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!14541 [MS][LITE] move bitpack to anf exporter

Browse Source 
From: @jianghui58
Reviewed-by: @HilbertDavid,@jpc_chenjianping
Signed-off-by: @HilbertDavid
pull/14541/MERGE
mindspore-ci-bot 4 years ago committed by Gitee
parent 04c9f1df84 46e08fb5a1
commit 7ffcf05809
5 changed files with 91 additions and 22 deletions
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2
mindspore/lite/test/models_npu.cfg
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@ -67,7 +67,7 @@ ml_video_edit_v10_best_model_nomean_20200723 8
#hdc_ocr_detect.onnx 30 #too many subgraphs
ml_edu_kit_hand_detection.onnx 1
ml_edu_kit_hand_key_position.onnx 2
ml_video_edit_oneclick_adaptis.pb 2 3
ml_video_edit_oneclick_adaptis.pb 2.4 3
densenet.tflite 3
resnet_v2_101_299.tflite 1
ml_video_edit_enhance.pb 2

90
mindspore/lite/tools/anf_exporter/anf_exporter.cc
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@ -18,6 +18,7 @@
#include <list>
#include <memory>
#include <string>
#include <functional>
#include <utility>
#include <vector>
#include <algorithm>
@ -33,6 +34,7 @@
#include "ops/tuple_get_item.h"
#include "tools/converter/quant_param_holder.h"
#include "tools/optimizer/common/gllo_utils.h"
#include "tools/converter/quantizer/bitpacking.h"
#include "src/tensor.h"
#include "src/common/utils.h"
#include "ops/op_utils.h"
@ -233,6 +235,65 @@ void AnfExporter::RemoveIfDepend(const CNodePtr &cnode) {
}
}
int AnfExporter::DoBitPack(const int &bit_num, schema::TensorT *tensor_input) {
if (bit_num > 0 && bit_num < 8) {
std::vector<int8_t> origin_data(tensor_input->data.size());
if (memcpy_s(origin_data.data(), origin_data.size() * sizeof(int8_t), tensor_input->data.data(),
tensor_input->data.size() * sizeof(uint8_t)) != EOK) {
MS_LOG(ERROR) << "memcpy failed.";
return RET_ERROR;
}
std::vector<uint8_t> pack_data{};
BitPack::BitPacking<int8_t, uint8_t>(bit_num, origin_data, &pack_data);
tensor_input->data.resize(pack_data.size() * sizeof(uint8_t));
if (memcpy_s(tensor_input->data.data(), tensor_input->data.size() * sizeof(uint8_t), pack_data.data(),
pack_data.size() * sizeof(uint8_t)) != EOK) {
MS_LOG(ERROR) << "memcpy_s failed.";
return RET_ERROR;
}
} else if (bit_num > 9 && bit_num < 16) {
auto shape_size =
std::accumulate(tensor_input->dims.begin(), tensor_input->dims.end(), size_t(1), std::multiplies<size_t>());
std::vector<int16_t> origin_data(shape_size);
if (memcpy_s(origin_data.data(), origin_data.size() * sizeof(int16_t), tensor_input->data.data(),
tensor_input->data.size() * sizeof(uint8_t)) != EOK) {
MS_LOG(ERROR) << "memcpy failed.";
return RET_ERROR;
}
std::vector<uint16_t> pack_data{};
BitPack::BitPacking<int16_t, uint16_t>(bit_num, origin_data, &pack_data);
tensor_input->data.resize(pack_data.size() * sizeof(uint16_t));
if (memcpy_s(tensor_input->data.data(), tensor_input->data.size() * sizeof(uint8_t), pack_data.data(),
pack_data.size() * sizeof(uint16_t)) != EOK) {
MS_LOG(ERROR) << "memcpy_s failed.";
return RET_ERROR;
}
}
return RET_OK;
}
int AnfExporter::SetQuantOutputTensorType(const std::unique_ptr<schema::MetaGraphT> &meta_graph,
const std::shared_ptr<mindspore::Primitive> &primitive,
const std::unique_ptr<schema::CNodeT> &dst_node) {
auto first_output_index = dst_node->outputIndex[0];
auto first_tensor_output = meta_graph->allTensors[first_output_index].get();
if (dst_node->quantType == schema::QuantType_PostTraining) {
if (primitive->name() != mindspore::ops::kNameQuantDTypeCast) {
first_tensor_output->dataType = kNumberTypeInt8;
} else {
auto primc = primitive->cast<std::shared_ptr<mindspore::ops::QuantDTypeCast>>();
if (primc == nullptr) {
MS_LOG(ERROR) << "primitive is nullptr.";
return RET_ERROR;
}
if (primc->get_dst_t() != kNumberTypeFloat32) {
first_tensor_output->dataType = kNumberTypeInt8;
}
}
}
return RET_OK;
}
int AnfExporter::ConvertQuantParam(const std::unique_ptr<schema::MetaGraphT> &meta_graph,
const std::shared_ptr<mindspore::Primitive> &primitive,
const std::unique_ptr<schema::CNodeT> &dst_node) {
@ -268,14 +329,23 @@ int AnfExporter::ConvertQuantParam(const std::unique_ptr<schema::MetaGraphT> &me
auto tensor_input = meta_graph->allTensors[activate_index].get();
if (tensor_input->quantParams.empty()) {
for (auto input_quant_param : input_quant_params[i]) {
std::unique_ptr<schema::QuantParamT> input_quant_param_ptr =
std::make_unique<schema::QuantParamT>(input_quant_param);
auto input_quant_param_ptr = std::make_unique<schema::QuantParamT>(input_quant_param);
MS_LOG(DEBUG) << "[input][" << i << "]node: " << dst_node->name << " scale: " << input_quant_param_ptr->scale
<< " zp: " << input_quant_param_ptr->zeroPoint;
input_quant_param_ptr->dstDtype = tensor_input->dataType;
tensor_input->quantParams.emplace_back(std::move(input_quant_param_ptr));
}
}
if (!tensor_input->quantParams.empty()) {
int bit_num = tensor_input->quantParams.at(0)->numBits;
if (bit_num != 8 && bit_num != 16) {
auto status = DoBitPack(bit_num, tensor_input);
if (status != RET_OK) {
MS_LOG(ERROR) << "do bit pack failed.";
return RET_ERROR;
}
}
}
}
} else {
MS_LOG(DEBUG) << "node: " << dst_node->name << " input quant params is empty";
@ -308,18 +378,10 @@ int AnfExporter::ConvertQuantParam(const std::unique_ptr<schema::MetaGraphT> &me
}
}
auto first_output_index = dst_node->outputIndex[0];
auto first_tensor_output = meta_graph->allTensors[first_output_index].get();
if (dst_node->quantType == schema::QuantType_PostTraining) {
if (primitive->name() != mindspore::ops::kNameQuantDTypeCast) {
first_tensor_output->dataType = kNumberTypeInt8;
} else {
auto primc = primitive->cast<std::shared_ptr<mindspore::ops::QuantDTypeCast>>();
MS_ASSERT(primc != nullptr);
if (primc->get_dst_t() != kNumberTypeFloat32) {
first_tensor_output->dataType = kNumberTypeInt8;
}
}
auto status = SetQuantOutputTensorType(meta_graph, primitive, dst_node);
if (status != RET_OK) {
MS_LOG(ERROR) << "set quant output tensor data type failed.";
return RET_ERROR;
}
return RET_OK;
}

