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!28458 [MSLITE][GPU] opencl op checkspec func's log clean 

Merge pull request !28458 from Greatpan/master_code_check
This commit is contained in:
i-robot 2021-12-31 09:16:06 +00:00 committed by Gitee
parent bd69acb758 d1f37486ca
commit 0ca3207994
8 changed files with 26 additions and 25 deletions
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8
mindspore/lite/src/runtime/kernel/opencl/kernel/arithmetic.cc
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@ -53,24 +53,24 @@ int ArithmeticOpenCLKernel::CheckSpecs() {
} }
if (in_tensors_.size() != INPUT_TENSOR_SIZE_2 || out_tensors_.size() != OUTPUT_TENSOR_SIZE_1) { if (in_tensors_.size() != INPUT_TENSOR_SIZE_2 || out_tensors_.size() != OUTPUT_TENSOR_SIZE_1) {
MS_LOG(ERROR) << "in size: " << in_tensors_.size() << ", out size: " << out_tensors_.size(); MS_LOG(WARNING) << "in size: " << in_tensors_.size() << ", out size: " << out_tensors_.size();
return RET_ERROR; return RET_ERROR;
} }
auto *param = reinterpret_cast<const ArithmeticParameter *>(op_parameter_); auto *param = reinterpret_cast<const ArithmeticParameter *>(op_parameter_);
if (!IsArithmetic(type())) { if (!IsArithmetic(type())) {
MS_LOG(ERROR) << "UnSupported Operator: " << schema::EnumNamePrimitiveType(type()); MS_LOG(WARNING) << "UnSupported Operator: " << schema::EnumNamePrimitiveType(type());
return RET_ERROR; return RET_ERROR;
} }
if (type() == schema::PrimitiveType_Eltwise) { if (type() == schema::PrimitiveType_Eltwise) {
auto mode = param->eltwise_mode_; auto mode = param->eltwise_mode_;
if (mode != EltwiseMode_PROD && mode != EltwiseMode_SUM && mode != EltwiseMode_MAXIMUM) { if (mode != EltwiseMode_PROD && mode != EltwiseMode_SUM && mode != EltwiseMode_MAXIMUM) {
MS_LOG(ERROR) << "Eltwise mode not support, mode:" << mode; MS_LOG(WARNING) << "Eltwise mode not support, mode:" << mode;
return RET_ERROR; return RET_ERROR;
} }
} }
if (!(param->activation_type_ == ActivationType_NO_ACTIVATION || param->activation_type_ == ActivationType_RELU || if (!(param->activation_type_ == ActivationType_NO_ACTIVATION || param->activation_type_ == ActivationType_RELU ||
param->activation_type_ == ActivationType_RELU6)) { param->activation_type_ == ActivationType_RELU6)) {
MS_LOG(ERROR) << "Unsupported activation type " << param->activation_type_; MS_LOG(WARNING) << "Unsupported activation type " << param->activation_type_;
return RET_ERROR; return RET_ERROR;
} }
return RET_OK; return RET_OK;

2
mindspore/lite/src/runtime/kernel/opencl/kernel/concat.cc
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@ -40,7 +40,7 @@ int ConcatOpenCLKernel::RunAxis0() {
for (size_t i = 0; i < in_tensors_.size(); i++) { for (size_t i = 0; i < in_tensors_.size(); i++) {
auto src_data = weight_ptrs_.at(i) == nullptr ? in_tensors_[i]->data() : weight_ptrs_.at(i); auto src_data = weight_ptrs_.at(i) == nullptr ? in_tensors_[i]->data() : weight_ptrs_.at(i);
if (allocator_->GetImageSize(src_data, &img_size) != RET_OK) { if (allocator_->GetImageSize(src_data, &img_size) != RET_OK) {
MS_LOG(ERROR) << "GetImageSize failed."; MS_LOG(WARNING) << "GetImageSize failed.";
return RET_ERROR; return RET_ERROR;
} }
auto src_origin = cl::array<cl::size_type, 3U>{0, 0, 0}; auto src_origin = cl::array<cl::size_type, 3U>{0, 0, 0};

