!7279 [MSLITE][Develop] add HashtableLookup kernel

Merge pull request !7279 from sunsuodong/hashtable_lookup
pull/7279/MERGE
mindspore-ci-bot 4 years ago committed by Gitee
commit 438cd08016

@ -34,26 +34,27 @@ int CustomExtractFeatures::UnPackToFlatBuilder(const schema::Primitive *primitiv
int CustomExtractFeatures::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
auto input = inputs_.at(0);
MS_ASSERT(input != nullptr);
if (input->data_c() == nullptr) {
MS_LOG(INFO) << "Do infer shape in runtime.";
return RET_INFER_INVALID;
}
int string_num = lite::GetStringCount(input);
auto output0 = outputs_.at(0);
auto output1 = outputs_.at(1);
MS_ASSERT(input != nullptr);
MS_ASSERT(output0 != nullptr);
MS_ASSERT(output1 != nullptr);
output0->set_data_type(input->data_type());
output0->SetFormat(input->GetFormat());
output1->set_data_type(input->data_type());
output1->SetFormat(input->GetFormat());
if (input->data_c() == nullptr) {
MS_LOG(INFO) << "Do infer shape in runtime.";
return RET_INFER_INVALID;
}
std::vector<int> shape;
int string_num = lite::GetStringCount(input);
shape.push_back(string_num == 0 ? 1 : string_num);
output0->set_shape(shape);
output0->set_data_type(input->data_type());
output0->SetFormat(input->GetFormat());
output1->set_shape(shape);
output1->set_data_type(input->data_type());
output1->SetFormat(input->GetFormat());
return RET_OK;
}
} // namespace lite

@ -14,6 +14,7 @@
* limitations under the License.
*/
#include "src/ops/hashtable_lookup.h"
#include "src/common/string_util.h"
namespace mindspore {
namespace lite {
@ -30,8 +31,34 @@ int HashtableLookup::UnPackToFlatBuilder(const schema::Primitive *primitive, fla
}
#endif
int HashtableLookup::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> outputs_) {
PrimitiveC::InferShape(inputs_, outputs_);
return RET_INFER_INVALID;
auto input = inputs_.at(0);
auto values = inputs_.at(2);
auto output = outputs_.at(0);
auto hits = outputs_.at(1);
MS_ASSERT(input != nullptr);
MS_ASSERT(keys != nullptr);
MS_ASSERT(values != nullptr);
MS_ASSERT(output != nullptr);
MS_ASSERT(hits != nullptr);
std::vector<int> hits_shape;
hits_shape.push_back(input->DimensionSize(0));
output->set_data_type(values->data_type());
output->SetFormat(input->GetFormat());
hits->set_shape(hits_shape);
hits->set_data_type(kNumberTypeUInt8);
hits->SetFormat(input->GetFormat());
if (input->data_c() == nullptr) {
MS_LOG(INFO) << "Do infer shape in runtime.";
return RET_INFER_INVALID;
}
int string_num = lite::GetStringCount(input);
std::vector<int> output_shape;
output_shape.push_back(string_num == 0 ? 1 : string_num);
output->set_shape(output_shape);
return RET_OK;
}
} // namespace lite
} // namespace mindspore

@ -1746,6 +1746,7 @@ PopulateParameterRegistry::PopulateParameterRegistry() {
populate_parameter_funcs_[schema::PrimitiveType_SkipGram] = PopulateSkipGramParameter;
populate_parameter_funcs_[schema::PrimitiveType_CustomExtractFeatures] = PopulateCommonOpParameter;
populate_parameter_funcs_[schema::PrimitiveType_CustomPredict] = PopulateCustomPredictParameter;
populate_parameter_funcs_[schema::PrimitiveType_HashtableLookup] = PopulateCommonOpParameter;
}
PopulateParameterRegistry *PopulateParameterRegistry::GetInstance() {