4
mindspore/lite/tools/anf_exporter/anf_exporter.h
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@ -75,6 +75,10 @@ class AnfExporter {
int SetGraphInputIndex(const std::unique_ptr<schema::MetaGraphT> &meta_graphT, const size_t &subgraph_index);
int SetGraphoutputIndex(const CNodePtr &cnode, size_t subgraph_index,
const std::unique_ptr<schema::MetaGraphT> &meta_graphT, schema::CNodeT *return_node);
static int DoBitPack(const int &bit_num, schema::TensorT *tensor_input);
static int SetQuantOutputTensorType(const std::unique_ptr<schema::MetaGraphT> &meta_graph,
const std::shared_ptr<mindspore::Primitive> &primitive,
const std::unique_ptr<schema::CNodeT> &dst_node);
static int ConvertQuantParam(const std::unique_ptr<schema::MetaGraphT> &meta_graph,
const std::shared_ptr<mindspore::Primitive> &primitive,
const std::unique_ptr<schema::CNodeT> &dst_node);

10
mindspore/lite/tools/converter/parser/tf/tf_model_parser.cc
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@ -243,6 +243,16 @@ STATUS SetStringTensorInfo(const tensorflow::TensorProto &tensor_proto, tensor::
for (int i = 0; i < tensor_shape.dim_size(); i++) {
shape_vector.push_back(tensor_shape.dim(i).size());
}
if (shape_vector.empty()) {
*tensor_info = CreateTensorInfo(nullptr, 0, shape_vector, kObjectTypeString);
if (*tensor_info == nullptr) {
MS_LOG(ERROR) << "create tensor info failed.";
return RET_ERROR;
}
return RET_OK;
}
std::string shape_str;
shape_str += std::to_string(shape_vector.size()) + ",";
for (auto &dim : shape_vector) {

7
mindspore/lite/tools/converter/quantizer/quantize_util.h
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@ -389,13 +389,6 @@ STATUS QuantFilter(const tensor::TensorPtr &weight, const PrimitivePtr &primitiv
MS_LOG(ERROR) << "Do huffman encode failed.";
return ret;
}
#else
// do bit pack
ret = DoBitPack(weight, bit_num, quant_data);
if (ret != RET_OK) {
MS_LOG(ERROR) << "Do bit pack failed.";
return ret;
}
#endif
if (quant_params.empty()) {

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