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!7688 clear warning of compiler 

Merge pull request !7688 from zhanghaibo/master
This commit is contained in:
mindspore-ci-bot 2020-10-26 08:53:35 +08:00 committed by Gitee
parent a418280659 182e2dc8c2
commit 5fa1047163
23 changed files with 50 additions and 76 deletions
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20
mindspore/lite/nnacl/fp32/deconv_winograd.c
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@ -227,17 +227,17 @@ void DeConvWgMerge(const float *src, float *dst, size_t src_stride, size_t dst_s
size_t src_step = src_stride * sizeof(float);
size_t dst_step = dst_stride * sizeof(float);
asm volatile(
"mov r7, %[src_ptr]\n"
"mov r11, %[src_ptr]\n"
"mov r8, %[dst_ptr]\n"
"mov r10, r8\n"
"vld1.32 {q0}, [r7], %[src_step]\n"
"vld1.32 {q0}, [r11], %[src_step]\n"
"vld1.32 {q1}, [r8], %[dst_step]\n"
"vld1.32 {q2}, [r7], %[src_step]\n"
"vld1.32 {q2}, [r11], %[src_step]\n"
"vld1.32 {q3}, [r8], %[dst_step]\n"
"vadd.f32 q0, q0, q1\n"
"vld1.32 {q8}, [r7], %[src_step]\n"
"vld1.32 {q8}, [r11], %[src_step]\n"
"vadd.f32 q2, q2, q3\n"
"vst1.32 {q0}, [r10], %[dst_step]\n"
@ -245,19 +245,19 @@ void DeConvWgMerge(const float *src, float *dst, size_t src_stride, size_t dst_s
"vld1.32 {q9}, [r8], %[dst_step]\n"
"vld1.32 {q10}, [r7], %[src_step]\n"
"vld1.32 {q10}, [r11], %[src_step]\n"
"vadd.f32 q8, q8, q9\n"
"vld1.32 {q11}, [r8], %[dst_step]\n"
"vadd.f32 q10, q10, q11\n"
"vld1.32 {q0}, [r7], %[src_step]\n"
"vld1.32 {q0}, [r11], %[src_step]\n"
"vst1.32 {q8}, [r10], %[dst_step]\n"
"vst1.32 {q10}, [r10], %[dst_step]\n"
"vld1.32 {q1}, [r8], %[dst_step]\n"
"vld1.32 {q2}, [r7], %[src_step]\n"
"vld1.32 {q2}, [r11], %[src_step]\n"
"vld1.32 {q3}, [r8], %[dst_step]\n"
"vadd.f32 q0, q0, q1\n"
@ -266,10 +266,10 @@ void DeConvWgMerge(const float *src, float *dst, size_t src_stride, size_t dst_s
"vst1.32 {q0}, [r10], %[dst_step]\n"
"vst1.32 {q2}, [r10], %[dst_step]\n"
"vld1.32 {q8}, [r7], %[src_step]\n"
"vld1.32 {q8}, [r11], %[src_step]\n"
"vld1.32 {q9}, [r8], %[dst_step]\n"
"vld1.32 {q10}, [r7], %[src_step]\n"
"vld1.32 {q10}, [r11], %[src_step]\n"
"vld1.32 {q11}, [r8], %[dst_step]\n"
"vadd.f32 q8, q8, q9\n"
@ -280,7 +280,7 @@ void DeConvWgMerge(const float *src, float *dst, size_t src_stride, size_t dst_s
:
: [ src_ptr ] "r"(src_ptr), [ dst_ptr ] "r"(dst_ptr), [ src_step ] "r"(src_step), [ dst_step ] "r"(dst_step)
: "r7", "r8", "r10", "q0", "q1", "q2", "q3", "q8", "q9", "q10", "q11");
: "r8", "r10", "r11", "q0", "q1", "q2", "q3", "q8", "q9", "q10", "q11");
#else
for (int j = 0; j < 8; j++) {
const float *s = src_ptr + j * src_stride;

