(TestConcatOpenCL, ConcatFp32_2input_dim4_axis3) {
   output_shape[3] = DivideRoundUp(output_shape[3], 4) * 4;
   auto data_type = kNumberTypeFloat32;
   auto tensor_type = schema::NodeType_ValueNode;
-  std::vector<tensor::Tensor *> inputs;
+  std::vector<lite::tensor::Tensor *> inputs;
   for (auto &shape : input_shapes) {
-    inputs.push_back(new tensor::Tensor(data_type, shape, schema::Format_NHWC, tensor_type));
+    inputs.push_back(new lite::tensor::Tensor(data_type, shape, schema::Format_NHWC, tensor_type));
   }
-  auto *output_tensor = new tensor::Tensor(data_type, output_shape, schema::Format_NHWC, tensor_type);
-  std::vector<tensor::Tensor *> outputs{output_tensor};
+  auto *output_tensor = new lite::tensor::Tensor(data_type, output_shape, schema::Format_NHWC, tensor_type);
+  std::vector<lite::tensor::Tensor *> outputs{output_tensor};
   std::cout << "input_shapes size=: " << input_shapes.size() << std::endl;
   MS_LOG(INFO) << "initialize tensors";
   auto param = new ConcatParameter();
   param->axis_ = 3;
-  auto *concat_kernel = new ConcatOpenCLKernel(reinterpret_cast<OpParameter *>(param), inputs, outputs);
+  auto *concat_kernel = new kernel::ConcatOpenCLKernel(reinterpret_cast<OpParameter *>(param), inputs, outputs);
   concat_kernel->Init();
 
   MS_LOG(INFO) << "initialize sub_graph";
-  std::vector<LiteKernel *> kernels{concat_kernel};
-  auto *sub_graph = new SubGraphOpenCLKernel(inputs, outputs, kernels, kernels, kernels);
+  std::vector<kernel::LiteKernel *> kernels{concat_kernel};
+  auto *sub_graph = new kernel::SubGraphOpenCLKernel(inputs, outputs, kernels, kernels, kernels);
   sub_graph->Init();
 
   MS_LOG(INFO) << "initialize input data";
   srand(time(NULL));
   for (auto &input_tensor : inputs) {
     auto input_data = reinterpret_cast<float *>(input_tensor->Data());
+    static unsigned int seed = 123;
     for (int i = 0; i < input_tensor->ElementsNum(); ++i) {
-      input_data[i] = static_cast<float>(rand_r() % 10 + 1);
+      input_data[i] = static_cast<float>(rand_r(&seed) % 10 + 1);
     }
     printf("\n");
   }

mindspore/lite/test/ut/src/runtime/kernel/opencl/depthwise_conv2d_tests.cc

@@ -23,9 +23,6 @@
 #include "mindspore/lite/src/runtime/kernel/opencl/subgraph_opencl_kernel.h"
 #include "mindspore/lite/src/runtime/kernel/opencl/kernel/depthwise_conv2d.h"
 
-using mindspore::kernel;
-using mindspore::lite;
-using mindspore;
 
 #define SAFE_DELETE_ARRAY(a) \
   if (a != nullptr) {        \
@@ -39,12 +36,12 @@ using mindspore;
   }
 
 namespace mindspore {
-class TestConvolutionDwOpenCL : public UT::Common {
+class TestConvolutionDwOpenCL : public mindspore::Common {
  public:
   TestConvolutionDwOpenCL(){}
 };
 
-void DepthWiseTestMain(const ConvParameter *conv_param, float_t *input_data, float_t *weight_data, float_t *gnd_data,
+void DepthWiseTestMain(ConvParameter *conv_param, float_t *input_data, float_t *weight_data, float_t *gnd_data,
                        schema::Format format, bool is_compare = true) {
   auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
   ocl_runtime->Init();
@@ -92,13 +89,13 @@ void DepthWiseTestMain(const ConvParameter *conv_param, float_t *input_data, flo
   inputs[1]->SetData(packed_weight);
   inputs[2]->SetData(bias_data);
 
-  OpParameter * parameter = conv_param;
-  auto *pKernel = new DepthwiseConv2dOpenCLKernel(parameter, inputs, outputs);
+  OpParameter * parameter = reinterpret_cast<OpParameter *>(conv_param);
+  auto *pKernel = new kernel::DepthwiseConv2dOpenCLKernel(parameter, inputs, outputs);
   pKernel->Init();
 
-  std::vector<LiteKernel *> kernels{pKernel};
+  std::vector<kernel::LiteKernel *> kernels{pKernel};
   std::vector<lite::tensor::Tensor *> inputs_{tensor_a};
-  auto *pGraph = new SubGraphOpenCLKernel(inputs_, outputs, kernels, kernels, kernels);
+  auto *pGraph = new kernel::SubGraphOpenCLKernel(inputs_, outputs, kernels, kernels, kernels);
   pGraph->Init();
 
