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!36260 fix code check 

Merge pull request !36260 from liyan2022/master
This commit is contained in:
i-robot 2022-06-24 09:11:52 +00:00 committed by Gitee
parent 260112518e eb56ead558
commit 8323815c57
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GPG Key ID: 173E9B9CA92EEF8F
18 changed files with 43 additions and 51 deletions
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5
include/api/types.h
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@ -368,8 +368,9 @@ struct MSCallBackParam {
};
/// \brief KernelCallBack defined the function pointer for callBack.
using MSKernelCallBack = std::function<bool(const std::vector<MSTensor> &inputs, const std::vector<MSTensor> &outputs,
const MSCallBackParam &opInfo)>;
using MSKernelCallBack =
std::function<bool(const std::vector<MSTensor> & /* inputs */, const std::vector<MSTensor> & /* outputs */,
const MSCallBackParam &opInfo)>;
std::vector<char> CharVersion();
inline std::string Version() { return CharToString(CharVersion()); }

38
mindspore/lite/tools/converter/quantizer/cle_pattern.cc
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@ -42,7 +42,7 @@ bool IsLinearActivation(const api::SharedPtr<ops::Conv2DFusion> &conv2d) {
return false;
}
bool IsCommonConvNode(const BaseRef &n) {
bool IsConvNode(const BaseRef &n, ConvNode node) {
if (utils::isa<AnfNodePtr>(n)) {
auto anf_node = utils::cast<AnfNodePtr>(n);
if (!opt::CheckPrimitiveType(anf_node, prim::kPrimConv2DFusion)) {
@ -58,32 +58,24 @@ bool IsCommonConvNode(const BaseRef &n) {
if (conv == nullptr) {
return false;
}
return conv->get_group() == 1;
if (node == COMMON_CONV) {
return conv->get_group() == 1;
} else if (node == DEPTHWISE_CONV) {
bool ret = IsLinearActivation(conv) && conv->GetAttr(ops::kIsDepthWise) != nullptr &&
GetValue<bool>(conv->GetAttr(ops::kIsDepthWise));
return ret;
} else {
MS_LOG(ERROR) << "Not supported conv node type.";
return false;
}
}
return false;
}
bool IsDepthWiseConvNode(const BaseRef &n) {
if (utils::isa<AnfNodePtr>(n)) {
auto anf_node = utils::cast<AnfNodePtr>(n);
if (!opt::CheckPrimitiveType(anf_node, prim::kPrimConv2DFusion)) {
return false;
}
api::SharedPtr<ops::Conv2DFusion> conv = nullptr;
if (utils::isa<CNodePtr>(anf_node)) {
auto c_node = anf_node->cast<CNodePtr>();
conv = ops::GetOperator<ops::Conv2DFusion>(c_node->input(0));
} else if (utils::isa<ValueNodePtr>(anf_node)) {
conv = ops::GetOperator<ops::Conv2DFusion>(anf_node);
}
if (conv == nullptr || !IsLinearActivation(conv)) {
return false;
}
auto ret = conv->GetAttr(ops::kIsDepthWise) != nullptr && GetValue<bool>(conv->GetAttr(ops::kIsDepthWise));
return ret;
}
return false;
}
bool IsCommonConvNode(const BaseRef &n) { return IsConvNode(n, COMMON_CONV); }
bool IsDepthWiseConvNode(const BaseRef &n) { return IsConvNode(n, DEPTHWISE_CONV); }
VectorRef CLEPattern::DefineConvWithConvPattern() const {
auto is_conv1 = std::make_shared<CondVar>(IsCommonConvNode);

1
mindspore/lite/tools/converter/quantizer/cle_pattern.h
View File

@ -31,6 +31,7 @@ struct CombinationLayer {
};
constexpr size_t kInputsNum2 = 2;
constexpr size_t kInputsNum3 = 3;
enum ConvNode { COMMON_CONV, DEPTHWISE_CONV };
class CLEPattern : public opt::MultiplePatternProcessPass {
public:
explicit CLEPattern(const std::string &name = "CLEPattern", bool multigraph = true)