4
mindspore/lite/src/runtime/kernel/opencl/kernel/softmax.h
View File

@ -28,7 +28,9 @@ class SoftmaxOpenCLKernel : public OpenCLKernel {
public:
SoftmaxOpenCLKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
const std::vector<lite::Tensor *> &outputs)
: OpenCLKernel(parameter, inputs, outputs), parameter_(reinterpret_cast<SoftmaxParameter *>(parameter)) {}
: OpenCLKernel(parameter, inputs, outputs) {
parameter_ = reinterpret_cast<SoftmaxParameter *>(parameter);
}
~SoftmaxOpenCLKernel() override = default;
int Init() override;

2
mindspore/lite/test/CMakeLists.txt
View File

@ -6,8 +6,6 @@ include_directories(${TOP_DIR})
include_directories(${TEST_DIR})
include(${CMAKE_CURRENT_SOURCE_DIR}/../../../cmake/dependency_gtest.cmake)
string(REPLACE " -Werror " " " CMAKE_C_FLAGS "${CMAKE_C_FLAGS}")
string(REPLACE " -Werror " " " CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
STRING(REPLACE " -fvisibility=hidden " " -fvisibility=default " CMAKE_C_FLAGS "${CMAKE_C_FLAGS}")
STRING(REPLACE " -fvisibility=hidden " " -fvisibility=default " CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")

2
mindspore/lite/test/common/common_test.h
View File

@ -50,7 +50,7 @@ class CommonTest : public testing::Test {
template <typename T>
static void CompareOutputData(T *output_data, T *correct_data, int size, float err_bound) {
for (size_t i = 0; i < size; i++) {
for (int i = 0; i < size; i++) {
T abs = fabs(output_data[i] - correct_data[i]);
ASSERT_LE(abs, err_bound);
}

2
mindspore/lite/test/ut/internal/CMakeLists.txt
View File

@ -6,8 +6,6 @@ include_directories(${TOP_DIR})
include_directories(${TEST_DIR})
add_compile_definitions(ENABLE_NNACL_INFER_SHAPE)
string(REPLACE " -Werror " " " CMAKE_C_FLAGS "${CMAKE_C_FLAGS}")
string(REPLACE " -Werror " " " CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
STRING(REPLACE " -fvisibility=hidden " " -fvisibility=default " CMAKE_C_FLAGS "${CMAKE_C_FLAGS}")
STRING(REPLACE " -fvisibility=hidden " " -fvisibility=default " CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")

2
mindspore/lite/test/ut/src/infer_test.cc
View File

@ -149,7 +149,7 @@ TEST_F(InferTest, TestConvNode) {
ASSERT_NE(nullptr, output_data);
//===================================================
ASSERT_EQ(output_size, outTensor->Size());
for (size_t i = 0; i < outTensor->ElementsNum(); i++) {
for (int i = 0; i < outTensor->ElementsNum(); i++) {
ASSERT_LE((output_data[i] - outData[i]), 0.001);
}
MS_LOG(INFO) << "Passed";

2
mindspore/lite/test/ut/src/runtime/kernel/arm/common/pack_tests.cc
View File

@ -184,7 +184,7 @@ TEST_F(TestPack, PackWeightUint8) {
std::string weight_path = "./test_data/conv/convuint8_weight_32_3_3_3.bin";
auto weight_data = reinterpret_cast<uint8_t *>(mindspore::lite::ReadFile(weight_path.c_str(), &weight_size));
auto int8_weight = reinterpret_cast<int8_t *>(malloc(weight_size));
for (int i = 0; i < weight_size; i++) {
for (unsigned int i = 0; i < weight_size; i++) {
int8_weight[i] = (int8_t)(weight_data[i] - 128);
}
int32_t filter_zp = 20;

2
mindspore/lite/test/ut/src/runtime/kernel/arm/common/strided_slice_tests.cc
View File