   // freamework to do!!!
@@ -141,7 +138,7 @@ void DepthWiseTestMain(const ConvParameter *conv_param, float_t *input_data, flo
     }
     std::cout << std::endl;
     // compare
-    UT::Common::CompareOutputData(packed_output, packed_correct_data, packed_output_size, 0.00001);
+    Common::CompareOutputData(packed_output, packed_correct_data, packed_output_size, 0.00001);
     SAFE_DELETE_ARRAY(packed_correct_data)
   }
 
@@ -202,7 +199,7 @@ TEST_F(TestConvolutionDwOpenCL, NoPadNC4HW4Fp32) {
                       2.2294958, 1.6570128, 2.465089,  1.4294086, 2.7941442, 1.7871612, 2.188921, 1.0601988};
 
   DepthWiseTestMain(conv_param, input_data, weight_data, gnd_data, schema::Format_NC4HW4);
-  opencl::OpenCLRuntime::DeleteInstance();
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 
 TEST_F(TestConvolutionDwOpenCL, PadNC4HW4Fp32) {
@@ -275,7 +272,7 @@ TEST_F(TestConvolutionDwOpenCL, PadNC4HW4Fp32) {
                       1.0517888,  0.59817517, 0.75649744, 1.2075498,  0.38804203};
 
   DepthWiseTestMain(conv_param, input_data, weight_data, gnd_data, schema::Format_NC4HW4);
-  opencl::OpenCLRuntime::DeleteInstance();
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 
 TEST_F(TestConvolutionDwOpenCL, NoPadNHWC4Fp32) {
@@ -321,7 +318,7 @@ TEST_F(TestConvolutionDwOpenCL, NoPadNHWC4Fp32) {
                       2.2294958, 1.6570128, 2.465089,  1.4294086, 2.7941442, 1.7871612, 2.188921, 1.0601988};
 
   DepthWiseTestMain(conv_param, input_data, weight_data, gnd_data, schema::Format_NHWC4);
-  opencl::OpenCLRuntime::DeleteInstance();
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 
 TEST_F(TestConvolutionDwOpenCL, PadNHWC4Fp32) {
@@ -394,7 +391,7 @@ TEST_F(TestConvolutionDwOpenCL, PadNHWC4Fp32) {
                       1.0517888,  0.59817517, 0.75649744, 1.2075498,  0.38804203};
 
   DepthWiseTestMain(conv_param, input_data, weight_data, gnd_data, schema::Format_NHWC4);
-  opencl::OpenCLRuntime::DeleteInstance();
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 
 
@@ -474,13 +471,13 @@ TEST_F(TestConvolutionDwOpenCL, ConvDwNoPadFp32) {
   inputs[1]->SetData(packed_weight);
   inputs[2]->SetData(bias_data);
 
-  OpParameter * parameter = conv_param;
-  auto *pKernel = new DepthwiseConv2dOpenCLKernel(parameter, inputs, outputs);
+  OpParameter * parameter = reinterpret_cast<OpParameter *>(conv_param);
+  auto *pKernel = new kernel::DepthwiseConv2dOpenCLKernel(parameter, inputs, outputs);
   pKernel->Init();
 
-  std::vector<LiteKernel *> kernels{pKernel};
+  std::vector<kernel::LiteKernel *> kernels{pKernel};
   std::vector<lite::tensor::Tensor *> inputs_{tensor_a};
-  auto *pGraph = new SubGraphOpenCLKernel(inputs_, outputs, kernels, kernels, kernels);
+  auto *pGraph = new kernel::SubGraphOpenCLKernel(inputs_, outputs, kernels, kernels, kernels);
   pGraph->Init();
 
   // freamework to do!!!
@@ -517,7 +514,7 @@ TEST_F(TestConvolutionDwOpenCL, ConvDwNoPadFp32) {
   }
   std::cout << std::endl;
   // compare
-  CompareOutputData(packed_output, packed_correct_data, packed_output_size, 0.00001);
+  Common::CompareOutputData(packed_output, packed_correct_data, packed_output_size, 0.00001);
 
   for (auto tensor : inputs) {
     tensor->SetData(nullptr);
@@ -530,7 +527,7 @@ TEST_F(TestConvolutionDwOpenCL, ConvDwNoPadFp32) {
   SAFE_DELETE_PTR(pKernel)
   SAFE_DELETE_PTR(pGraph)
   MS_LOG(INFO) << "TestConvolutionDwNoPadFp32 passed";
-  opencl::OpenCLRuntime::DeleteInstance();
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 
 TEST_F(TestConvolutionDwOpenCL, ConvDwPadFp32) {
@@ -637,13 +634,13 @@ TEST_F(TestConvolutionDwOpenCL, ConvDwPadFp32) {
   inputs[1]->SetData(packed_weight);
   inputs[2]->SetData(bias_data);
 
-  OpParameter * parameter = conv_param;
-  auto *pKernel = new DepthwiseConv2dOpenCLKernel(parameter, inputs, outputs);
+  OpParameter * parameter = reinterpret_cast<OpParameter *>(conv_param);
+  auto *pKernel = new kernel::DepthwiseConv2dOpenCLKernel(parameter, inputs, outputs);
   pKernel->Init();
 
