| 提交 | 用户 | 时间 | ||
| 7fd198 | 1 | package com.iailab.module.model.mdk.predict.impl; |
| 潘 | 2 | |
| 3 | import com.alibaba.fastjson.JSONArray; | |
| 4 | import com.alibaba.fastjson.JSONObject; | |
| 5 | import com.iail.model.IAILModel; | |
| 4f1717 | 6 | import com.iailab.module.model.common.enums.CommonConstant; |
| 373ab1 | 7 | import com.iailab.module.model.common.enums.OutResultType; |
| 69bd5e | 8 | import com.iailab.module.model.mcs.pre.entity.MmItemOutputEntity; |
| 7fd198 | 9 | import com.iailab.module.model.mcs.pre.entity.MmModelArithSettingsEntity; |
| 潘 | 10 | import com.iailab.module.model.mcs.pre.entity.MmPredictModelEntity; |
| 69bd5e | 11 | import com.iailab.module.model.mcs.pre.service.MmItemOutputService; |
| 7fd198 | 12 | import com.iailab.module.model.mcs.pre.service.MmModelArithSettingsService; |
| 潘 | 13 | import com.iailab.module.model.mdk.common.enums.TypeA; |
| 14 | import com.iailab.module.model.mdk.common.exceptions.ModelInvokeException; | |
| 15 | import com.iailab.module.model.mdk.predict.PredictModelHandler; | |
| 16 | import com.iailab.module.model.mdk.sample.SampleConstructor; | |
| 17 | import com.iailab.module.model.mdk.sample.dto.SampleData; | |
| 18 | import com.iailab.module.model.mdk.vo.PredictResultVO; | |
| 1a2b62 | 19 | import com.iailab.module.model.mpk.common.utils.DllUtils; |
| 7fd198 | 20 | import lombok.extern.slf4j.Slf4j; |
| 潘 | 21 | import org.springframework.beans.factory.annotation.Autowired; |
| 22 | import org.springframework.stereotype.Component; | |
| 23 | ||
| 69bd5e | 24 | import java.util.*; |
| 7fd198 | 25 | |
| 潘 | 26 | /** |
| 27 | * @author PanZhibao | |
| 28 | * @Description | |
| 29 | * @createTime 2024年09月01日 | |
| 30 | */ | |
| 31 | @Slf4j | |
| 32 | @Component | |
| 33 | public class PredictModelHandlerImpl implements PredictModelHandler { | |
| 34 | ||
| 35 | @Autowired | |
| 36 | private MmModelArithSettingsService mmModelArithSettingsService; | |
| 37 | ||
| 38 | @Autowired | |
| 69bd5e | 39 | private MmItemOutputService mmItemOutputService; |
| 7fd198 | 40 | |
| 潘 | 41 | @Autowired |
| 42 | private SampleConstructor sampleConstructor; | |
| 43 | ||
| 4f1717 | 44 | /** |
| 潘 | 45 | * 根据模型预测,返回预测结果 |
| 46 | * | |
| 47 | * @param predictTime | |
| 48 | * @param predictModel | |
| 49 | * @return | |
| 50 | * @throws ModelInvokeException | |
| 51 | */ | |
| 7fd198 | 52 | @Override |
| 4f1717 | 53 | public synchronized PredictResultVO predictByModel(Date predictTime, MmPredictModelEntity predictModel) throws ModelInvokeException { |
| 7fd198 | 54 | PredictResultVO result = new PredictResultVO(); |
| 潘 | 55 | if (predictModel == null) { |
| 56 | throw new ModelInvokeException("modelEntity is null"); | |
| 57 | } | |
| 58 | String modelId = predictModel.getId(); | |
| 59 | try { | |
| 60 | List<SampleData> sampleDataList = sampleConstructor.constructSample(TypeA.Predict.name(), modelId, predictTime); | |
| 61 | String modelPath = predictModel.getModelpath(); | |
| 62 | if (modelPath == null) { | |
| 373ab1 | 63 | log.info("模型路径不存在，modelId=" + modelId); |
| 7fd198 | 64 | return null; |
| 潘 | 65 | } |
| 66 | IAILModel newModelBean = composeNewModelBean(predictModel); | |
| 67 | HashMap<String, Object> settings = getPredictSettingsByModelId(modelId); | |