@ -117,7 +117,7 @@ TEST_F(TestStridedSlice, StridedSliceInt8) {
EXPECT_EQ(0, ret);
int8_t expect[4] = {-6, -5, 7, 8};
for (int i = 0; i < sizeof(expect); ++i) {
for (unsigned int i = 0; i < sizeof(expect); ++i) {
EXPECT_EQ(output_data[i], expect[i]);
}

2
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/constant_of_shape_fp32_test.cc
View File

@ -33,7 +33,7 @@ int ConstantOfShapeTestInit(std::vector<lite::Tensor *> *inputs_, std::vector<li
inputs_->push_back(in_t);
std::vector<int> c_shape(in_t->ElementsNum());
for (int i = 0; i < c_shape.size(); ++i) {
for (unsigned int i = 0; i < c_shape.size(); ++i) {
c_shape[i] = a_ptr[i];
}
auto out_t = new lite::Tensor(kNumberTypeFloat, c_shape, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR);

8
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/convolution_depthwise_fp32_tests.cc
View File

@ -138,10 +138,10 @@ TEST_F(TestConvolutionDwFp32, ConvDwFp32Accuracy) {
CompareOutputData(output_ptr, correct_data, outputs[0]->ElementsNum(), 0.0001);
delete conv_param;
for (int i = 0; i < inputs.size(); i++) {
for (unsigned int i = 0; i < inputs.size(); i++) {
delete inputs[i];
}
for (int i = 0; i < outputs.size(); i++) {
for (unsigned int i = 0; i < outputs.size(); i++) {
delete outputs[i];
}
delete kernel;
@ -189,10 +189,10 @@ TEST_F(TestConvolutionDwFp32, ConvDwFp32Performance) {
printf("Convolution_depthwise fp32 average time : %f ms\n", time_avg / 1000.0f);
delete conv_param;
for (int i = 0; i < inputs.size(); i++) {
for (unsigned int i = 0; i < inputs.size(); i++) {
delete inputs[i];
}
for (int i = 0; i < outputs.size(); i++) {
for (unsigned int i = 0; i < outputs.size(); i++) {
delete outputs[i];
}
delete kernel;

2
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/elu_fp32_test.cc
View File

@ -60,7 +60,7 @@ TEST_F(TestEluFp32, EluTest) {
elu->Run();
std::cout << "output shape:" << std::endl;
for (int i = 0; i < outputs_.front()->shape().size(); ++i) {
for (unsigned int i = 0; i < outputs_.front()->shape().size(); ++i) {
std::cout << outputs_.front()->shape()[i] << ' ';
}
std::cout << std::endl;

2
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/embedding_lookup_fp32_test.cc
View File

@ -75,7 +75,7 @@ TEST_F(TestEmbeddingLookupFp32, ElTest) {
el->Run();
std::cout << "output shape:" << std::endl;
for (int i = 0; i < outputs_.front()->shape().size(); ++i) {
for (unsigned int i = 0; i < outputs_.front()->shape().size(); ++i) {
std::cout << outputs_.front()->shape()[i] << ' ';
}
std::cout << std::endl;

7
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/fullconnection_fp32_tests.cc
View File

