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optimize opencl runtime

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pull/6930/head
wandongdong 4 years ago
parent 2a41f76f4f
commit 61551512af
33 changed files with 139 additions and 101 deletions
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10
mindspore/lite/src/lite_session.cc
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@ -26,9 +26,6 @@
#include "src/common/utils.h"
#include "src/common/graph_util.h"
#include "src/kernel_registry.h"
#if SUPPORT_GPU
#include "src/runtime/opencl/opencl_runtime.h"
#endif
namespace mindspore {
namespace lite {
@ -343,7 +340,7 @@ int LiteSession::Init(Context *context) {
}
#if SUPPORT_GPU
if (context_->device_type_ == DT_GPU) {
auto opencl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto opencl_runtime = ocl_runtime_wrap_.GetInstance();
opencl_runtime->SetFp16Enable(context_->float16_priority);
if (opencl_runtime->Init() != RET_OK) {
context_->device_type_ = DT_CPU;
@ -394,11 +391,6 @@ LiteSession::~LiteSession() {
for (auto *kernel : kernels_) {
delete kernel;
}
#if SUPPORT_GPU
if (context_->device_type_ == DT_GPU) {
lite::opencl::OpenCLRuntime::DeleteInstance();
}
#endif
delete this->context_;
delete this->executor;
this->executor = nullptr;

6
mindspore/lite/src/lite_session.h
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@ -30,6 +30,9 @@
#include "schema/model_generated.h"
#include "src/executor.h"
#include "src/tensor.h"
#if SUPPORT_GPU
#include "src/runtime/opencl/opencl_runtime.h"
#endif
namespace mindspore {
namespace lite {
@ -108,6 +111,9 @@ class LiteSession : public session::LiteSession {
std::unordered_map<std::string, mindspore::tensor::MSTensor *> output_tensor_map_;
Executor *executor = nullptr;
std::atomic<bool> is_running_ = false;
#if SUPPORT_GPU
opencl::OpenCLRuntimeWrapper ocl_runtime_wrap_;
#endif
};
} // namespace lite
} // namespace mindspore

2
mindspore/lite/src/runtime/kernel/opencl/kernel/gather.cc
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@ -54,7 +54,7 @@ int GatherOpenCLKernel::Init() {
auto indices_tensor = in_tensors_.at(1);
int indices_num = indices_tensor->ElementsNum();
bool isIndicesInt32 = indices_tensor->data_type() == kNumberTypeInt32;
auto allocator = lite::opencl::OpenCLRuntime::GetInstance()->GetAllocator();
auto allocator = ocl_runtime_->GetAllocator();
if (!isIndicesInt32) {
indices_data_ = reinterpret_cast<int32_t *>(allocator->Malloc(sizeof(int32_t) * indices_num));
if (indices_data_ == nullptr) {

12
mindspore/lite/src/runtime/kernel/opencl/opencl_kernel.h
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@ -38,15 +38,10 @@ class OpenCLKernel : public LiteKernel {
explicit OpenCLKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
const std::vector<lite::Tensor *> &outputs)
: LiteKernel(parameter, inputs, outputs, nullptr, nullptr) {
ocl_runtime_ = lite::opencl::OpenCLRuntime::GetInstance();
ocl_runtime_ = ocl_runtime_wrap_.GetInstance();
}
~OpenCLKernel() {
if (ocl_runtime_ != nullptr) {
lite::opencl::OpenCLRuntime::DeleteInstance();
ocl_runtime_ = nullptr;
}
}
~OpenCLKernel() {}
virtual int Init() { return RET_ERROR; }
virtual int Prepare() { return RET_ERROR; }
@ -69,7 +64,8 @@ class OpenCLKernel : public LiteKernel {
schema::Format in_ori_format_{schema::Format::Format_NHWC};
schema::Format out_ori_format_{schema::Format::Format_NHWC4};
schema::Format op_format_{schema::Format::Format_NHWC4};
lite::opencl::OpenCLRuntime *ocl_runtime_{nullptr};
lite::opencl::OpenCLRuntimeWrapper ocl_runtime_wrap_;
lite::opencl::OpenCLRuntime *ocl_runtime_;
};
} // namespace mindspore::kernel