6
mindspore/lite/src/runtime/kernel/opencl/kernel/matmul.cc
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@ -446,7 +446,7 @@ kernel::InnerKernel *OpenCLMatMulKernelCreator(const std::vector<lite::Tensor *>
new (std::nothrow) MatMulOpenCLKernel(opParameter, inputs, outputs, static_cast<const lite::InnerContext *>(ctx)); new (std::nothrow) MatMulOpenCLKernel(opParameter, inputs, outputs, static_cast<const lite::InnerContext *>(ctx));
} }
if (kernel == nullptr) { if (kernel == nullptr) {
MS_LOG(ERROR) << "kernel " << opParameter->name_ << "is nullptr."; MS_LOG(WARNING) << "kernel " << opParameter->name_ << "is nullptr.";
free(opParameter); free(opParameter);
return nullptr; return nullptr;
} }
@ -454,14 +454,14 @@ kernel::InnerKernel *OpenCLMatMulKernelCreator(const std::vector<lite::Tensor *>
MS_LOG(WARNING) << "kernel don't infer shape yet!"; MS_LOG(WARNING) << "kernel don't infer shape yet!";
auto ret = reinterpret_cast<MatMulOpenCLKernel *>(kernel)->StoreConstData(); auto ret = reinterpret_cast<MatMulOpenCLKernel *>(kernel)->StoreConstData();
if (ret != mindspore::lite::RET_OK) { if (ret != mindspore::lite::RET_OK) {
MS_LOG(ERROR) << "Store " << opParameter->name_ << " const data failed!"; MS_LOG(WARNING) << "Store " << opParameter->name_ << " const data failed!";
delete kernel; delete kernel;
return nullptr; return nullptr;
} }
return kernel; return kernel;
} }
if (kernel->CheckSpecs() != RET_OK || kernel->OpenCLKernel::CheckSpecs() != RET_OK) { if (kernel->CheckSpecs() != RET_OK || kernel->OpenCLKernel::CheckSpecs() != RET_OK) {
MS_LOG(ERROR) << "Check " << opParameter->name_ << " specification failed!"; MS_LOG(WARNING) << "Check " << opParameter->name_ << " specification failed!";
delete kernel; delete kernel;
return nullptr; return nullptr;
} }

6
mindspore/lite/src/runtime/kernel/opencl/kernel/reduce.cc
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@ -110,7 +110,7 @@ int ReduceOpenCLKernel::SetShapeSizeIs0Axes() {
reduction_indices = reduction_indices + (C4NUM % input_shape_size); reduction_indices = reduction_indices + (C4NUM % input_shape_size);
reduce_axes_[reduction_indices] = true; reduce_axes_[reduction_indices] = true;
} else { } else {
MS_LOG(ERROR) << "in Reduce: axes tensor's reduction_indices should be -1, 1, 2, 3"; MS_LOG(WARNING) << "in Reduce: axes tensor's reduction_indices should be -1, 1, 2, 3";
return RET_ERROR; return RET_ERROR;
} }
return RET_OK; return RET_OK;
@ -132,7 +132,7 @@ int ReduceOpenCLKernel::SetShapeSizeIs1Axes() {
axes_[i] = reinterpret_cast<int *>(axes_tensor->data())[i]; axes_[i] = reinterpret_cast<int *>(axes_tensor->data())[i];
} }
if (num_axes > 2 || num_axes < 1) { if (num_axes > 2 || num_axes < 1) {
MS_LOG(ERROR) << "Unsupported reduce num axes " << num_axes; MS_LOG(WARNING) << "Unsupported reduce num axes " << num_axes;
return RET_PARAM_INVALID; return RET_PARAM_INVALID;
} }
@ -165,7 +165,7 @@ int ReduceOpenCLKernel::SetAxes() {
} else if (axes_tensor->shape().size() == 1) { } else if (axes_tensor->shape().size() == 1) {
return SetShapeSizeIs1Axes(); return SetShapeSizeIs1Axes();
} else { } else {
MS_LOG(ERROR) << "in Reduce: axes tensor's ndim should be 0 or 1."; MS_LOG(WARNING) << "in Reduce: axes tensor's ndim should be 0 or 1.";
return RET_ERROR; return RET_ERROR;
} }

