forked from mindspore-Ecosystem/mindspore
!6819 [MSLITE][Develop] fix split fp16 kernel
Merge pull request !6819 from sunsuodong/fix_split_fp16
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commit
b446d66d11
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@ -13,10 +13,10 @@
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "nnacl/fp16/cast_fp16.h"
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#include "nnacl/fp16/split_fp16.h"
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#include "src/runtime/kernel/arm/fp16/split_fp16.h"
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#include "src/runtime/kernel/arm/fp16/common_fp16.h"
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#include "src/runtime/kernel/arm/base/split_base.h"
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#include "nnacl/fp16/split_fp16.h"
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#include "nnacl/split.h"
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#include "nnacl/split_parameter.h"
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#include "src/kernel_registry.h"
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@ -36,9 +36,10 @@ int SplitFp16CPUKernel::Init() {
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if (ret != RET_OK) {
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return ret;
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}
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output_ptr_.resize(param->num_split_);
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for (size_t i = 0; i < output_ptr_.size(); i++) {
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output_ptr_[i] = nullptr;
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}
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if (!InferShapeDone()) {
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return RET_OK;
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}
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@ -79,48 +80,37 @@ int SplitFp16CPUKernel::Run() {
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MS_LOG(ERROR) << "Prepare failed.";
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return RET_ERROR;
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}
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auto in_tensor = in_tensors_.front();
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if (in_tensor->data_type() == kNumberTypeFloat32) {
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input_ptr_ =
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reinterpret_cast<float16_t *>(context_->allocator->Malloc(in_tensor->ElementsNum() * sizeof(float16_t)));
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input_ptr_ = ConvertInputFp32toFp16(in_tensors_.at(0), context_);
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if (input_ptr_ == nullptr) {
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MS_LOG(ERROR) << "malloc input_ptr_ failed.";
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MS_LOG(ERROR) << "input or output is nullptr";
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return RET_ERROR;
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}
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Float32ToFloat16(reinterpret_cast<float *>(in_tensor->MutableData()), input_ptr_, in_tensor->ElementsNum());
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} else {
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input_ptr_ = reinterpret_cast<float16_t *>(in_tensor->MutableData());
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}
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for (int i = 0; i < param->num_split_; i++) {
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if (in_tensor->data_type() == kNumberTypeFloat32) {
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output_ptr_[i] = reinterpret_cast<float16_t *>(
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context_->allocator->Malloc(out_tensors_.at(i)->ElementsNum() * sizeof(float16_t)));
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output_ptr_[i] = MallocOutputFp16(out_tensors_.at(i), context_);
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if (output_ptr_[i] == nullptr) {
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MS_LOG(ERROR) << "malloc output_ptr_[" << i << "]" << " failed.";
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FreeInputAndOutput();
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MS_LOG(ERROR) << "input or output is nullptr";
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return RET_ERROR;
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}
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Float32ToFloat16(reinterpret_cast<float *>(out_tensors_.at(i)->MutableData()), output_ptr_[i],
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out_tensors_.at(i)->ElementsNum());
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} else {
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output_ptr_[i] = reinterpret_cast<float16_t *>(out_tensors_.at(i)->MutableData());
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}
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}
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ret = ParallelLaunch(this->context_->thread_pool_, SplitRun, this, thread_n_num_);
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if (ret != RET_OK) {
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MS_LOG(ERROR) << "split error error_code[" << ret << "]";
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return RET_ERROR;
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}
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if (in_tensor->data_type() == kNumberTypeFloat32) {
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return ret;
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}
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void SplitFp16CPUKernel::FreeInputAndOutput() {
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if (in_tensors_.at(0)->data_type() == kNumberTypeFloat32) {
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context_->allocator->Free(input_ptr_);
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input_ptr_ = nullptr;
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}
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for (int i = 0; i < param->num_split_; i++) {
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if (in_tensor->data_type() == kNumberTypeFloat32) {
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if (out_tensors_.at(i)->data_type() == kNumberTypeFloat32) {
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context_->allocator->Free(output_ptr_[i]);
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output_ptr_[i] = nullptr;
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}
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}
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return RET_OK;
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}
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kernel::LiteKernel *CpuSplitFp16KernelCreator(const std::vector<lite::Tensor *> &inputs,
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@ -37,8 +37,9 @@ class SplitFp16CPUKernel : public SplitBaseCPUKernel {
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int Split(int task_id);
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private:
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float16_t *input_ptr_;
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float16_t *input_ptr_ = nullptr;
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std::vector<float16_t *> output_ptr_;
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void FreeInputAndOutput();
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};
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} // namespace mindspore::kernel
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