public String toJson() { try { return NeuralNetConfiguration.mapper().writeValueAsString(this); } catch (JsonProcessingException e) { throw new RuntimeException(e); } }
public static MemoryReport fromJson(String json) { try { return NeuralNetConfiguration.mapper().readValue(json, MemoryReport.class); } catch (IOException e) { throw new RuntimeException(e); } }
public String toJson() { try { return NeuralNetConfiguration.mapper().writeValueAsString(this); } catch (JsonProcessingException e) { throw new RuntimeException(e); } }
public static FineTuneConfiguration fromJson(String json) { try { return NeuralNetConfiguration.mapper().readValue(json, FineTuneConfiguration.class); } catch (IOException e) { throw new RuntimeException(e); } }
/** * Return this configuration as json * * @return this configuration represented as json */ public String toJson() { ObjectMapper mapper = mapper(); try { String ret = mapper.writeValueAsString(this); return ret; } catch (org.nd4j.shade.jackson.core.JsonProcessingException e) { throw new RuntimeException(e); } }
/** * * @return JSON representation of NN configuration */ public String toJson() { ObjectMapper mapper = NeuralNetConfiguration.mapper(); synchronized (mapper) { //JSON mappers are supposed to be thread safe: however, in practice they seem to miss fields occasionally //when writeValueAsString is used by multiple threads. This results in invalid JSON. See issue #3243 try { return mapper.writeValueAsString(this); } catch (org.nd4j.shade.jackson.core.JsonProcessingException e) { throw new RuntimeException(e); } } }
/** * Create a neural net configuration from json * * @param json the neural net configuration from json * @return */ public static NeuralNetConfiguration fromJson(String json) { ObjectMapper mapper = mapper(); try { NeuralNetConfiguration ret = mapper.readValue(json, NeuralNetConfiguration.class); return ret; } catch (IOException e) { throw new RuntimeException(e); } }
/** * @return JSON representation of computation graph configuration */ public String toJson() { //As per MultiLayerConfiguration.toJson() ObjectMapper mapper = NeuralNetConfiguration.mapper(); synchronized (mapper) { //JSON mappers are supposed to be thread safe: however, in practice they seem to miss fields occasionally //when writeValueAsString is used by multiple threads. This results in invalid JSON. See issue #3243 try { return mapper.writeValueAsString(this); } catch (org.nd4j.shade.jackson.core.JsonProcessingException e) { throw new RuntimeException(e); } } }
/** * @return JSON representation of Component configuration */ @JsonIgnore public String getConf() { try { //NeuralNetConfiguration.mapper().setSerializationInclusion(JsonInclude.Include.NON_NULL); String json = NeuralNetConfiguration.mapper().writer().writeValueAsString(this); return json.replaceAll("\\s", ""); } catch (JsonProcessingException ex) { log.error("Could not serialize class to JSON: " + ex.toString()); 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; }
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; }
ObjectMapper mapper = NeuralNetConfiguration.mapper(); ComputationGraphConfiguration conf; try {
ObjectMapper mapper = NeuralNetConfiguration.mapper(); try { conf = mapper.readValue(json, MultiLayerConfiguration.class);