-  std::vector<LiteKernel *> kernels{pKernel};
+  std::vector<kernel::LiteKernel *> kernels{pKernel};
   std::vector<lite::tensor::Tensor *> inputs_{tensor_a};
-  auto *pGraph = new SubGraphOpenCLKernel(inputs_, outputs, kernels, kernels, kernels);
+  auto *pGraph = new kernel::SubGraphOpenCLKernel(inputs_, outputs, kernels, kernels, kernels);
   pGraph->Init();
 
   // freamework to do!!!
@@ -688,7 +685,7 @@ TEST_F(TestConvolutionDwOpenCL, ConvDwPadFp32) {
   }
   std::cout << std::endl;
   // compare
-  CompareOutputData(packed_output, packed_correct_data, packed_output_size, 0.00001);
+  Common::CompareOutputData(packed_output, packed_correct_data, packed_output_size, 0.00001);
 
   SAFE_DELETE_ARRAY(packed_input);
   SAFE_DELETE_ARRAY(packed_correct_data)
@@ -703,7 +700,7 @@ TEST_F(TestConvolutionDwOpenCL, ConvDwPadFp32) {
   SAFE_DELETE_PTR(pKernel)
   SAFE_DELETE_PTR(pGraph)
   MS_LOG(INFO) << "TestConvolutionDwPadFp32 passed";
-  opencl::OpenCLRuntime::DeleteInstance();
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 
 TEST_F(TestConvolutionDwOpenCL, ProfilingMobilenetv2) {
@@ -803,7 +800,7 @@ TEST_F(TestConvolutionDwOpenCL, ProfilingMobilenetv2) {
   }
   SAFE_DELETE_ARRAY(input_data);
   SAFE_DELETE_ARRAY(weight_data);
-  opencl::OpenCLRuntime::DeleteInstance();
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 
 }  // namespace mindspore

mindspore/lite/test/ut/src/runtime/kernel/opencl/matmul_tests.cc

@@ -22,10 +22,6 @@
 #include "mindspore/lite/src/runtime/kernel/opencl/subgraph_opencl_kernel.h"
 #include "mindspore/lite/src/runtime/kernel/opencl/kernel/matmul.h"
 
-// using namespace mindspore::kernel;
-// using namespace mindspore::lite;
-// using namespace mindspore;
-
 namespace mindspore {
 class TestMatMulOpenCL : public mindspore::Common {
  public:
@@ -53,11 +49,11 @@ TEST_F(TestMatMulOpenCL, MatMulFp32) {
   lite::tensor::Tensor *tensor_out = new lite::tensor::Tensor(TypeId(kNumberTypeFloat32), {1, co});
   std::vector<lite::tensor::Tensor *> inputs{tensor_x, tensor_w};
   std::vector<lite::tensor::Tensor *> outputs{tensor_out};
-  auto *arith_kernel = new MatMulOpenCLKernel(nullptr, inputs, outputs, false);
+  auto *arith_kernel = new kernel::MatMulOpenCLKernel(nullptr, inputs, outputs, false);
   arith_kernel->Init();
 
   std::vector<LiteKernel *> kernels{arith_kernel};
-  auto *pGraph = new SubGraphOpenCLKernel(inputs, outputs, kernels, kernels, kernels);
+  auto *pGraph = new kernel::SubGraphOpenCLKernel(inputs, outputs, kernels, kernels, kernels);
   pGraph->Init();
 
   memcpy(inputs[0]->Data(), input_data, sizeof(float) * ci);

mindspore/lite/test/ut/src/runtime/kernel/opencl/softmax_cl_tests.cc

@@ -22,10 +22,6 @@
 #include "mindspore/lite/src/runtime/kernel/opencl/subgraph_opencl_kernel.h"
 #include "mindspore/lite/src/runtime/kernel/opencl/kernel/softmax.h"
 
-// using namespace mindspore::kernel;
-// using namespace mindspore::lite;
-// using namespace mindspore;
-
 namespace mindspore {
 
 class TestSoftmaxOpenCL : public mindspore::Common {};
@@ -53,12 +49,12 @@ TEST_F(TestSoftmaxOpenCL, SoftmaxFp32) {
   std::vector<lite::tensor::Tensor *> outputs{tensor_out};
 
   MS_LOG(INFO) << "create OpenCL Kernel";
-  auto *Softmax_kernel = new SoftmaxOpenCLKernel(reinterpret_cast<OpParameter *>(param), inputs, outputs);
+  auto *Softmax_kernel = new kernel::SoftmaxOpenCLKernel(reinterpret_cast<OpParameter *>(param), inputs, outputs);
   Softmax_kernel->Init();
   std::vector<LiteKernel *> kernels{Softmax_kernel};
 
   MS_LOG(INFO) << "create SubGraphOpenCLKernel";
-  auto *pGraph = new SubGraphOpenCLKernel(inputs, outputs, kernels, kernels, kernels);
+  auto *pGraph = new kernel::SubGraphOpenCLKernel(inputs, outputs, kernels, kernels, kernels);
   pGraph->Init();
 
   MS_LOG(INFO) << "initialize data";