@ -0,0 +1,96 @@
/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "src/runtime/kernel/arm/string/hashtable_lookup.h"
#include <string>
#include <algorithm>
#include "src/kernel_registry.h"
#include "src/common/string_util.h"
using mindspore::lite::KernelRegistrar;
using mindspore::schema::PrimitiveType_HashtableLookup;
namespace mindspore::kernel {
int HashtableLookupCPUKernel::Init() {
if (!InferShapeDone()) {
return RET_OK;
}
return ReSize();
}
int HashtableLookupCPUKernel::ReSize() { return RET_OK; }
static int CmpKeyFunc(const void *lhs, const void *rhs) {
return *static_cast<const int *>(lhs) - *static_cast<const int *>(rhs);
}
int HashtableLookupCPUKernel::Run() {
auto ret = Prepare();
if (ret != RET_OK) {
MS_LOG(ERROR) << "Prepare fail! Ret error code: " << ret;
return ret;
}
auto input_tensor = in_tensors_.at(0);
auto keys_tensor = in_tensors_.at(1);
auto values_tensor = in_tensors_.at(2);
auto output_tensor = out_tensors_.at(0);
auto hits_tensor = out_tensors_.at(1);
int rows = values_tensor->DimensionSize(0);
int32_t *input_data = reinterpret_cast<int32_t *>(input_tensor->MutableData());
uint8_t *hits_data = reinterpret_cast<uint8_t *>(hits_tensor->MutableData());
std::vector<lite::StringPack> output_string_pack;
std::vector<lite::StringPack> all_string_pack = ParseTensorBuffer(input_tensor);
for (int i = 0; i < input_tensor->ElementsNum(); i++) {
int index = -1;
void *p = bsearch(&(input_data[i]), keys_tensor->MutableData(), rows, sizeof(int32_t), CmpKeyFunc);
if (p != nullptr) {
index = reinterpret_cast<int32_t *>(p) - reinterpret_cast<int32_t *>(keys_tensor->MutableData());
}
if (index >= rows || index < 0) {
lite::StringPack tmp = {0, nullptr};
output_string_pack.push_back(tmp);
hits_data[i] = 0;
} else {
output_string_pack.push_back(all_string_pack[i]);
hits_data[i] = 1;
}
}
WriteStringsToTensor(output_tensor, output_string_pack);
return RET_OK;
}
kernel::LiteKernel *CpuHashtableLookupKernelCreator(const std::vector<lite::Tensor *> &inputs,
const std::vector<lite::Tensor *> &outputs, OpParameter *parameter,
const lite::InnerContext *ctx, const kernel::KernelKey &desc,
const mindspore::lite::PrimitiveC *primitive) {
auto *kernel = new (std::nothrow) HashtableLookupCPUKernel(parameter, inputs, outputs, ctx, primitive);
if (kernel == nullptr) {
MS_LOG(ERROR) << "new HashtableLookupCPUKernel fail!";
return nullptr;
}
auto ret = kernel->Init();
if (ret != RET_OK) {
MS_LOG(ERROR) << "Init kernel failed, name: " << parameter->name_
<< ", type: " << schema::EnumNamePrimitiveType(static_cast<schema::PrimitiveType>(parameter->type_));
delete kernel;
return nullptr;
}
return kernel;
}
REG_KERNEL(kCPU, kNumberTypeFloat32, PrimitiveType_HashtableLookup, CpuHashtableLookupKernelCreator)
} // namespace mindspore::kernel

@ -0,0 +1,38 @@
/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_STRING_HASHTABLE_LOOKUP_H_
#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_STRING_HASHTABLE_LOOKUP_H_
#include <vector>
#include "src/lite_kernel.h"
#include "include/context.h"
namespace mindspore::kernel {
class HashtableLookupCPUKernel : public LiteKernel {
public:
HashtableLookupCPUKernel(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) {}
~HashtableLookupCPUKernel() {}
int Init() override;
int ReSize() override;
int Run() override;
};
} // namespace mindspore::kernel
#endif // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_STRING_HASHTABLE_LOOKUP_H_

@ -68,7 +68,7 @@ std::vector<LabelInfo> PredictCPUKernel::GetLabelInfo() {
return label_info_vec;
}
bool LabelInfoCmp(const LabelInfo &lhs, const LabelInfo &rhs) { return lhs.weight > rhs.weight; }
static bool LabelInfoCmp(const LabelInfo &lhs, const LabelInfo &rhs) { return lhs.weight > rhs.weight; }
int PredictCPUKernel::Run() {
auto ret = Prepare();

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