6
mindspore/lite/src/runtime/kernel/opencl/subgraph_opencl_kernel.cc
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@ -17,7 +17,6 @@
#include "src/runtime/kernel/opencl/subgraph_opencl_kernel.h"
#include <set>
#include "src/runtime/opencl/opencl_executor.h"
#include "src/runtime/opencl/opencl_runtime.h"
#include "src/runtime/kernel/opencl/utils.h"
#include "include/errorcode.h"
#include "src/common/utils.h"
@ -161,7 +160,6 @@ int SubGraphOpenCLKernel::GenToFormatOp(const std::vector<lite::Tensor *> &in_te
}
int SubGraphOpenCLKernel::Init() {
ocl_runtime_ = lite::opencl::OpenCLRuntime::GetInstance();
allocator_ = ocl_runtime_->GetAllocator();
MS_LOG(DEBUG) << "input num=" << in_tensors_.size() << ", output num=" << out_tensors_.size();
for (const auto tensor : in_tensors_) {
@ -308,10 +306,6 @@ int SubGraphOpenCLKernel::UnInit() {
nodes_.clear();
in_convert_ops_.clear();
out_convert_ops_.clear();
if (ocl_runtime_ != nullptr) {
lite::opencl::OpenCLRuntime::DeleteInstance();
ocl_runtime_ = nullptr;
}
return RET_OK;
}

5
mindspore/lite/src/runtime/kernel/opencl/subgraph_opencl_kernel.h
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@ -36,7 +36,9 @@ class SubGraphOpenCLKernel : public SubGraphKernel {
const std::vector<kernel::LiteKernel *> outKernels,
const std::vector<kernel::LiteKernel *> nodes, const lite::InnerContext *ctx = nullptr,
const mindspore::lite::PrimitiveC *primitive = nullptr)
: SubGraphKernel(inputs, outputs, inKernels, outKernels, nodes, ctx, primitive) {}
: SubGraphKernel(inputs, outputs, inKernels, outKernels, nodes, ctx, primitive) {
ocl_runtime_ = ocl_runtime_wrap_.GetInstance();
}
~SubGraphOpenCLKernel() override;
int Init() override;
@ -64,6 +66,7 @@ class SubGraphOpenCLKernel : public SubGraphKernel {
std::vector<OpenCLToFormatParameter *> out_parameters_;
std::vector<LiteKernel *> in_convert_ops_;
std::vector<LiteKernel *> out_convert_ops_;
lite::opencl::OpenCLRuntimeWrapper ocl_runtime_wrap_;
lite::opencl::OpenCLRuntime *ocl_runtime_{nullptr};
};
} // namespace mindspore::kernel