@ -146,8 +146,8 @@ TEST_F(TestFcFp32, FcTest2) {
CompareOutputData(reinterpret_cast<float *>(outputs_[0]->MutableData()), correct, total_size, 0.0001);
}
int FcTestInit3(std::vector<lite::Tensor *> *inputs_, std::vector<lite::Tensor *> *outputs_,
MatMulParameter *matmal_param, float **correct) {
void FcTestInit3(std::vector<lite::Tensor *> *inputs_, std::vector<lite::Tensor *> *outputs_,
MatMulParameter *matmal_param, float **correct) {
Tensor *in_t = new Tensor(kNumberTypeFloat, {1, 1, 1, 20}, schema::Format_NHWC, lite::Tensor::Category::CONST_TENSOR);
in_t->MallocData();
float in[] = {1, 0, 3, 0, 4, 5, 2, 5, 2, 5, 1, 5, 0, 1, 2, 0, 2, 1, 0, 5};
@ -177,7 +177,6 @@ int FcTestInit3(std::vector<lite::Tensor *> *inputs_, std::vector<lite::Tensor *
matmal_param->a_transpose_ = false;
matmal_param->has_bias_ = false;
matmal_param->act_type_ = ActType_No;
return out_t->ElementsNum();
}
TEST_F(TestFcFp32, FcTest3) {
@ -185,7 +184,7 @@ TEST_F(TestFcFp32, FcTest3) {
std::vector<lite::Tensor *> outputs_;
auto matmul_param = new MatMulParameter();
float *correct;
int total_size = FcTestInit3(&inputs_, &outputs_, matmul_param, &correct);
FcTestInit3(&inputs_, &outputs_, matmul_param, &correct);
lite::InnerContext *ctx = new lite::InnerContext;
ctx->thread_num_ = 1;
ASSERT_EQ(lite::RET_OK, ctx->Init());

8
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/lstm_fp32_tests.cc
View File

@ -171,10 +171,10 @@ TEST_F(LstmFp32, LstmForwardFp32Accuracy) {
CompareOutput(outputs[2], output2_data);
delete lstm_param;
for (int i = 0; i < inputs.size() - 1; i++) {
for (unsigned int i = 0; i < inputs.size() - 1; i++) {
delete inputs[i];
}
for (int i = 0; i < outputs.size(); i++) {
for (unsigned int i = 0; i < outputs.size(); i++) {
delete outputs[i];
}
delete kernel;
@ -321,10 +321,10 @@ TEST_F(LstmFp32, LstmBackwardFp32Accuracy) {
CompareOutput(outputs[2], output2_data);
delete lstm_param;
for (int i = 0; i < inputs.size() - 1; i++) {
for (unsigned int i = 0; i < inputs.size() - 1; i++) {
delete inputs[i];
}
for (int i = 0; i < outputs.size(); i++) {
for (unsigned int i = 0; i < outputs.size(); i++) {
delete outputs[i];
}
delete kernel;

1
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/power_fp32_tests.cc
View File

@ -79,7 +79,6 @@ TEST_F(TestPowerFp32, Simple) {
op->Init();
op->Run();
float correct[] = {1, 64, 2187, 65536};
float *output = reinterpret_cast<float *>(outputs_[0]->MutableData());
CompareOutputData(reinterpret_cast<float *>(outputs_[0]->MutableData()), correct, total_size, 0.0001);
delete op;
for (auto t : inputs_) delete t;

2
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/skip_gram_fp32.cc
View File

@ -67,7 +67,7 @@ TEST_F(TestSkipGramFp32, ElTest) {
el->Run();
std::vector<StringPack> output = mindspore::lite::ParseTensorBuffer(outputs_[0]);
for (int i = 0; i < output.size(); i++) {
for (unsigned int i = 0; i < output.size(); i++) {
for (int j = 0; j < output[i].len; j++) {
printf("%c", output[i].data[j]);
}

14
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/space_to_batch_fp32_tests.cc
View File

