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fix tests compile errors

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pull/3894/head
wandongdong 5 years ago
parent 8ff7c0b640
commit 190fc3cc5a
11 changed files with 67 additions and 75 deletions
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9
build.sh
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@ -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

1
mindspore/lite/CMakeLists.txt
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@ -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)

19
mindspore/lite/src/runtime/kernel/opencl/kernel/concat.cc
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@ -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();

9
mindspore/lite/src/runtime/kernel/opencl/kernel/concat.h
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@ -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();

1
mindspore/lite/src/runtime/kernel/opencl/kernel/conv2d_transpose.h
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@ -39,7 +39,6 @@ class Conv2dTransposeOpenCLKernel : public LiteKernel {
~Conv2dTransposeOpenCLKernel() override {};
int Init() override;
int InferShape() {}
int ReSize() override;
int Run() override;
void PadWeight();

1
mindspore/lite/src/runtime/kernel/opencl/kernel/matmul.h
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@ -41,7 +41,6 @@ class MatMulOpenCLKernel : public LiteKernel {
~MatMulOpenCLKernel() override{};
int Init() override;
int InferShape() {}
int ReSize() override;
int Run() override;
void PadWeight();

8
mindspore/lite/test/CMakeLists.txt
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@ -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()

27
mindspore/lite/test/ut/src/runtime/kernel/opencl/concat_test.cc → mindspore/lite/test/ut/src/runtime/kernel/opencl/concat_tests.cc
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@ -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");
}

51
mindspore/lite/test/ut/src/runtime/kernel/opencl/depthwise_conv2d_tests.cc
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@ -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

8
mindspore/lite/test/ut/src/runtime/kernel/opencl/matmul_tests.cc
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@ -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);

8
mindspore/lite/test/ut/src/runtime/kernel/opencl/softmax_cl_tests.cc
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@ -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";

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