62
mindspore/lite/src/runtime/kernel/opencl/utils.cc
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@ -15,9 +15,11 @@
*/
#include "src/runtime/kernel/opencl/utils.h"
#include <fstream>
#include <algorithm>
#include <vector>
#include "src/kernel_registry.h"
#include "src/runtime/opencl/opencl_runtime.h"
using mindspore::lite::KernelRegistrar;
@ -221,4 +223,64 @@ std::string CLErrorCode(cl_int error_code) {
return "Unknown OpenCL error code";
}
}
void Write2File(void *mem, const std::string &file_name, int size) {
std::fstream os;
os.open(file_name, std::ios::out | std::ios::binary);
os.write(static_cast<char *>(mem), size);
os.close();
}
void PrintTensor(lite::Tensor *tensor, int num, const std::string &out_file) {
if (tensor->data_c() == nullptr) {
return;
}
auto runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
runtime->SyncCommandQueue();
auto allocator = runtime->GetAllocator();
auto origin_data = tensor->data_c();
allocator->MapBuffer(origin_data, CL_MAP_READ, nullptr, true);
tensor->SetData(origin_data);
auto Height = tensor->shape().size() == 4 ? tensor->Height() : 1;
auto Width = tensor->shape().size() == 4 ? tensor->Width() : 1;
auto SLICES = UP_DIV(tensor->Channel(), C4NUM);
auto alignment = runtime->GetImagePitchAlignment();
auto dtype_size = tensor->data_type() == kNumberTypeFloat16 ? sizeof(cl_half4) : sizeof(cl_float4);
auto row_pitch = (Width * SLICES + alignment - 1) / alignment * alignment * dtype_size;
auto row_size = Width * SLICES * dtype_size;
std::cout << "tensor->GetFormat() =" << tensor->GetFormat() << "\n";
std::cout << "Height =" << Height << "\n";
std::cout << "Width =" << Width << "\n";
std::cout << "SLICES =" << SLICES << "\n";
std::cout << "image_alignment =" << alignment << "\n";
std::cout << "dtype_size =" << dtype_size << "\n";
std::cout << "row_pitch =" << row_pitch << "\n";
std::cout << "row_size =" << row_size << "\n";
std::cout << "tensor->Size() =" << tensor->Size() << "\n";
std::vector<char> data(tensor->Size());
for (int i = 0; i < Height; ++i) {
memcpy(static_cast<char *>(data.data()) + i * row_size, static_cast<char *>(origin_data) + i * row_pitch, row_size);
}
std::cout << "shape=(";
for (auto x : tensor->shape()) {
printf("%3d,", x);
}
printf("): ");
for (size_t i = 0; i < num && i < tensor->ElementsNum(); ++i) {
if (tensor->data_type() == kNumberTypeFloat16)
printf("%zu %6.3f | ", i, (reinterpret_cast<float16_t *>(data.data()))[i]);
else
printf("%zu %6.3f | ", i, (reinterpret_cast<float *>(data.data()))[i]);
}
printf("\n");
if (!out_file.empty()) {
Write2File(data.data(), out_file, tensor->Size());
}
allocator->UnmapBuffer(origin_data);
}
} // namespace mindspore::kernel

4
mindspore/lite/src/runtime/kernel/opencl/utils.h
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@ -44,6 +44,10 @@ std::vector<size_t> GetCommonLocalSize(const std::vector<size_t> &global, int ma
std::string CLErrorCode(cl_int error_code);
void Write2File(void *mem, const std::string &file_name, int size);
void PrintTensor(lite::Tensor *tensor, int num = 10, const std::string &out_file = "");
template <class T1, class T2>
void PackNCHWToNC4HW4(void *src, void *dst, int batch, int plane, int channel, const std::function<T2(T1)> &to_dtype) {
int c4 = UP_DIV(channel, C4NUM);

7
mindspore/lite/src/runtime/opencl/opencl_executor.h
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@ -27,11 +27,7 @@
namespace mindspore::lite::opencl {
class OpenCLExecutor : Executor {
public:
OpenCLExecutor() : Executor() {
auto ocl_runtime = OpenCLRuntime::GetInstance();
allocator_ = ocl_runtime->GetAllocator();
OpenCLRuntime::DeleteInstance();
}
OpenCLExecutor() : Executor() { allocator_ = ocl_runtime.GetInstance()->GetAllocator(); }
int Prepare(const std::vector<kernel::LiteKernel *> &kernels);
@ -42,6 +38,7 @@ class OpenCLExecutor : Executor {
protected:
InnerContext *context = nullptr;
OpenCLAllocator *allocator_;
OpenCLRuntimeWrapper ocl_runtime;
};
} // namespace mindspore::lite::opencl
#endif

7
mindspore/lite/src/runtime/opencl/opencl_runtime.cc
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@ -393,11 +393,16 @@ int OpenCLRuntime::RunKernel(const cl::Kernel &kernel, const std::vector<size_t>
cl::Event event;
cl_int ret = CL_SUCCESS;
ret = command_queue->enqueueNDRangeKernel(kernel, cl::NullRange, global_range, local_range, nullptr, &event);
if (ret != CL_SUCCESS) {
MS_LOG(ERROR) << "Kernel execute failed:" << CLErrorCode(ret);
return RET_ERROR;
}
static int cnt = 0;
const int flush_period = 10;
if (cnt % flush_period == 0) {
command_queue->flush();
}
cnt++;
MS_LOG(DEBUG) << "RunKernel success!";
#if MS_OPENCL_PROFILE
event.wait();

