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!7613 [MSLITE][Develop] fix LshProjection kernel and refactor it

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Merge pull request !7613 from sunsuodong/fix_lsh_projection
pull/7613/MERGE
mindspore-ci-bot 5 years ago committed by Gitee
parent 00d40d36c0 cd0700e588
commit cfa7211c0a
4 changed files with 115 additions and 105 deletions
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11
mindspore/lite/nnacl/lsh_projection_parameter.h
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@ -23,13 +23,10 @@ typedef struct LshProjectionParameter {
OpParameter op_parameter_;
int lsh_type_;
int hash_shape_[2];
int in_item_num_;
size_t in_item_size_;
size_t seed_size_;
size_t key_size_;
int64_t real_dst_count;
int task_id_;
int64_t count_unit_;
int feature_num_;
char **hash_buffs_;
size_t hash_buff_size_;
int64_t thread_stride_;
} LshProjectionParameter;
#endif // MINDSPORE_LITE_NNACL_LSH_PROJECTION_PARAMETER_H_

149
mindspore/lite/src/runtime/kernel/arm/fp32/lsh_projection.cc
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@ -23,7 +23,6 @@
using mindspore::kernel::KERNEL_ARCH::kCPU;
using mindspore::lite::KernelRegistrar;
using mindspore::lite::RET_ERROR;
using mindspore::lite::RET_MEMORY_FAILED;
using mindspore::lite::RET_OK;
using mindspore::schema::PrimitiveType_LshProjection;
@ -37,53 +36,77 @@ int LshProjectionCPUKernel::Init() {
int LshProjectionCPUKernel::ReSize() { return RET_OK; }
int LshProjectionRun(void *cdata, int task_id) {
auto kernel = reinterpret_cast<LshProjectionCPUKernel *>(cdata);
return kernel->DoExecute(task_id);
}
int LshProjectionCPUKernel::Run() {
auto input_tensor0 = in_tensors_.at(0);
auto input_tensor1 = in_tensors_.at(1);
auto out_tensor0 = out_tensors_.at(0);
hash = reinterpret_cast<float *>(input_tensor0->MutableData());
in_data = reinterpret_cast<char *>(input_tensor1->MutableData());
weight = in_tensors_.size() == 2 ? nullptr : reinterpret_cast<float *>(in_tensors_.at(2)->MutableData());
output = reinterpret_cast<int32_t *>(out_tensor0->MutableData());
const size_t seed_size = sizeof(float);
const size_t input_item_size =
input_tensor1->ElementsNum() * sizeof(input_tensor1->data_type()) / input_tensor1->DimensionSize(0);
const size_t key_size = seed_size + input_item_size;
lsh_param_->seed_size_ = seed_size;
lsh_param_->in_item_size_ = input_item_size;
lsh_param_->key_size_ = key_size;
lsh_param_->in_item_num_ = input_tensor1->DimensionSize(0);
memcpy(lsh_param_->hash_shape_, input_tensor0->shape().data(), sizeof(int) * input_tensor0->shape().size());
elements_num_ = input_tensor0->DimensionSize(0);
count_unit_ = thread_num_ > 1 ? UP_DIV(elements_num_, thread_num_) : elements_num_;
auto ret = ParallelLaunch(this->context_->thread_pool_, LshProjectionRun, this, thread_num_);
auto input0_tensor = in_tensors_.at(0);
auto input1_tensor = in_tensors_.at(1);
auto out_tensor = out_tensors_.at(0);
hash_seed_ = reinterpret_cast<float *>(input0_tensor->MutableData());
feature_ = reinterpret_cast<int32_t *>(input1_tensor->MutableData());
weight_ = in_tensors_.size() == 2 ? nullptr : reinterpret_cast<float *>(in_tensors_.at(2)->MutableData());
output_ = reinterpret_cast<int32_t *>(out_tensor->MutableData());
param_->hash_buff_size_ = sizeof(float) + sizeof(int32_t);
param_->feature_num_ = input1_tensor->ElementsNum();