| 68 | if (settings == null) { | |
| 69 | log.error("模型setting不存在，modelId=" + modelId); | |
| 70 | return null; | |
| 71 | } | |
| 72 | int portLength = sampleDataList.size(); | |
| 73 | Object[] param2Values = new Object[portLength + 2]; | |
| 74 | for (int i = 0; i < portLength; i++) { | |
| 4f1717 | 75 | param2Values[i] = sampleDataList.get(i).getMatrix(); |
| 7fd198 | 76 | } |
| 潘 | 77 | param2Values[portLength] = newModelBean.getDataMap().get("models"); |
| 4f1717 | 78 | param2Values[portLength + 1] = settings; |
| 7fd198 | 79 | |
| 潘 | 80 | log.info("#######################预测模型 " + predictModel.getItemid() + " ##########################"); |
| 81 | JSONObject jsonObjNewModelBean = new JSONObject(); | |
| 82 | jsonObjNewModelBean.put("newModelBean", newModelBean); | |
| 83 | log.info(String.valueOf(jsonObjNewModelBean)); | |
| 84 | JSONObject jsonObjParam2Values = new JSONObject(); | |
| 85 | jsonObjParam2Values.put("param2Values", param2Values); | |
| 86 | log.info(String.valueOf(jsonObjParam2Values)); | |
| 87 | ||
| 88 | //IAILMDK.run | |
| 1a2b62 | 89 | HashMap<String, Object> modelResult = DllUtils.run(newModelBean, param2Values, predictModel.getMpkprojectid()); |
| 4f1717 | 90 | if (!modelResult.containsKey(CommonConstant.MDK_STATUS_CODE) || !modelResult.containsKey(CommonConstant.MDK_RESULT) || |
| 潘 | 91 | !modelResult.get(CommonConstant.MDK_STATUS_CODE).toString().equals(CommonConstant.MDK_STATUS_100)) { |
| b2aca2 | 92 | throw new RuntimeException("模型结果异常：" + modelResult); |
| D | 93 | } |
| 4f1717 | 94 | modelResult = (HashMap<String, Object>) modelResult.get(CommonConstant.MDK_RESULT); |
| 7fd198 | 95 | //打印结果 |
| 51c1c2 | 96 | log.info("预测模型计算完成：modelId=" + modelId + modelResult); |
| 7fd198 | 97 | JSONObject jsonObjResult = new JSONObject(); |
| 1a2b62 | 98 | jsonObjResult.put("result", modelResult); |
| 7fd198 | 99 | log.info(String.valueOf(jsonObjResult)); |
| 潘 | 100 | |
| 373ab1 | 101 | List<MmItemOutputEntity> itemOutputList = mmItemOutputService.getByItemid(predictModel.getItemid()); |
| 潘 | 102 | Map<MmItemOutputEntity, double[]> predictMatrixs = new HashMap<>(itemOutputList.size()); |
| 103 | for (MmItemOutputEntity output : itemOutputList) { | |
| 104 | if (!modelResult.containsKey(output.getResultstr())) { | |
| 105 | continue; | |
| 106 | } | |
| 107 | OutResultType outResultType = OutResultType.getEumByCode(output.getResultType()); | |
| 108 | switch (outResultType) { | |
| 109 | case D1: | |
| 110 | double[] temp1 = (double[]) modelResult.get(output.getResultstr()); | |
| 111 | predictMatrixs.put(output, temp1); | |
| 112 | break; | |
| 113 | case D2: | |
| 114 | double[][] temp2 = (double[][]) modelResult.get(output.getResultstr()); | |
| 115 | double[] tempColumn = new double[temp2.length]; | |
| 116 | for (int i = 0; i < tempColumn.length; i++) { | |
| 117 | tempColumn[i] = temp2[i][output.getResultIndex()]; | |
| 69bd5e | 118 | } |
| 373ab1 | 119 | predictMatrixs.put(output, tempColumn); |
| 潘 | 120 | break; |
| 121 | default: | |
| 122 | break; | |
| 1a2b62 | 123 | } |
| D | 124 | } |
| 69bd5e | 125 | result.setPredictMatrixs(predictMatrixs); |
| 1a2b62 | 126 | result.setModelResult(modelResult); |