18
mindspore/lite/src/runtime/opencl/opencl_runtime.h
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@ -37,11 +37,10 @@ struct GpuInfo {
int model_num = 0;
float opencl_version = 0;
};
class OpenCLRuntimeWrapper;
class OpenCLRuntime {
public:
static OpenCLRuntime *GetInstance();
static void DeleteInstance();
friend OpenCLRuntimeWrapper;
~OpenCLRuntime();
OpenCLRuntime(const OpenCLRuntime &) = delete;
@ -138,6 +137,8 @@ class OpenCLRuntime {
int GetKernelMaxWorkGroupSize(cl_kernel kernel, cl_device_id device_id);
private:
static OpenCLRuntime *GetInstance();
static void DeleteInstance();
OpenCLRuntime();
GpuInfo ParseGpuInfo(std::string device_name, std::string device_version);
@ -169,5 +170,16 @@ class OpenCLRuntime {
void *handle_{nullptr};
};
class OpenCLRuntimeWrapper {
public:
OpenCLRuntimeWrapper() { ocl_runtime_ = OpenCLRuntime::GetInstance(); }
~OpenCLRuntimeWrapper() { OpenCLRuntime::DeleteInstance(); }
explicit OpenCLRuntimeWrapper(const OpenCLRuntime &) = delete;
OpenCLRuntimeWrapper &operator=(const OpenCLRuntime &) = delete;
OpenCLRuntime *GetInstance() { return ocl_runtime_; }
private:
OpenCLRuntime *ocl_runtime_{nullptr};
};
} // namespace mindspore::lite::opencl
#endif // MINDSPORE_LITE_SRC_OPENCL_RUNTIME_H_

15
mindspore/lite/test/ut/src/runtime/kernel/opencl/activation_tests.cc
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@ -82,7 +82,7 @@ TEST_F(TestActivationOpenCL, ReluFp_dim4) {
std::string in_file = "/data/local/tmp/in_data.bin";
std::string out_file = "/data/local/tmp/relu.bin";
MS_LOG(INFO) << "Relu Begin test!";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();
auto data_type = kNumberTypeFloat16;
@ -184,14 +184,13 @@ TEST_F(TestActivationOpenCL, ReluFp_dim4) {
delete input_tensor;
delete output_tensor;
delete sub_graph;
lite::opencl::OpenCLRuntime::DeleteInstance();
}
TEST_F(TestActivationOpenCL, Relu6Fp_dim4) {
std::string in_file = "/data/local/tmp/in_data.bin";
std::string out_file = "/data/local/tmp/relu6.bin";
MS_LOG(INFO) << "Relu6 Begin test!";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
auto data_type = kNumberTypeFloat16;
ocl_runtime->SetFp16Enable(data_type == kNumberTypeFloat16);
bool enable_fp16 = ocl_runtime->GetFp16Enable();
@ -296,14 +295,13 @@ TEST_F(TestActivationOpenCL, Relu6Fp_dim4) {
delete input_tensor;
delete output_tensor;
delete sub_graph;
lite::opencl::OpenCLRuntime::DeleteInstance();
}
TEST_F(TestActivationOpenCL, SigmoidFp_dim4) {
std::string in_file = "/data/local/tmp/in_data.bin";
std::string out_file = "/data/local/tmp/sigmoid.bin";
MS_LOG(INFO) << "Sigmoid Begin test!";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto data_type = kNumberTypeFloat32;
ocl_runtime->SetFp16Enable(data_type == kNumberTypeFloat16);
@ -408,14 +406,13 @@ TEST_F(TestActivationOpenCL, SigmoidFp_dim4) {
delete input_tensor;
delete output_tensor;
delete sub_graph;
lite::opencl::OpenCLRuntime::DeleteInstance();
}
TEST_F(TestActivationOpenCL, LeakyReluFp_dim4) {
std::string in_file = "/data/local/tmp/in_data.bin";
std::string out_file = "/data/local/tmp/leaky_relu.bin";
MS_LOG(INFO) << "Leaky relu Begin test!";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto data_type = kNumberTypeFloat16; // need modify
ocl_runtime->SetFp16Enable(data_type == kNumberTypeFloat16);
@ -519,14 +516,13 @@ TEST_F(TestActivationOpenCL, LeakyReluFp_dim4) {
delete param;
delete input_tensor;
delete output_tensor;
lite::opencl::OpenCLRuntime::DeleteInstance();
}
TEST_F(TestActivationOpenCLTanh, TanhFp_dim4) {
std::string in_file = "/data/local/tmp/test_data/in_tanhfp16.bin";
std::string out_file = "/data/local/tmp/test_data/out_tanhfp16.bin";
MS_LOG(INFO) << "Tanh Begin test!";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto data_type = kNumberTypeFloat16;
ocl_runtime->SetFp16Enable(data_type == kNumberTypeFloat16);
@ -627,7 +623,6 @@ TEST_F(TestActivationOpenCLTanh, TanhFp_dim4) {
printf_tensor<float>("Tanh:FP32--output data---", outputs[0]);
CompareRes<float>(output_tensor, out_file);
}
lite::opencl::OpenCLRuntime::DeleteInstance();
input_tensor->SetData(nullptr);
delete input_tensor;
output_tensor->SetData(nullptr);