2
mindspore/lite/tools/converter/quantizer/cle_strategy.cc
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@ -33,8 +33,6 @@
namespace mindspore::lite::quant {
using lite::RET_ERROR;
using lite::RET_OK;
static const std::set<std::string> kSupportCLENode = {
schema::EnumNamePrimitiveType(schema::PrimitiveType_Conv2DFusion)};
static const float kDefaultScale = 1;
int CLEStrategy::Run() {
MS_LOG(INFO) << "CLE start to find pattern.";

13
mindspore/lite/tools/converter/quantizer/data_distribution.cc
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@ -112,7 +112,7 @@ void DataDistribution::HandleBinForKL(int quant_bint_nums, int bin_index, std::v
float left_scale = 0.0f;
if (left_upper > start) {
left_scale = left_upper - start;
if (this->histogram_[left_upper - 1] != 0) {
if (!IsZero(this->histogram_[left_upper - 1])) {
count += left_scale;
}
}
@ -120,12 +120,13 @@ void DataDistribution::HandleBinForKL(int quant_bint_nums, int bin_index, std::v
double right_scale = 0.0f;
if (right_lower < end) {
right_scale = end - right_lower;
if (this->histogram_[right_lower] != 0) {
if (!IsZero(this->histogram_[right_lower])) {
count += right_scale;
}
}
std::for_each(this->histogram_.begin() + left_upper, this->histogram_.begin() + right_lower, [&count](float item) {
if (item != 0) {
bool is_zero = (item <= kEps && item >= -kEps);
if (!is_zero) {
count += 1;
}
});
@ -133,14 +134,14 @@ void DataDistribution::HandleBinForKL(int quant_bint_nums, int bin_index, std::v
continue;
}
const float average_num = quantized_histogram->at(i) / count;
if (left_upper > start && this->histogram_[left_upper - 1] != 0) {
if (left_upper > start && !IsZero(this->histogram_[left_upper - 1])) {
expanded_histogram->at(left_upper - 1) += average_num * left_scale;
}
if (right_lower < end && this->histogram_[right_lower] != 0) {
if (right_lower < end && !IsZero(this->histogram_[right_lower])) {
expanded_histogram->at(right_lower) += average_num * right_scale;
}
for (int k = left_upper; k < right_lower; ++k) {
if (this->histogram_[k] != 0) {
if (!IsZero(this->histogram_[k])) {
expanded_histogram->at(k) += average_num;
}
}

4
mindspore/lite/tools/converter/quantizer/data_distribution.h
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@ -21,6 +21,8 @@
#include "tools/converter/quantizer/quant_params.h"
#include "tools/converter/quantizer/quantize_util.h"
namespace mindspore::lite::quant {
constexpr float kEps = 1e-8;
class DataDistribution {
public:
DataDistribution() = default;
@ -78,6 +80,8 @@ class DataDistribution {
std::pair<float, float> CalQuantileMinMax(const std::vector<float> &min_datas, const std::vector<float> &max_datas);
inline bool IsZero(float x) { return (x <= kEps && x >= -kEps); }
private:
std::vector<float> histogram_;
CNodePtr cnode_;

4
mindspore/lite/tools/converter/quantizer/debug_info_manager.cc
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@ -94,7 +94,7 @@ std::string DebugInfoManager::ParseInOutTensorToString(InOutFlag in_out_flag) {
return "ERROR";
}
std::string DebugInfoManager::ParseDataTypeFlagToString(DataTypeFlag data_type_flag) {
std::string DebugInfoManager::ParseDataTypeFlagToString(DataTypeFlag data_type_flag) const {
switch (data_type_flag) {
case ORIGIN:
return "Origin";
@ -363,7 +363,7 @@ int DebugInfoManager::AddComparedInfo(const mindspore::MSCallBackParam &call_bac
}
std::map<std::string, mindspore::schema::Tensor *> DebugInfoManager::ParseInputTensors(
const mindspore::lite::LiteModel &model) {
const mindspore::lite::LiteModel &model) const {
std::map<std::string, mindspore::schema::Tensor *> maps;
for (auto &node : model.graph_.all_nodes_) {
for (auto &index : node->input_indices_) {

