select-dataset-list api solarPanelCnt 추가, spotless 적용 #181
@@ -254,6 +254,7 @@ public class DatasetDto {
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private Long wasteCnt;
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private Long landCoverCnt;
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private Integer solarPanelCnt;
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public SelectDataSet(
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String modelNo,
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@@ -308,6 +309,29 @@ public class DatasetDto {
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this.containerCnt = containerCnt;
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}
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public SelectDataSet(
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String modelNo,
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Long datasetId,
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UUID uuid,
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String dataType,
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String title,
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Long roundNo,
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Integer compareYyyy,
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Integer targetYyyy,
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String memo,
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Integer solarPanelCnt) {
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this.datasetId = datasetId;
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this.uuid = uuid;
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this.dataType = dataType;
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this.dataTypeName = getDataTypeName(dataType);
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this.title = title;
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this.roundNo = roundNo;
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this.compareYyyy = compareYyyy;
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this.targetYyyy = targetYyyy;
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this.memo = memo;
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this.solarPanelCnt = solarPanelCnt;
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}
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public String getDataTypeName(String groupTitleCd) {
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LearnDataType type = Enums.fromId(LearnDataType.class, groupTitleCd);
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return type == null ? null : type.getText();
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@@ -1,6 +1,7 @@
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package com.kamco.cd.training.model;
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import com.kamco.cd.training.common.dto.MonitorDto;
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import com.kamco.cd.training.common.enums.ModelType;
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import com.kamco.cd.training.common.service.SystemMonitorService;
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import com.kamco.cd.training.config.api.ApiResponseDto;
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import com.kamco.cd.training.dataset.dto.DatasetDto;
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@@ -143,9 +144,9 @@ public class ModelTrainMngApiController {
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@Parameter(
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description = "모델 구분",
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example = "",
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schema = @Schema(allowableValues = {"G1", "G2", "G3"}))
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schema = @Schema(allowableValues = {"G1", "G2", "G3", "G4"}))
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@RequestParam
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String modelType,
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ModelType modelType,
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@Parameter(
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description = "선택 구분",
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example = "",
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@@ -153,7 +154,7 @@ public class ModelTrainMngApiController {
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@RequestParam
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String selectType) {
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DatasetReq req = new DatasetReq();
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req.setModelNo(modelType);
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req.setModelNo(modelType.getId());
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req.setDataType(selectType);
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return ApiResponseDto.ok(modelTrainMngService.getDatasetSelectList(req));
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}
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@@ -51,10 +51,10 @@ public class ModelTrainMngService {
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@Value("${train.docker.response_dir}")
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private String responseDir;
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@Value("${train.docker.symbolic_link_dir}")
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private String symbolicDir;
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/**
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* 모델학습 조회
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*
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@@ -324,6 +324,8 @@ public class ModelTrainMngService {
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public List<SelectDataSet> getDatasetSelectList(DatasetReq req) {
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if (req.getModelNo().equals(ModelType.G1.getId())) {
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return modelTrainMngCoreService.getDatasetSelectG1List(req);
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} else if (req.getModelNo().equals(ModelType.G4.getId())) {
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return modelTrainMngCoreService.getDatasetSelectG4List(req);
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} else {
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return modelTrainMngCoreService.getDatasetSelectG2G3List(req);
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}
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@@ -337,6 +337,16 @@ public class ModelTrainMngCoreService {
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return datasetRepository.getDatasetTransferSelectG2G3List(modelId, modelNo);
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}
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/**
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* 데이터셋 G4 목록
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*
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* @param req
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* @return
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*/
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public List<SelectDataSet> getDatasetSelectG4List(DatasetReq req) {
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return datasetRepository.getDatasetSelectG4List(req);
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}
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// TODO 미사용 끝
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/**
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@@ -27,6 +27,8 @@ public interface DatasetRepositoryCustom {
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List<SelectDataSet> getDatasetSelectG2G3List(DatasetReq req);
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List<SelectDataSet> getDatasetSelectG4List(DatasetReq req);
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Long getDatasetMaxStage(int compareYyyy, int targetYyyy);
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Long insertDatasetMngData(DatasetMngRegDto mngRegDto);
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@@ -4,6 +4,7 @@ import static com.kamco.cd.training.postgres.entity.QDatasetObjEntity.datasetObj