6
mindspore/lite/test/ut/src/runtime/kernel/opencl/arithmetic_self_tests.cc
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@ -43,7 +43,7 @@ void CompareOutputData1(T *input_data1, T *output_data, T *correct_data, int siz
TEST_F(TestArithmeticSelfOpenCLfp16, ArithmeticSelfOpenCLFp16) {
MS_LOG(INFO) << " begin test ";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->SetFp16Enable(true);
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();
@ -125,7 +125,6 @@ TEST_F(TestArithmeticSelfOpenCLfp16, ArithmeticSelfOpenCLFp16) {
sub_graph->Run();
auto *output_data_gpu = reinterpret_cast<float16_t *>(output_tensor->data_c());
CompareOutputData1(input_data1, output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.000001);
lite::opencl::OpenCLRuntime::DeleteInstance();
for (auto tensor : inputs) {
tensor->SetData(nullptr);
delete tensor;
@ -139,7 +138,7 @@ TEST_F(TestArithmeticSelfOpenCLfp16, ArithmeticSelfOpenCLFp16) {
TEST_F(TestArithmeticSelfOpenCLCI, ArithmeticSelfRound) {
MS_LOG(INFO) << " begin test ";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();
float input_data1[] = {0.75f, 0.06f, 0.74f, 0.30f, 0.9f, 0.59f, 0.03f, 0.37f,
@ -216,7 +215,6 @@ TEST_F(TestArithmeticSelfOpenCLCI, ArithmeticSelfRound) {
sub_graph->Run();
auto *output_data_gpu = reinterpret_cast<float *>(output_tensor->data_c());
CompareOutputData1(input_data1, output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.000001);
lite::opencl::OpenCLRuntime::DeleteInstance();
for (auto tensor : inputs) {
tensor->SetData(nullptr);
delete tensor;

3
mindspore/lite/test/ut/src/runtime/kernel/opencl/arithmetic_tests.cc
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@ -68,7 +68,7 @@ static void LogData(void *data, const int size, const std::string prefix) {
template <class T>
static void TestCase(const std::vector<int> &shape_a, const std::vector<int> &shape_b) {
bool is_log_data = false;
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
auto allocator = ocl_runtime->GetAllocator();
bool is_bias_add = shape_b.empty();
@ -212,7 +212,6 @@ static void TestCase(const std::vector<int> &shape_a, const std::vector<int> &sh
for (auto tensor : outputs) {
delete tensor;
}
lite::opencl::OpenCLRuntime::DeleteInstance();
}
class TestArithmeticOpenCL : public mindspore::CommonTest {

3
mindspore/lite/test/ut/src/runtime/kernel/opencl/avg_pooling_tests.cc
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@ -53,7 +53,7 @@ void InitAvgPoolingParam(PoolingParameter *param) {
}
void RunTestCaseAvgPooling(const std::vector<int> &shape, void *input_data, void *output_data, bool enable_fp16) {
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
size_t dtype_size = enable_fp16 ? sizeof(float16_t) : sizeof(float);
ocl_runtime->SetFp16Enable(enable_fp16);
@ -125,7 +125,6 @@ void RunTestCaseAvgPooling(const std::vector<int> &shape, void *input_data, void
}
MS_LOG(INFO) << "Test AvgPool2d passed";
lite::opencl::OpenCLRuntime::DeleteInstance();
}
TEST_F(TestAvgPoolingOpenCL, AvgPoolingFp32) {