param_->hash_shape_[0] = input0_tensor->DimensionSize(0);
param_->hash_shape_[1] = input0_tensor->DimensionSize(1);
param_->thread_stride_ = op_parameter_->thread_num_ > 1 ? UP_DIV(param_->hash_shape_[0], op_parameter_->thread_num_)
: param_->hash_shape_[0];
auto ret = MallocKeys();
if (ret != RET_OK) {
return ret;
}
ret = ParallelLaunch(this->context_->thread_pool_, LshProjectionRun, this, op_parameter_->thread_num_);
if (ret != RET_OK) {
MS_LOG(ERROR) << "LshProjection kernel parallel launch failed";
}
FreeKeys();
return ret;
}
int LshProjectionRun(void *cdata, int task_id) {
auto lsh_projection = reinterpret_cast<LshProjectionCPUKernel *>(cdata);
lsh_projection->DoExecute(task_id);
int LshProjectionCPUKernel::MallocKeys() {
param_->hash_buffs_ = static_cast<char **>(context_->allocator->Malloc(op_parameter_->thread_num_ * sizeof(char *)));
if (param_->hash_buffs_ == nullptr) {
MS_LOG(ERROR) << "Memory allocation failed";
return RET_ERROR;
}
for (int i = 0; i < op_parameter_->thread_num_; i++) {
param_->hash_buffs_[i] = static_cast<char *>(context_->allocator->Malloc(param_->hash_buff_size_));
if (param_->hash_buffs_[i] == nullptr) {
FreeKeys();
MS_LOG(ERROR) << "Memory allocation failed";
return RET_ERROR;
}
}
return RET_OK;
}
int LshProjectionCPUKernel::DoExecute(int task_id) {
int64_t real_dst_count = MSMIN(elements_num_ - task_id * count_unit_, count_unit_);
lsh_param_->real_dst_count = real_dst_count;
lsh_param_->task_id_ = task_id;
lsh_param_->count_unit_ = count_unit_;
if (real_dst_count <= 0) {
return lite::RET_OK;
void LshProjectionCPUKernel::FreeKeys() {
if (param_->hash_buffs_ != nullptr) {
for (int i = 0; i < op_parameter_->thread_num_; i++) {
context_->allocator->Free(param_->hash_buffs_[i]);
}
context_->allocator->Free(param_->hash_buffs_);
}
}
int LshProjectionCPUKernel::DoExecute(int task_id) {
int cur_group_num = MSMIN(param_->hash_shape_[0] - task_id * param_->thread_stride_, param_->thread_stride_);
int start = task_id * param_->thread_stride_;
int end = start + cur_group_num;
char *hash_buff = param_->hash_buffs_[task_id];
switch (lsh_param_->lsh_type_) {
switch (param_->lsh_type_) {
case schema::LshProjectionType_SPARSE:
LshProjectionSparse(hash, in_data, weight, output, lsh_param_);
LshProjectionSparse(hash_seed_, feature_, weight_, output_, param_, start, end, hash_buff);
break;
case schema::LshProjectionType_DENSE:
LshProjectionDense(hash, in_data, weight, output, lsh_param_);
LshProjectionDense(hash_seed_, feature_, weight_, output_, param_, start, end, hash_buff);
break;
default:
return RET_ERROR;
@ -91,50 +114,43 @@ int LshProjectionCPUKernel::DoExecute(int task_id) {
return RET_OK;
}
int LshProjectionCPUKernel::GetSignBit(char *in_data, float *weight, float seed, LshProjectionParameter *para) {
int LshProjectionCPUKernel::GetSignBit(int32_t *feature_, float *weight_, float seed, LshProjectionParameter *para,
char *hash_buff) {
double score = 0.0;
for (int i = 0; i < para->in_item_num_; i++) {
char *key = static_cast<char *>(context_->allocator->Malloc(lsh_param_->key_size_));
if (key == nullptr) {
MS_LOG(ERROR) << "malloc key failed.";
return RET_ERROR;
}
memcpy(key, &seed, para->seed_size_);
memcpy(key + para->seed_size_, in_data, para->in_item_size_);
in_data += para->in_item_size_;
int64_t hash_i = static_cast<int64_t>(mindspore::lite::StringHash64(key, para->key_size_));