| 7fd198 | 127 | result.setPredictTime(predictTime); |
| 潘 | 128 | } catch (Exception ex) { |
| 4f1717 | 129 | log.error("调用发生异常，异常信息为:{}", ex); |
| 7fd198 | 130 | ex.printStackTrace(); |
| ead005 | 131 | throw new ModelInvokeException(ex.getMessage()); |
| 7fd198 | 132 | } |
| 潘 | 133 | return result; |
| 134 | } | |
| 135 | ||
| 136 | /** | |
| 137 | * 构造IAILMDK.run()方法的newModelBean参数 | |
| 138 | * | |
| 139 | * @param predictModel | |
| 140 | * @return | |
| 141 | */ | |
| 142 | private IAILModel composeNewModelBean(MmPredictModelEntity predictModel) { | |
| 143 | IAILModel newModelBean = new IAILModel(); | |
| 144 | newModelBean.setClassName(predictModel.getClassname().trim()); | |
| 145 | newModelBean.setMethodName(predictModel.getMethodname().trim()); | |
| 146 | //构造参数类型 | |
| 147 | String[] paArStr = predictModel.getModelparamstructure().trim().split(","); | |
| 148 | Class<?>[] paramsArray = new Class[paArStr.length]; | |
| 149 | for (int i = 0; i < paArStr.length; i++) { | |
| 150 | if ("[[D".equals(paArStr[i])) { | |
| 151 | paramsArray[i] = double[][].class; | |
| 152 | } else if ("Map".equals(paArStr[i]) || "java.util.HashMap".equals(paArStr[i])) { | |
| 153 | paramsArray[i] = HashMap.class; | |
| 154 | } | |
| 155 | } | |
| 156 | newModelBean.setParamsArray(paramsArray); | |
| 157 | HashMap<String, Object> dataMap = new HashMap<>(); | |
| 158 | HashMap<String, String> models = new HashMap<>(1); | |
| b2aca2 | 159 | models.put("model_path", predictModel.getModelpath()); |
| 7fd198 | 160 | dataMap.put("models", models); |
| 潘 | 161 | newModelBean.setDataMap(dataMap); |
| 162 | return newModelBean; | |
| 163 | } | |
| 164 | ||
| 165 | /** | |
| 166 | * 根据模型id获取参数map | |
| 167 | * | |
| 168 | * @param modelId | |
| 169 | * @return | |
| 170 | */ | |
| 171 | private HashMap<String, Object> getPredictSettingsByModelId(String modelId) { | |
| 172 | List<MmModelArithSettingsEntity> list = mmModelArithSettingsService.getByModelId(modelId); | |
| 173 | HashMap<String, Object> result = new HashMap<>(); | |
| 174 | for (MmModelArithSettingsEntity entry : list) { | |
| 175 | String valueType = entry.getValuetype().trim(); //去除两端空格 | |
| 176 | if ("int".equals(valueType)) { | |
| 177 | int value = Integer.parseInt(entry.getValue()); | |
| 178 | result.put(entry.getKey(), value); | |
| 179 | } else if ("double".equals(valueType)) { | |
| 180 | double value = Double.parseDouble(entry.getValue()); | |
| 181 | result.put(entry.getKey(), value); | |
| 182 | } else if ("string".equals(valueType)) { | |
| 183 | String value = entry.getValue(); | |
| 184 | result.put(entry.getKey(), value); | |
| 185 | } else if ("decimalArray".equals(valueType)) { | |
| 186 | JSONArray valueArray = JSONArray.parseArray(entry.getValue()); | |
| 187 | double[] value = new double[valueArray.size()]; | |
| 188 | for (int i = 0; i < valueArray.size(); i++) { | |
| 189 | value[i] = Double.parseDouble(valueArray.get(i).toString()); | |
| 190 | } | |
| 191 | result.put(entry.getKey(), value); | |
| 192 | } else if ("decimal".equals(valueType)) { | |
| 193 | double value = Double.parseDouble(entry.getValue()); | |
| 194 | result.put(entry.getKey(), value); | |
| 195 | } | |
| 196 | } | |
| 197 | return result; | |
| 198 | } | |
| 199 | } | |