9
mindspore/lite/test/ut/src/runtime/kernel/opencl/batchnorm_tests.cc
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@ -38,7 +38,7 @@ class TestBatchnormOpenCLCI : public mindspore::CommonTest {
TEST_F(TestBatchnormOpenCLCI, Batchnormfp32CI) {
MS_LOG(INFO) << " begin test ";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();
@ -142,7 +142,6 @@ TEST_F(TestBatchnormOpenCLCI, Batchnormfp32CI) {
auto *output_data_gpu = reinterpret_cast<float *>(output_tensor->data_c());
CompareOutputData(output_data_gpu, correct_data, output_tensor->ElementsNum(), 0.0001);
lite::opencl::OpenCLRuntime::DeleteInstance();
for (auto tensor : inputs) {
tensor->SetData(nullptr);
delete tensor;
@ -156,7 +155,7 @@ TEST_F(TestBatchnormOpenCLCI, Batchnormfp32CI) {
TEST_F(TestBatchnormOpenCLfp16, Batchnormfp16input_dim4) {
MS_LOG(INFO) << "begin test";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->SetFp16Enable(true);
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();
@ -262,7 +261,6 @@ TEST_F(TestBatchnormOpenCLfp16, Batchnormfp16input_dim4) {
auto *output_data_gpu = reinterpret_cast<float16_t *>(output_tensor->data_c());
CompareOutputData(output_data_gpu, correct_data, output_tensor->ElementsNum(), 0.01);
lite::opencl::OpenCLRuntime::DeleteInstance();
for (auto tensor : inputs) {
tensor->SetData(nullptr);
delete tensor;
@ -276,7 +274,7 @@ TEST_F(TestBatchnormOpenCLfp16, Batchnormfp16input_dim4) {
TEST_F(TestBatchnormOpenCLfp32, Batchnormfp32input_dim4) {
MS_LOG(INFO) << " begin test ";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();
@ -381,7 +379,6 @@ TEST_F(TestBatchnormOpenCLfp32, Batchnormfp32input_dim4) {
auto *output_data_gpu = reinterpret_cast<float *>(output_tensor->data_c());
CompareOutputData(output_data_gpu, correct_data, output_tensor->ElementsNum(), 0.0001);
lite::opencl::OpenCLRuntime::DeleteInstance();
for (auto tensor : inputs) {
tensor->SetData(nullptr);
delete tensor;

3
mindspore/lite/test/ut/src/runtime/kernel/opencl/biasadd_tests.cc
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@ -75,7 +75,7 @@ TEST_F(TestBiasAddOpenCL, BiasAddFp32_dim4) {
std::string weight_file = "/data/local/tmp/weight_data.bin";
std::string standard_answer_file = "/data/local/tmp/biasadd.bin";
MS_LOG(INFO) << "BiasAdd Begin test:";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto data_type = kNumberTypeFloat16; // need modify
ocl_runtime->SetFp16Enable(data_type == kNumberTypeFloat16);
@ -200,6 +200,5 @@ TEST_F(TestBiasAddOpenCL, BiasAddFp32_dim4) {
delete output_tensor;
delete sub_graph;
delete param;
lite::opencl::OpenCLRuntime::DeleteInstance();
}
} // namespace mindspore