4
mindspore/lite/tools/converter/quantizer/debug_info_manager.h
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@ -112,7 +112,7 @@ class DebugInfoManager {
int tensor_index, QuantDebugInfo *quant_debug_info, const mindspore::lite::Tensor &tensor,
const quant::DebugMode &debug_mode);
std::string ParseDataTypeFlagToString(DataTypeFlag data_type_flag);
std::string ParseDataTypeFlagToString(DataTypeFlag data_type_flag) const;
std::string ParseTensorTypeFlagToString(TensorTypeFlag tensor_type_flag);
@ -122,7 +122,7 @@ class DebugInfoManager {
void SaveInfo(std::ofstream &out_file, const QuantDebugInfo &info);
std::map<std::string, mindspore::schema::Tensor *> ParseInputTensors(const mindspore::lite::LiteModel &model);
std::map<std::string, mindspore::schema::Tensor *> ParseInputTensors(const mindspore::lite::LiteModel &model) const;
std::map<std::string, mindspore::schema::Tensor *> ParseOutputTensorFromModel(const Model &model);

2
mindspore/lite/tools/converter/quantizer/fse_bit_stream.cc
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@ -58,7 +58,7 @@ void FSEBitStream::Empty() {
int64_t FSEBitStream::Pop(uint8_t bit_count) {
MS_ASSERT(curr_bit_count_ <= kCurrentBitCount);
int64_t right = curr_chunk_ >> (kCurrentBitCount - curr_bit_count_);
int64_t right = curr_chunk_ >> static_cast<size_t>(kCurrentBitCount - curr_bit_count_);
int64_t res = right & ((1 << bit_count) - 1);
curr_bit_count_ -= static_cast<int8_t>(bit_count);
if (curr_bit_count_ > 0) {

2
mindspore/lite/tools/converter/quantizer/full_quant_quantizer.cc
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@ -303,7 +303,7 @@ int FullQuantQuantizer::QuantNode(const FuncGraphPtr &func_graph) {
auto outputs_diverg_info = calibrator_->GetOutputDivergInfo();
auto cnodes = func_graph->GetOrderedCnodes();
for (auto &cnode : cnodes) {
for (const auto &cnode : cnodes) {
auto op_name = cnode->fullname_with_scope();
auto primitive = GetValueNode<PrimitivePtr>(cnode->input(0));
if (primitive == nullptr) {

1
mindspore/lite/tools/converter/quantizer/full_quant_quantizer.h
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@ -29,7 +29,6 @@
#include "schema/inner/model_generated.h"
#include "tools/converter/quantizer/quantizer.h"
#include "tools/converter/quantizer/quantize_util.h"
#include "tools/converter/quantizer/quant_params.h"
#include "tools/converter/preprocess/preprocess_param.h"
#include "tools/converter/quantizer/calibrator.h"
#include "tools/converter/quantizer/data_distribution.h"

2
mindspore/lite/tools/converter/quantizer/insert_quant_node_manager.cc
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@ -118,7 +118,7 @@ int InsertQuantNodeManager::InsertCastNode(const FuncGraphPtr &graph, const CNod
return RET_OK;
}
int InsertQuantNodeManager::CheckDataType(const AnfNodePtr &input_node, TypeId check_type_id) {
int InsertQuantNodeManager::CheckDataType(const AnfNodePtr &input_node, TypeId check_type_id) const {
bool is_graph_input = IsGraphInput(input_node);
if (!input_node->isa<mindspore::CNode>() && !is_graph_input) {
return RET_NO_CHANGE;