@ -39,7 +39,7 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest4) {
param.block_sizes_[0] = 2;
param.block_sizes_[1] = 1;
DoSpaceToBatchNHWC(input.data(), out, param.block_sizes_, in_shape.data(), out_shape.data());
for (int i = 0; i < kOutSize; ++i) {
for (unsigned int i = 0; i < kOutSize; ++i) {
std::cout << out[i] << " ";
}
std::cout << "\n";
@ -57,7 +57,7 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest5) {
param.block_sizes_[0] = 1;
param.block_sizes_[1] = 2;
DoSpaceToBatchNHWC(input.data(), out, param.block_sizes_, in_shape.data(), out_shape.data());
for (int i = 0; i < kOutSize; ++i) {
for (unsigned int i = 0; i < kOutSize; ++i) {
std::cout << out[i] << " ";
}
std::cout << "\n";
@ -75,7 +75,7 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest6) {
param.block_sizes_[0] = 2;
param.block_sizes_[1] = 2;
DoSpaceToBatchNHWC(input.data(), out, param.block_sizes_, in_shape.data(), out_shape.data());
for (int i = 0; i < kOutSize; ++i) {
for (unsigned int i = 0; i < kOutSize; ++i) {
std::cout << out[i] << " ";
}
std::cout << "\n";
@ -97,7 +97,7 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest7) {
param.block_sizes_[0] = 2;
param.block_sizes_[1] = 2;
DoSpaceToBatchNHWC(input.data(), out, param.block_sizes_, in_shape.data(), out_shape.data());
for (int i = 0; i < kOutSize; ++i) {
for (unsigned int i = 0; i < kOutSize; ++i) {
std::cout << out[i] << " ";
}
std::cout << "\n";
@ -116,7 +116,7 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest8) {
std::vector<int> out_shape = {1, 5, 5, 2};
std::vector<int> padding = {0, 1, 0, 1};
DoSpaceToBatchPaddingNHWC(input.data(), out, in_shape.data(), padding.data(), out_shape.data());
for (int i = 0; i < kOutSize; ++i) {
for (unsigned int i = 0; i < kOutSize; ++i) {
std::cout << out[i] << " ";
}
std::cout << "\n";
@ -136,7 +136,7 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest9) {
std::vector<int> out_shape = {1, 6, 6, 2};
std::vector<int> padding = {1, 1, 1, 1};
DoSpaceToBatchPaddingNHWC(input.data(), out, in_shape.data(), padding.data(), out_shape.data());
for (int i = 0; i < kOutSize; ++i) {
for (unsigned int i = 0; i < kOutSize; ++i) {
std::cout << out[i] << " ";
}
std::cout << "\n";
@ -162,7 +162,7 @@ TEST_F(SpaceToBatchTestFp32, SpaceToBatchTest10) {
param.block_sizes_[0] = 2;
param.block_sizes_[1] = 2;
DoSpaceToBatchNHWC(pedding_out, out, param.block_sizes_, pedding_out_shape.data(), out_shape.data());
for (int i = 0; i < kOutSize; ++i) {
for (unsigned int i = 0; i < kOutSize; ++i) {
std::cout << out[i] << " ";
}
std::cout << "\n";

15
mindspore/lite/test/ut/src/runtime/kernel/arm/fp32_grad/pooling_grad_fp32_tests.cc
View File

@ -276,10 +276,7 @@ TEST_F(TestPoolingGradFp32, AvgPoolGradStride2Fp32) {
kernel->Init();
auto time_start = mindspore::lite::GetTimeUs();
kernel->Run();
auto time_end = mindspore::lite::GetTimeUs();
printf("single thread running time : %lu ms\n", time_end - time_start);
std::string output_path = "./test_data/pooling/avgpoolgradfp32_s2_dx_3_28_28_3.bin";
auto res = lite::CompareRelativeOutput(out_data, output_path);
@ -340,10 +337,7 @@ TEST_F(TestPoolingGradFp32, AvgPoolGradStride3Fp32) {
kernel->Init();
auto time_start = mindspore::lite::GetTimeUs();
kernel->Run();
auto time_end = mindspore::lite::GetTimeUs();
printf("single thread running time : %lu ms\n", time_end - time_start);
std::string output_path = "./test_data/pooling/avgpoolgradfp32_s3_dx_3_28_28_3.bin";
auto res = lite::CompareRelativeOutput(out_data, output_path);
@ -461,10 +455,7 @@ TEST_F(TestPoolingGradFp32, MaxPoolGradBatchFp32) {
kernel->Init();
auto time_start = mindspore::lite::GetTimeUs();
kernel->Run();
auto time_end = mindspore::lite::GetTimeUs();
printf("single thread running time : %lu ms\n", time_end - time_start);
std::string output_path = "./test_data/pooling/maxpoolgradfp32_1_xgrad_3_28_28_3.bin";
auto res = lite::CompareRelativeOutput(out_data, output_path);
@ -535,10 +526,7 @@ TEST_F(TestPoolingGradFp32, MaxPoolGradStride2Fp32) {
kernel->Init();
auto time_start = mindspore::lite::GetTimeUs();
kernel->Run();
auto time_end = mindspore::lite::GetTimeUs();
printf("single thread running time : %lu ms\n", time_end - time_start);
std::string output_path = "./test_data/pooling/maxpoolgradfp32_s2_xgrad_3_28_28_3.bin";
auto res = lite::CompareRelativeOutput(out_data, output_path);
@ -609,10 +597,7 @@ TEST_F(TestPoolingGradFp32, MaxPoolGradStride3Fp32) {
kernel->Init();
auto time_start = mindspore::lite::GetTimeUs();
kernel->Run();
auto time_end = mindspore::lite::GetTimeUs();
printf("single thread running time : %lu ms\n", time_end - time_start);
std::string output_path = "./test_data/pooling/maxpoolgradfp32_s3_xgrad_3_28_28_3.bin";
auto res = lite::CompareRelativeOutput(out_data, output_path);