6
mindspore/lite/test/ut/src/runtime/kernel/opencl/cast_tests.cc
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@ -38,7 +38,7 @@ void CompareOutputData1(T *output_data, T *correct_data, int size, float err_bou
TEST_F(TestCastSelfOpenCL, Castfp32tofp16) {
MS_LOG(INFO) << " begin test ";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();
@ -113,7 +113,6 @@ TEST_F(TestCastSelfOpenCL, Castfp32tofp16) {
sub_graph->Run();
auto *output_data_gpu = reinterpret_cast<float16_t *>(output_tensor->data_c());
CompareOutputData1(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.000001);
lite::opencl::OpenCLRuntime::DeleteInstance();
for (auto tensor : inputs) {
tensor->SetData(nullptr);
delete tensor;
@ -127,7 +126,7 @@ TEST_F(TestCastSelfOpenCL, Castfp32tofp16) {
TEST_F(TestCastSelfOpenCL, Castfp16tofp32) {
MS_LOG(INFO) << " begin test ";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();
@ -201,7 +200,6 @@ TEST_F(TestCastSelfOpenCL, Castfp16tofp32) {
sub_graph->Run();
auto *output_data_gpu = reinterpret_cast<float *>(output_tensor->data_c());
CompareOutputData1(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.000001);
lite::opencl::OpenCLRuntime::DeleteInstance();
for (auto tensor : inputs) {
tensor->SetData(nullptr);
delete tensor;

9
mindspore/lite/test/ut/src/runtime/kernel/opencl/concat_tests.cc
Unescape View File

@ -47,7 +47,7 @@ void CompareOutputData1(T *output_data, T *correct_data, int size, float err_bou
TEST_F(TestConcatOpenCLCI, ConcatFp32_2inputforCI) {
MS_LOG(INFO) << " begin test ";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();
@ -134,7 +134,6 @@ TEST_F(TestConcatOpenCLCI, ConcatFp32_2inputforCI) {
sub_graph->Run();
auto *output_data_gpu = reinterpret_cast<float *>(output_tensor->data_c());
CompareOutputData1(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.00001);
lite::opencl::OpenCLRuntime::DeleteInstance();
for (auto tensor : inputs) {
tensor->SetData(nullptr);
delete tensor;
@ -148,7 +147,7 @@ TEST_F(TestConcatOpenCLCI, ConcatFp32_2inputforCI) {
TEST_F(TestConcatOpenCLfp16, ConcatFp16_2input_dim4_axis1) {
MS_LOG(INFO) << " begin test ";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->SetFp16Enable(true);
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();
@ -264,7 +263,6 @@ TEST_F(TestConcatOpenCLfp16, ConcatFp16_2input_dim4_axis1) {
sub_graph->Run();
auto *output_data_gpu = reinterpret_cast<float16_t *>(output_tensor->data_c());
CompareOutputData1(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.000001);
lite::opencl::OpenCLRuntime::DeleteInstance();
for (auto tensor : inputs) {
tensor->SetData(nullptr);
delete tensor;
@ -278,7 +276,7 @@ TEST_F(TestConcatOpenCLfp16, ConcatFp16_2input_dim4_axis1) {
TEST_F(TestConcatOpenCLfp32, ConcatFp32_2input_dim4_axis3) {
MS_LOG(INFO) << " begin test ";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();
@ -385,7 +383,6 @@ TEST_F(TestConcatOpenCLfp32, ConcatFp32_2input_dim4_axis3) {
sub_graph->Run();
auto *output_data_gpu = reinterpret_cast<float *>(output_tensor->data_c());
CompareOutputData1(output_data_gpu, correctOutput, output_tensor->ElementsNum(), 0.00001);
lite::opencl::OpenCLRuntime::DeleteInstance();
for (auto tensor : inputs) {
tensor->SetData(nullptr);
delete tensor;

3
mindspore/lite/test/ut/src/runtime/kernel/opencl/conv2d_transpose_tests.cc
Unescape View File

@ -32,7 +32,7 @@ class TestConv2dTransposeOpenCL : public mindspore::CommonTest {
void RunTestCaseConv2dTranspose(const std::vector<int> &shape, void *input_data, void *weight_data, void *bias_data,
void *output_data, bool enable_fp16) {
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
size_t dtype_size = enable_fp16 ? sizeof(float16_t) : sizeof(float);
ocl_runtime->SetFp16Enable(enable_fp16);
@ -134,7 +134,6 @@ void RunTestCaseConv2dTranspose(const std::vector<int> &shape, void *input_data,
for (auto t : outputs) {
t->SetData(nullptr);
}
lite::opencl::OpenCLRuntime::DeleteInstance();
}
TEST_F(TestConv2dTransposeOpenCL, Conv2dTransposeFp32) {