2
mindspore/lite/tools/converter/quantizer/insert_quant_node_manager.h
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@ -43,7 +43,7 @@ class InsertQuantNodeManager {
int InsertCastNode(const FuncGraphPtr &graph, const CNodePtr &cnode, size_t input_index, bool is_graph_input);
int CheckDataType(const AnfNodePtr &input_node, TypeId check_type_id);
int CheckDataType(const AnfNodePtr &input_node, TypeId check_type_id) const;
int NewDynamicQuantNode(const FuncGraphPtr &graph, const CNodePtr &cnode);

1
mindspore/lite/tools/converter/quantizer/mixed_bit_weight_quantizer.h
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@ -22,7 +22,6 @@
#include "schema/inner/model_generated.h"
#include "src/common/log_adapter.h"
#include "src/common/quant_utils.h"
#include "include/errorcode.h"
namespace mindspore::lite::quant {
constexpr float kBinarySearchStep = 2.0;

1
mindspore/lite/tools/converter/quantizer/quant_helper/conv_quant_type_determiner.cc
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@ -18,7 +18,6 @@
#include "tools/converter/quantizer/quant_helper/conv_quant_type_determiner.h"
#include "tools/converter/quantizer/quantize_util.h"
#include "src/common/log_adapter.h"
#include "mindspore/core/ir/dtype/type_id.h"
namespace mindspore::lite {
bool ConvQuantTypeDeterminer::DetermineQuantWeight(const mindspore::schema::MetaGraphT &graph,
mindspore::schema::CNodeT *node) {

2
mindspore/lite/tools/converter/quantizer/quantize_util.cc
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@ -82,7 +82,7 @@ int ComputeBiasDataAndQuantParam(const std::vector<double> &bias_scales, const s
quant_params->at(i).scale = bias_scale_tmp;
MS_LOG(DEBUG) << "new filter scale: " << filter_scale;
}
auto quant_data = (int32_t)std::round(raw_datas[i] / bias_scale_tmp);
auto quant_data = static_cast<int32_t>(std::round(raw_datas[i] / bias_scale_tmp));
quant_datas->at(i) = quant_data;
}
return RET_OK;

8
mindspore/lite/tools/converter/quantizer/quantize_util.h
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@ -215,9 +215,9 @@ bool IndexingCompress(const std::set<T> &quant_data_set, const std::map<T, size_
bits[index++] = (unique_value_cnt >> (bit_num - i - 1)) & (0x1);
}
// write the unique value set: each value has bit_num bit signed
for (auto unique_value : quant_data_set) {
for (auto iter = quant_data_set.cbegin(); iter != quant_data_set.cend(); ++iter) {
for (size_t i = 0; i < bit_num; i++) {
bits[index++] = ((unique_value + (1 << (bit_num - 1))) >> (bit_num - i - 1)) & (0x1);
bits[index++] = ((*iter + (1 << (bit_num - 1))) >> (bit_num - i - 1)) & (0x1);
}
}
// write the index: each index has unique_value_bit unsigned
@ -375,8 +375,8 @@ bool PackRepetition(size_t bit_num, schema::TensorT *tensor) {
}
std::map<T, size_t> unique_value_index_map;
auto index = 0;
for (auto value : quant_data_set) {
unique_value_index_map[value] = index++;
for (auto iter = quant_data_set.cbegin(); iter != quant_data_set.cend(); ++iter) {
unique_value_index_map[*iter] = index++;
}
auto unique_value_cnt = quant_data_set.size();

2
mindspore/lite/tools/converter/quantizer/quantizer.h
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@ -16,11 +16,9 @@
#ifndef MINDSPORE_LITE_TOOLS_CONVERTER_QUANTIZER_QUANTIZER_H_
#define MINDSPORE_LITE_TOOLS_CONVERTER_QUANTIZER_QUANTIZER_H_
#include <unordered_map>
#include <utility>
#include <memory>
#include "schema/inner/model_generated.h"
#include "include/errorcode.h"
#include "ir/func_graph.h"
#include "ir/anf.h"
#include "base/base.h"