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import static com.kamco.cd.training.postgres.entity.QModelDatasetMappEntity.modelDatasetMappEntity;
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import static com.kamco.cd.training.postgres.entity.QModelMasterEntity.modelMasterEntity;
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import com.kamco.cd.training.common.enums.DetectionClassification;
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import com.kamco.cd.training.common.enums.ModelType;
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import com.kamco.cd.training.dataset.dto.DatasetDto.DatasetMngRegDto;
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import com.kamco.cd.training.dataset.dto.DatasetDto.DatasetReq;
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@@ -104,10 +105,6 @@ public class DatasetRepositoryImpl implements DatasetRepositoryCustom {
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builder.and(dataset.dataType.eq(req.getDataType()));
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}
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if (StringUtils.isNotBlank(req.getDataType()) && !"CURRENT".equals(req.getDataType())) {
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builder.and(dataset.dataType.eq(req.getDataType()));
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}
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if (req.getIds() != null) {
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builder.and(dataset.id.in(req.getIds()));
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}
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@@ -126,12 +123,15 @@ public class DatasetRepositoryImpl implements DatasetRepositoryCustom {
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dataset.targetYyyy,
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dataset.memo,
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new CaseBuilder()
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.when(datasetObjEntity.targetClassCd.eq("building"))
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.when(
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datasetObjEntity.targetClassCd.eq(DetectionClassification.BUILDING.getId()))
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.then(1)
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.otherwise(0)
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.sum(),
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new CaseBuilder()
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.when(datasetObjEntity.targetClassCd.eq("container"))
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.when(
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datasetObjEntity.targetClassCd.eq(
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DetectionClassification.CONTAINER.getId()))
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.then(1)
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.otherwise(0)
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.sum()))
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@@ -249,19 +249,31 @@ public class DatasetRepositoryImpl implements DatasetRepositoryCustom {
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}
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// TODO 미사용 끝
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@Override
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public List<SelectDataSet> getDatasetSelectG2G3List(DatasetReq req) {
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String building = DetectionClassification.BUILDING.getId();
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String container = DetectionClassification.CONTAINER.getId();
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String waste = DetectionClassification.WASTE.getId();
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String solar = DetectionClassification.SOLAR.getId();
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BooleanBuilder builder = new BooleanBuilder();
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builder.and(dataset.deleted.isFalse());
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NumberExpression<Long> selectedCnt = null;
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NumberExpression<Long> wasteCnt =
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datasetObjEntity.targetClassCd.when("waste").then(1L).otherwise(0L).sum();
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datasetObjEntity
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.targetClassCd
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.when(DetectionClassification.WASTE.getId())
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.then(1L)
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.otherwise(0L)
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.sum();
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// G1, G2, G4 제외
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NumberExpression<Long> elseCnt =
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new CaseBuilder()
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.when(datasetObjEntity.targetClassCd.notIn("building", "container", "waste"))
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.when(datasetObjEntity.targetClassCd.notIn(building, container, waste, solar))
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.then(1L)
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.otherwise(0L)
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.sum();
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@@ -481,4 +493,53 @@ public class DatasetRepositoryImpl implements DatasetRepositoryCustom {
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.where(dataset.uid.eq(uid), dataset.deleted.isFalse())
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.fetchOne();
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}
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@Override
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public List<SelectDataSet> getDatasetSelectG4List(DatasetReq req) {
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BooleanBuilder builder = new BooleanBuilder();
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builder.and(dataset.deleted.isFalse());
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if (StringUtils.isNotBlank(req.getDataType()) && !"CURRENT".equals(req.getDataType())) {
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builder.and(dataset.dataType.eq(req.getDataType()));
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}
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if (req.getIds() != null) {
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builder.and(dataset.id.in(req.getIds()));
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}
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return queryFactory
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.select(
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Projections.constructor(
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SelectDataSet.class,
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Expressions.constant(req.getModelNo()),
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dataset.id,
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dataset.uuid,
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dataset.dataType,
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dataset.title,
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dataset.roundNo,
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dataset.compareYyyy,
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dataset.targetYyyy,
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dataset.memo,
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new CaseBuilder()
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.when(
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datasetObjEntity.targetClassCd.equalsIgnoreCase(
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DetectionClassification.SOLAR.getId()))
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.then(1)
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.otherwise(0)
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.sum()))
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.from(dataset)
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.leftJoin(datasetObjEntity)
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.on(dataset.id.eq(datasetObjEntity.datasetUid))
