public void setGraphConfiguration(JsonNode conf) { if(conf != null) { String json = conf.toString(); if(json != null && !json.equals("null")) { net = new ComputationGraph(ComputationGraphConfiguration.fromJson(json)); net.init(); } } }
ComputationGraphConfiguration confFromJson = ComputationGraphConfiguration.fromJson(json); ComputationGraph cg = new ComputationGraph(confFromJson); cg.init(params, false);
log.warn("Tried keras sequence config", e); try { return ComputationGraphConfiguration.fromJson(input); } catch (Exception e3) { log.warn("Tried computation graph from json");
private Triple<MultiLayerConfiguration, ComputationGraphConfiguration, NeuralNetConfiguration> getConfig() { boolean noData = currentSessionID == null; StatsStorage ss = (noData ? null : knownSessionIDs.get(currentSessionID)); List<Persistable> allStatic = (noData ? Collections.EMPTY_LIST : ss.getAllStaticInfos(currentSessionID, StatsListener.TYPE_ID)); if (allStatic.size() == 0) return null; StatsInitializationReport p = (StatsInitializationReport) allStatic.get(0); String modelClass = p.getModelClassName(); String config = p.getModelConfigJson(); if (modelClass.endsWith("MultiLayerNetwork")) { MultiLayerConfiguration conf = MultiLayerConfiguration.fromJson(config); return new Triple<>(conf, null, null); } else if (modelClass.endsWith("ComputationGraph")) { ComputationGraphConfiguration conf = ComputationGraphConfiguration.fromJson(config); return new Triple<>(null, conf, null); } else { try { NeuralNetConfiguration layer = NeuralNetConfiguration.mapper().readValue(config, NeuralNetConfiguration.class); return new Triple<>(null, null, layer); } catch (Exception e) { e.printStackTrace(); } } return null; }
private Triple<MultiLayerConfiguration, ComputationGraphConfiguration, NeuralNetConfiguration> getConfig() { boolean noData = currentSessionID == null; StatsStorage ss = (noData ? null : knownSessionIDs.get(currentSessionID)); List<Persistable> allStatic = (noData ? Collections.EMPTY_LIST : ss.getAllStaticInfos(currentSessionID, StatsListener.TYPE_ID)); if (allStatic.size() == 0) return null; StatsInitializationReport p = (StatsInitializationReport) allStatic.get(0); String modelClass = p.getModelClassName(); String config = p.getModelConfigJson(); if (modelClass.endsWith("MultiLayerNetwork")) { MultiLayerConfiguration conf = MultiLayerConfiguration.fromJson(config); return new Triple<>(conf, null, null); } else if (modelClass.endsWith("ComputationGraph")) { ComputationGraphConfiguration conf = ComputationGraphConfiguration.fromJson(config); return new Triple<>(null, conf, null); } else { try { NeuralNetConfiguration layer = NeuralNetConfiguration.mapper().readValue(config, NeuralNetConfiguration.class); return new Triple<>(null, null, layer); } catch (Exception e) { e.printStackTrace(); } } return null; }
private Triple<MultiLayerConfiguration, ComputationGraphConfiguration, NeuralNetConfiguration> getConfig() { boolean noData = currentSessionID == null; StatsStorage ss = (noData ? null : knownSessionIDs.get(currentSessionID)); List<Persistable> allStatic = (noData ? Collections.EMPTY_LIST : ss.getAllStaticInfos(currentSessionID, StatsListener.TYPE_ID)); if (allStatic.size() == 0) return null; StatsInitializationReport p = (StatsInitializationReport) allStatic.get(0); String modelClass = p.getModelClassName(); String config = p.getModelConfigJson(); if (modelClass.endsWith("MultiLayerNetwork")) { MultiLayerConfiguration conf = MultiLayerConfiguration.fromJson(config); return new Triple<>(conf, null, null); } else if (modelClass.endsWith("ComputationGraph")) { ComputationGraphConfiguration conf = ComputationGraphConfiguration.fromJson(config); return new Triple<>(null, conf, null); } else { try { NeuralNetConfiguration layer = NeuralNetConfiguration.mapper().readValue(config, NeuralNetConfiguration.class); return new Triple<>(null, null, layer); } catch (Exception e) { e.printStackTrace(); } } return null; }
ComputationGraphConfiguration conf = ComputationGraphConfiguration.fromJson(configJson);
ComputationGraphConfiguration conf = ComputationGraphConfiguration.fromJson(configJson);
ComputationGraphConfiguration conf = ComputationGraphConfiguration.fromJson(configJson);
if (!rootDevice) { this.replicatedModel = new ComputationGraph(ComputationGraphConfiguration .fromJson(((ComputationGraph) protoModel).getConfiguration().toJson())); this.replicatedModel.init();
if (!rootDevice) { this.replicatedModel = new ComputationGraph(ComputationGraphConfiguration .fromJson(((ComputationGraph) protoModel).getConfiguration().toJson())); this.replicatedModel.init();
if (!onRootModel) { ComputationGraphConfiguration conf = ComputationGraphConfiguration .fromJson(((ComputationGraph) originalModel).getConfiguration().toJson()); conf.setTrainingWorkspaceMode(workspaceMode);
if (!onRootModel) { ComputationGraphConfiguration conf = ComputationGraphConfiguration .fromJson(((ComputationGraph) originalModel).getConfiguration().toJson()); conf.setTrainingWorkspaceMode(workspaceMode);