for (int i = 0; i < para->feature_num_; i++) {
memcpy(hash_buff, &seed, sizeof(float));
memcpy(hash_buff + sizeof(float), &(feature_[i]), sizeof(int32_t));
int64_t hash_i = static_cast<int64_t>(lite::StringHash64(hash_buff, para->hash_buff_size_));
double hash_d = static_cast<double>(hash_i);
if (weight == nullptr) {
if (weight_ == nullptr) {
score += hash_d;
} else {
score += weight[i] * hash_d;
score += weight_[i] * hash_d;
}
context_->allocator->Free(key);
}
return (score > 0) ? 1 : 0;
}
void LshProjectionCPUKernel::LshProjectionSparse(float *hash, char *in_data, float *weight, int32_t *output,
LshProjectionParameter *para) {
int start = para->task_id_ * para->count_unit_;
int end = start + para->real_dst_count;
void LshProjectionCPUKernel::LshProjectionSparse(float *hash_seed_, int32_t *feature_, float *weight_, int32_t *output_,
LshProjectionParameter *para, int32_t start, int32_t end,
char *hash_buff) {
for (int i = start; i < end; i++) {
int32_t hash_sign = 0;
for (int j = 0; j < para->hash_shape_[1]; j++) {
int bit = GetSignBit(in_data, weight, hash[i * para->hash_shape_[1] + j], para);
int bit = GetSignBit(feature_, weight_, hash_seed_[i * para->hash_shape_[1] + j], para, hash_buff);
hash_sign = (hash_sign << 1) | bit;
}
output[i] = hash_sign + i * (1 << para->hash_shape_[1]);
output_[i] = hash_sign + i * (1 << para->hash_shape_[1]);
}
}
void LshProjectionCPUKernel::LshProjectionDense(float *hash, char *in_data, float *weight, int32_t *output,
LshProjectionParameter *para) {
int start = para->task_id_ * para->count_unit_;
int end = start + para->real_dst_count;
void LshProjectionCPUKernel::LshProjectionDense(float *hash_seed_, int32_t *feature_, float *weight_, int32_t *output_,
LshProjectionParameter *para, int32_t start, int32_t end,
char *hash_buff) {
for (int i = start; i < end; i++) {
for (int j = 0; j < para->hash_shape_[1]; j++) {
output[i * para->hash_shape_[1] + j] = GetSignBit(in_data, weight, hash[i * para->hash_shape_[1] + j], para);
output_[i * para->hash_shape_[1] + j] =
GetSignBit(feature_, weight_, hash_seed_[i * para->hash_shape_[1] + j], para, hash_buff);
}
}
}
@ -144,16 +160,6 @@ kernel::LiteKernel *CpuLshProjectionFp32KernelCreator(const std::vector<lite::Te
OpParameter *op_parameter, const lite::InnerContext *ctx,
const kernel::KernelKey &desc,
const mindspore::lite::PrimitiveC *primitive) {
if (op_parameter == nullptr) {
MS_LOG(ERROR) << "Input op_parameter is nullptr!";
return nullptr;
}
if (ctx == nullptr) {
MS_LOG(ERROR) << "Input context is nullptr!";
free(op_parameter);
return nullptr;
}
MS_ASSERT(desc.type == schema::PrimitiveType_LshProjection);
auto *kernel = new (std::nothrow) LshProjectionCPUKernel(op_parameter, inputs, outputs, ctx, primitive);
if (kernel == nullptr) {
MS_LOG(ERROR) << "new LshProjectionCPUKernel fail!";
@ -171,5 +177,4 @@ kernel::LiteKernel *CpuLshProjectionFp32KernelCreator(const std::vector<lite::Te
}
REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_LshProjection, CpuLshProjectionFp32KernelCreator)
} // namespace mindspore::kernel

30
mindspore/lite/src/runtime/kernel/arm/fp32/lsh_projection.h
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@ -28,8 +28,8 @@ class LshProjectionCPUKernel : public LiteKernel {
LshProjectionCPUKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