2
mindspore/lite/test/ut/src/runtime/kernel/arm/int8/relux_int8_tests.cc
View File

@ -108,7 +108,7 @@ TEST_F(TestReluXInt8, Relu6) {
// 0.0f, 0.0f, 1.25f, 3.0f, 4.5f, 6.0f, 6.0f, 6.0f
int8_t expect[8] = {-128, -128, -96, -52, -14, 25, 25, 25};
for (int i = 0; i < sizeof(expect); ++i) {
for (unsigned int i = 0; i < sizeof(expect); ++i) {
EXPECT_EQ(output_data[i], expect[i]);
}

6
mindspore/lite/test/ut/src/runtime/kernel/arm/string/normalize.cc
View File

@ -68,12 +68,12 @@ TEST_F(TestNormalize, TestSentence) {
kernel_ = creator_(inputs_, outputs_, &parameter_, &ctx_, desc_, nullptr);
ASSERT_NE(kernel_, nullptr);
auto ret = kernel_->Init();
MS_ASSERT(ret == 0);
ASSERT_EQ(ret, 0);
ret = kernel_->Run();
MS_ASSERT(ret == 0);
ASSERT_EQ(ret, 0);
std::vector<StringPack> output = mindspore::lite::ParseTensorBuffer(outputs_[0]);
for (int i = 0; i < output.size(); i++) {
for (unsigned int i = 0; i < output.size(); i++) {
for (int j = 0; j < output[i].len; j++) {
printf("%c", output[i].data[j]);
}

11
mindspore/lite/test/ut/src/runtime/kernel/opencl/activation_tests.cc
View File