3
mindspore/lite/test/ut/src/runtime/kernel/opencl/convolution_tests.cc
Unescape View File

@ -157,7 +157,7 @@ void TEST_MAIN(const std::string &attr, Format input_format, Format output_forma
&param->dilation_h_, &param->dilation_w_);
MS_LOG(DEBUG) << "initialize OpenCLRuntime and OpenCLAllocator";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
ocl_runtime->SetFp16Enable(data_type == kNumberTypeFloat16);
auto allocator = ocl_runtime->GetAllocator();
@ -201,7 +201,6 @@ void TEST_MAIN(const std::string &attr, Format input_format, Format output_forma
input.SetData(nullptr);
output.SetData(nullptr);
delete sub_graph;
lite::opencl::OpenCLRuntime::DeleteInstance();
}
void TEST_MAIN(const std::string &attr, Format input_format, Format output_format, const TypeId data_type,

3
mindspore/lite/test/ut/src/runtime/kernel/opencl/depthwise_conv2d_tests.cc
Unescape View File

@ -33,7 +33,7 @@ class TestConvolutionDwOpenCL : public mindspore::CommonTest {
template <class T1, class T2>
void DepthWiseTestMain(ConvParameter *conv_param, T2 *input_data, T1 *weight_data, T2 *gnd_data, schema::Format format,
TypeId dtype = kNumberTypeFloat32, bool is_compare = true, T2 err_max = 1e-5) {
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();
if (dtype == kNumberTypeFloat16) {
@ -167,7 +167,6 @@ void DepthWiseTestMain(ConvParameter *conv_param, T2 *input_data, T1 *weight_dat
inputs[1]->SetData(nullptr);
inputs[2]->SetData(nullptr);
delete[] packed_input;
lite::opencl::OpenCLRuntime::DeleteInstance();
inputs[0]->SetData(nullptr);
outputs[0]->SetData(nullptr);
return;

2
mindspore/lite/test/ut/src/runtime/kernel/opencl/gather_tests.cc
Unescape View File

@ -32,7 +32,7 @@ void test_main_gather(void *input_data, void *correct_data, const std::vector<in
const std::vector<int> &indices, GatherParameter *param, TypeId data_type,
schema::Format format) {
MS_LOG(INFO) << " begin test ";
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto allocator = ocl_runtime->GetAllocator();

3
mindspore/lite/test/ut/src/runtime/kernel/opencl/matmul_tests.cc
Unescape View File

@ -31,7 +31,7 @@ class TestMatMulOpenCL : public mindspore::CommonTest {
void RunTestCaseMatMul(const std::vector<int> &shape, void *input_data, void *weight_data, void *output_data,
bool enable_fp16, int dims) {
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
size_t dtype_size = enable_fp16 ? sizeof(float16_t) : sizeof(float);
ocl_runtime->SetFp16Enable(enable_fp16);
@ -123,7 +123,6 @@ void RunTestCaseMatMul(const std::vector<int> &shape, void *input_data, void *we
t->SetData(nullptr);
}
MS_LOG(INFO) << "TestMatMul passed";
lite::opencl::OpenCLRuntime::DeleteInstance();
}
TEST_F(TestMatMulOpenCL, MatMul2DFp32) {

3
mindspore/lite/test/ut/src/runtime/kernel/opencl/max_pooling_tests.cc
Unescape View File

@ -53,7 +53,7 @@ void InitMaxPoolingParam(PoolingParameter *param) {
}
void RunTestCaseMaxPooling(const std::vector<int> &shape, void *input_data, void *output_data, bool enable_fp16) {
auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
size_t dtype_size = enable_fp16 ? sizeof(float16_t) : sizeof(float);
ocl_runtime->SetFp16Enable(enable_fp16);
@ -124,7 +124,6 @@ void RunTestCaseMaxPooling(const std::vector<int> &shape, void *input_data, void
}
MS_LOG(INFO) << "Test MaxPool2d passed";
lite::opencl::OpenCLRuntime::DeleteInstance();
}
TEST_F(TestMaxPoolingOpenCL, MaxPoolingFp32) {

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