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.where(builder)
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.groupBy(
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dataset.id,
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dataset.uuid,
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dataset.dataType,
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dataset.title,
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dataset.roundNo,
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dataset.memo)
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.orderBy(dataset.createdDttm.desc())
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.fetch();
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}
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}
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@@ -262,9 +262,9 @@ public class DockerTrainService {
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c.add("-v");
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c.add(basePath + ":" + basePath); // 심볼릭 링크와 연결되는 실제 파일 경로도 마운트를 해줘야 함
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c.add("-v");
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c.add(symbolicDir + ":/data"); //요청할경로
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c.add(symbolicDir + ":/data"); // 요청할경로
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c.add("-v");
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c.add(responseDir + ":/checkpoints"); //저장될경로
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c.add(responseDir + ":/checkpoints"); // 저장될경로
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// 표준입력 유지 (-it 대신 -i만 사용)
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c.add("-i");
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@@ -384,7 +384,20 @@ public class JobRecoveryOnStartupService {
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return new OutputResult(false, "total-epoch-missing");
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}
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log.info("[RECOVERY] totalEpoch={}. jobId={}", totalEpoch, job.getId());
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Integer valInterval = extractValInterval(job).orElse(null);
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if (valInterval == null || valInterval <= 0) {
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log.warn(
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"[RECOVERY] valInterval missing or invalid. jobId={}, valInterval={}",
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job.getId(),
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valInterval);
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return new OutputResult(false, "val-interval-missing");
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}
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log.info(
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"[RECOVERY] totalEpoch={}. valInterval={}. jobId={}",
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totalEpoch,
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valInterval,
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job.getId());
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// 3) val.csv 존재 확인
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Path valCsv = outDir.resolve("val.csv");
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@@ -396,14 +409,17 @@ public class JobRecoveryOnStartupService {
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// 4) val.csv 라인 수 확인
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long lines = countNonHeaderLines(valCsv);
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// expected = 실제 val 실행 횟수
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int expectedLines = totalEpoch / valInterval;
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log.info(
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"[RECOVERY] val.csv lines counted. jobId={}, lines={}, expected={}",
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job.getId(),
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lines,
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totalEpoch);
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expectedLines);
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// 5) 완료 판정
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if (lines == totalEpoch) {
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if (lines >= expectedLines) {
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log.info("[RECOVERY] outputs look COMPLETE. jobId={}", job.getId());
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return new OutputResult(true, "ok");
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}
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@@ -412,7 +428,7 @@ public class JobRecoveryOnStartupService {
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"[RECOVERY] val.csv line mismatch. jobId={}, lines={}, expected={}",
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job.getId(),
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lines,
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totalEpoch);
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expectedLines);
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return new OutputResult(
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false, "val.csv-lines-mismatch lines=" + lines + " expected=" + totalEpoch);
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@@ -530,4 +546,19 @@ public class JobRecoveryOnStartupService {
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return reason;
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}
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}
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/** paramsJson에서 valInterval 추출 */
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private Optional<Integer> extractValInterval(ModelTrainJobDto job) {
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Map<String, Object> params = job.getParamsJson();
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if (params == null) return Optional.empty();
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Object v = params.get("valInterval");
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if (v == null) return Optional.empty();
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try {
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return Optional.of(Integer.parseInt(String.valueOf(v)));
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} catch (Exception ignore) {
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return Optional.empty();
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}
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}
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}
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@@ -19,6 +19,7 @@ public class TmpDatasetService {
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@Value("${train.docker.symbolic_link_dir}")
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private String symbolicDir;
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/**
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* train, val, test 폴더별로 link
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*
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@@ -132,7 +132,9 @@ public class TrainJobWorker {
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String failMsg = result.getStatus() + "\n" + result.getLogs();
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log.info("training fail exitCode={} Msg ={}", result.getExitCode(), failMsg);
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if (result.getExitCode() == -1 || result.getExitCode() == 143) {
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if (result.getExitCode() == -1
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|| result.getExitCode() == 143
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|| result.getExitCode() == 137) {
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// 실패 처리
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modelTrainJobCoreService.markPaused(
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jobId, result.getExitCode(), result.getStatus() + "\n" + result.getLogs());
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Reference in New Issue
Block a user