@ -91,7 +91,6 @@ TEST_F(TestActivationOpenCL, ReluFp_dim4) {
MS_LOG(INFO) << "Init tensors.";
std::vector<int> input_shape = {1, 9};
schema::Format format = schema::Format_NC;
schema::Format op_format = schema::Format_NC4;
auto tensor_type = lite::Tensor::CONST_TENSOR;
auto *input_tensor = new (std::nothrow) lite::Tensor(data_type, input_shape, format, tensor_type);
if (input_tensor == nullptr) {
@ -198,7 +197,6 @@ TEST_F(TestActivationOpenCL, Relu6Fp_dim4) {
MS_LOG(INFO) << "Init tensors.";
std::vector<int> input_shape = {1, 9};
schema::Format format = schema::Format_NC;
schema::Format op_format = schema::Format_NC4;
auto tensor_type = lite::Tensor::CONST_TENSOR;
auto *input_tensor = new (std::nothrow) lite::Tensor(data_type, input_shape, format, tensor_type);
if (input_tensor == nullptr) {
@ -308,7 +306,6 @@ TEST_F(TestActivationOpenCL, SigmoidFp_dim4) {
MS_LOG(INFO) << "Init tensors.";
std::vector<int> input_shape = {1, 9};
schema::Format format = schema::Format_NC;
schema::Format op_format = schema::Format_NC4;
auto tensor_type = lite::Tensor::CONST_TENSOR;
auto *input_tensor = new (std::nothrow) lite::Tensor(data_type, input_shape, format, tensor_type);
if (input_tensor == nullptr) {
@ -411,15 +408,14 @@ TEST_F(TestActivationOpenCL, LeakyReluFp_dim4) {
MS_LOG(INFO) << "Leaky relu Begin test!";
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto data_type = kNumberTypeFloat16; // need modify
auto data_type = kNumberTypeFloat16;
ocl_runtime->SetFp16Enable(data_type == kNumberTypeFloat16);
bool enable_fp16 = ocl_runtime->GetFp16Enable();
MS_LOG(INFO) << "Init tensors.";
std::vector<int> input_shape = {1, 9}; // need modify
std::vector<int> input_shape = {1, 9};
auto tensor_type = lite::Tensor::CONST_TENSOR;
schema::Format format = schema::Format_NC; // need modify
schema::Format op_format = schema::Format_NHWC4; // need modify
schema::Format format = schema::Format_NC;
auto *input_tensor = new (std::nothrow) lite::Tensor(data_type, input_shape, format, tensor_type);
if (input_tensor == nullptr) {
MS_LOG(ERROR) << "new input tensor error!";
@ -527,7 +523,6 @@ TEST_F(TestActivationOpenCLTanh, TanhFp_dim4) {
MS_LOG(INFO) << "Init tensors.";
std::vector<int> input_shape = {1, 2, 3, 9};
schema::Format format = schema::Format_NHWC;
schema::Format op_format = schema::Format_NC4HW4;
auto tensor_type = lite::Tensor::CONST_TENSOR;
auto *input_tensor = new (std::nothrow) lite::Tensor(data_type, input_shape, format, tensor_type);
if (input_tensor == nullptr) {

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

@ -77,13 +77,12 @@ TEST_F(TestBiasAddOpenCL, BiasAddFp32_dim4) {
MS_LOG(INFO) << "BiasAdd Begin test:";
auto ocl_runtime = lite::opencl::OpenCLRuntimeWrapper().GetInstance();
ocl_runtime->Init();
auto data_type = kNumberTypeFloat16; // need modify
auto data_type = kNumberTypeFloat16;
ocl_runtime->SetFp16Enable(data_type == kNumberTypeFloat16);
std::vector<int> input_shape = {1, 9}; // need modify
std::vector<int> output_shape = {1, 9}; // need modify
std::vector<int> input_shape = {1, 9};
std::vector<int> output_shape = {1, 9};
auto tensor_type = lite::Tensor::CONST_TENSOR;
schema::Format type = schema::Format_NC; // need modify
schema::Format op_format = schema::Format_NC4; // need modify
schema::Format type = schema::Format_NC;
int weight_shape = 0;
if (input_shape.size() == 4) {
weight_shape = input_shape[3];

1
mindspore/lite/test/ut/src/runtime/kernel/opencl/prelu_tests.cc
View File

@ -86,7 +86,6 @@ TEST_F(TestPReluOpenCL, PReluFp32_dim4) {
auto data_type = kNumberTypeFloat16;
ocl_runtime->SetFp16Enable(data_type == kNumberTypeFloat16);
schema::Format format = schema::Format_NHWC;
schema::Format op_format = schema::Format_NC4HW4;
auto tensor_type = lite::Tensor::CONST_TENSOR;
auto input_tensor = new (std::nothrow) lite::Tensor(data_type, input_shape, format, tensor_type);
if (input_tensor == nullptr) {