const std::vector<lite::Tensor *> &outputs, const lite::InnerContext *ctx,
const mindspore::lite::PrimitiveC *primitive)
: LiteKernel(parameter, inputs, outputs, ctx, primitive), thread_num_(ctx->thread_num_) {
lsh_param_ = reinterpret_cast<LshProjectionParameter *>(op_parameter_);
: LiteKernel(parameter, inputs, outputs, ctx, primitive) {
param_ = reinterpret_cast<LshProjectionParameter *>(op_parameter_);
}
~LshProjectionCPUKernel() = default;
@ -37,23 +37,21 @@ class LshProjectionCPUKernel : public LiteKernel {
int ReSize() override;
int Run() override;
int DoExecute(int task_id);
int GetSignBit(char *in_data, float *weight, float seed, LshProjectionParameter *para);
void LshProjectionSparse(float *hash, char *in_data, float *weight, int32_t *output, LshProjectionParameter *param);
void LshProjectionDense(float *hash, char *in_data, float *weight, int32_t *output, LshProjectionParameter *param);
private:
LshProjectionParameter *lsh_param_ = nullptr;
int thread_num_;
int64_t elements_num_;
int64_t count_unit_;
float *hash = nullptr;
char *in_data = nullptr;
float *weight = nullptr;
int32_t *output = nullptr;
int MallocKeys();
void FreeKeys();
int GetSignBit(int32_t *feature_, float *weight_, float seed, LshProjectionParameter *para, char *hash_buff);
void LshProjectionSparse(float *hash_seed_, int32_t *feature_, float *weight_, int32_t *output_,
LshProjectionParameter *param, int32_t start, int32_t end, char *hash_buff);
void LshProjectionDense(float *hash_seed_, int32_t *feature_, float *weight_, int32_t *output_,
LshProjectionParameter *param, int32_t start, int32_t end, char *hash_buff);
LshProjectionParameter *param_ = nullptr;
float *hash_seed_ = nullptr;
int32_t *feature_ = nullptr;
float *weight_ = nullptr;
int32_t *output_ = nullptr;
};
int LshProjectionRun(void *cdata, int task_id);
} // namespace mindspore::kernel
#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_FP32_LSH_PROJECTION_H_

30
mindspore/lite/tools/benchmark/benchmark.cc
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@ -98,17 +98,27 @@ int Benchmark::ReadInputFile() {
MS_LOG(ERROR) << "ReadFile return nullptr";
return RET_ERROR;
}
auto tensor_data_size = cur_tensor->Size();
if (size != tensor_data_size) {
std::cerr << "Input binary file size error, required: " << tensor_data_size << ", in fact: " << size
<< std::endl;
MS_LOG(ERROR) << "Input binary file size error, required: " << tensor_data_size << ", in fact: " << size;
delete bin_buf;
return RET_ERROR;
if (cur_tensor->data_type() == kObjectTypeString) {
std::string str(bin_buf, size);
auto ret = StringsToMSTensor({str}, cur_tensor);
if (ret != RET_OK) {
MS_LOG(ERROR) << "write strings to tensor failed";
delete[] bin_buf;
return RET_ERROR;
}
} else {
auto tensor_data_size = cur_tensor->Size();
if (size != tensor_data_size) {
std::cerr << "Input binary file size error, required: " << tensor_data_size << ", in fact: " << size
<< std::endl;
MS_LOG(ERROR) << "Input binary file size error, required: " << tensor_data_size << ", in fact: " << size;
delete[] bin_buf;
return RET_ERROR;
}
auto input_data = cur_tensor->MutableData();
memcpy(input_data, bin_buf, tensor_data_size);
}
auto input_data = cur_tensor->MutableData();
memcpy(input_data, bin_buf, tensor_data_size);
delete[](bin_buf);
delete[] bin_buf;
}
}
return RET_OK;

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