8
mindspore/lite/src/runtime/kernel/opencl/kernel/reshape.cc
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@ -34,20 +34,20 @@ namespace mindspore::kernel {
int ReshapeOpenCLKernel::CheckSpecs() { int ReshapeOpenCLKernel::CheckSpecs() {
if ((in_tensors_.size() != INPUT_TENSOR_SIZE_1 && in_tensors_.size() != INPUT_TENSOR_SIZE_2) || if ((in_tensors_.size() != INPUT_TENSOR_SIZE_1 && in_tensors_.size() != INPUT_TENSOR_SIZE_2) ||
out_tensors_.size() != OUTPUT_TENSOR_SIZE_1) { out_tensors_.size() != OUTPUT_TENSOR_SIZE_1) {
MS_LOG(ERROR) << "Reshape input output size unsupported."; MS_LOG(WARNING) << "Reshape input output size unsupported.";
return RET_ERROR; return RET_ERROR;
} }
if (in_tensors_[0]->data_type() != kNumberTypeFloat32 && in_tensors_[0]->data_type() != kNumberTypeFloat16 && if (in_tensors_[0]->data_type() != kNumberTypeFloat32 && in_tensors_[0]->data_type() != kNumberTypeFloat16 &&
in_tensors_[0]->data_type() != kNumberTypeInt32) { in_tensors_[0]->data_type() != kNumberTypeInt32) {
MS_LOG(ERROR) << "Unsupported data type " << in_tensors_[0]->data_type(); MS_LOG(WARNING) << "Unsupported data type " << in_tensors_[0]->data_type();
return RET_ERROR; return RET_ERROR;
} }
if (in_tensors_[0]->shape().size() > DIMENSION_4D) { if (in_tensors_[0]->shape().size() > DIMENSION_4D) {
MS_LOG(ERROR) << "Reshape input size should in 0-4, actual: " << in_tensors_[0]->shape().size(); MS_LOG(WARNING) << "Reshape input size should in 0-4, actual: " << in_tensors_[0]->shape().size();
return RET_ERROR; return RET_ERROR;
} }
if (out_tensors_[0]->shape().size() > OUTPUT_TENSOR_SIZE_4) { if (out_tensors_[0]->shape().size() > OUTPUT_TENSOR_SIZE_4) {
MS_LOG(ERROR) << "Reshape output size should in 0-4, actual: " << out_tensors_[0]->shape().size(); MS_LOG(WARNING) << "Reshape output size should in 0-4, actual: " << out_tensors_[0]->shape().size();
return RET_ERROR; return RET_ERROR;
} }
return RET_OK; return RET_OK;

1
mindspore/lite/src/runtime/kernel/opencl/kernel/scale.cc
View File

@ -37,6 +37,7 @@ int ScaleOpenCLKernel::CheckSpecs() {
auto *param = reinterpret_cast<const ScaleParameter *>(op_parameter_); auto *param = reinterpret_cast<const ScaleParameter *>(op_parameter_);
if (param->activation_type_ != ActType_No && param->activation_type_ != ActType_Relu && if (param->activation_type_ != ActType_No && param->activation_type_ != ActType_Relu &&
param->activation_type_ != ActType_Relu6) { param->activation_type_ != ActType_Relu6) {
MS_LOG(WARNING) << "unsupported scale activation type " << param->activation_type_;
return RET_ERROR; return RET_ERROR;
} }
auto *scale_param = reinterpret_cast<const ScaleParameter *>(op_parameter_); auto *scale_param = reinterpret_cast<const ScaleParameter *>(op_parameter_);

10
mindspore/lite/src/runtime/kernel/opencl/opencl_kernel.h
View File

@ -258,14 +258,14 @@ kernel::InnerKernel *OpenCLKernelCreator(const std::vector<lite::Tensor *> &inpu
auto *kernel = new (std::nothrow) auto *kernel = new (std::nothrow)
T(reinterpret_cast<OpParameter *>(opParameter), inputs, outputs, static_cast<const lite::InnerContext *>(ctx)); T(reinterpret_cast<OpParameter *>(opParameter), inputs, outputs, static_cast<const lite::InnerContext *>(ctx));
if (kernel == nullptr) { if (kernel == nullptr) {
MS_LOG(ERROR) << "kernel " << opParameter->name_ << "is nullptr."; MS_LOG(WARNING) << "kernel " << opParameter->name_ << "is nullptr.";
free(opParameter); free(opParameter);
return nullptr; return nullptr;
} }
auto ret = kernel->CheckSpecsWithoutShape(); auto ret = kernel->CheckSpecsWithoutShape();
if (ret != mindspore::lite::RET_OK) { if (ret != mindspore::lite::RET_OK) {
MS_LOG(ERROR) << "Check " << opParameter->name_ << " specification Without shape failed!"; MS_LOG(WARNING) << "Check " << opParameter->name_ << " specification Without shape failed!";
delete kernel; delete kernel;
return nullptr; return nullptr;
} }
@ -281,19 +281,19 @@ kernel::InnerKernel *OpenCLKernelCreator(const std::vector<lite::Tensor *> &inpu
} }
ret = kernel->CheckSpecs(); ret = kernel->CheckSpecs();
if (ret != mindspore::lite::RET_OK) { if (ret != mindspore::lite::RET_OK) {
MS_LOG(ERROR) << "Check " << opParameter->name_ << " specification failed!"; MS_LOG(WARNING) << "Check " << opParameter->name_ << " specification failed!";
delete kernel; delete kernel;
return nullptr; return nullptr;
} }
ret = kernel->OpenCLKernel::CheckSpecs(); ret = kernel->OpenCLKernel::CheckSpecs();
if (ret != mindspore::lite::RET_OK) { if (ret != mindspore::lite::RET_OK) {
MS_LOG(ERROR) << "Check " << opParameter->name_ << " specification failed!"; MS_LOG(WARNING) << "Check " << opParameter->name_ << " specification failed!";
delete kernel; delete kernel;
return nullptr; return nullptr;
} }
ret = reinterpret_cast<OpenCLKernel *>(kernel)->StoreConstData(); ret = reinterpret_cast<OpenCLKernel *>(kernel)->StoreConstData();
if (ret != mindspore::lite::RET_OK) { if (ret != mindspore::lite::RET_OK) {
MS_LOG(ERROR) << "Store " << opParameter->name_ << " const data failed!"; MS_LOG(WARNING) << "Store " << opParameter->name_ << " const data failed!";
delete kernel; delete kernel;
return nullptr; return nullptr;
} }

6
mindspore/lite/src/runtime/kernel/opencl/utils.cc
View File

@ -338,11 +338,11 @@ void PackNCHWToNHWC4(void *src, void *dst, bool src_is_fp16, bool dst_is_fp16, c
int CheckParamLikeTensor(const std::string &kernel_name, const std::string &tensor_name, lite::Tensor *tensor, int CheckParamLikeTensor(const std::string &kernel_name, const std::string &tensor_name, lite::Tensor *tensor,
TypeId expect_data_type, const std::vector<int> &expect_shape) { TypeId expect_data_type, const std::vector<int> &expect_shape) {
if (!tensor->IsConst()) { if (!tensor->IsConst()) {
MS_LOG(ERROR) << "in " << kernel_name << ": tensor " << tensor_name << " must be Const."; MS_LOG(WARNING) << "in " << kernel_name << ": tensor " << tensor_name << " must be Const.";
return RET_ERROR; return RET_ERROR;
} }
if (tensor->data_type() != expect_data_type) { if (tensor->data_type() != expect_data_type) {
MS_LOG(ERROR) << "in " << kernel_name << ": tensor's data_type must be " << expect_data_type; MS_LOG(WARNING) << "in " << kernel_name << ": tensor's data_type must be " << expect_data_type;
return RET_ERROR; return RET_ERROR;
} }
if (tensor->shape() != expect_shape) { if (tensor->shape() != expect_shape) {
@ -358,7 +358,7 @@ int CheckParamLikeTensor(const std::string &kernel_name, const std::string &tens
} }
tensor_shape_str += ")"; tensor_shape_str += ")";
MS_LOG(ERROR) << "in " << kernel_name MS_LOG(WARNING) << "in " << kernel_name
<< ": tensor's shape is error. expect_shape: " + expect_shape_str + << ": tensor's shape is error. expect_shape: " + expect_shape_str +
" tensor->shape(): " + tensor_shape_str; " tensor->shape(): " + tensor_shape_str;
return RET_ERROR; return RET_ERROR;