Deep Learning
Deep learning.
dl4j csv_train_and_save_model <json_config>
Description
To Train and save a model from a CSV file.
Parameters
json_config: The JSON configuration - string - required
admin
#------------------------------------------;
# START GLOBAL PARAMETERS ;
#------------------------------------------;
json load "dl4j_config" "{}";
json iobject "dl4j_config" / "dataTrainFile" "demo/dl4j_iris.csv" STR; #The CSV source file;
json iobject "dl4j_config" / "batchSizeTraining" "150" STR; #The number of line to train;
json iobject "dl4j_config" / "csvTest" "demo/dl4j_iris_test.csv" STR; #The CSV source file;
json iobject "dl4j_config" / "testBatchSize" "9" STR; #The number of line to test;
json iobject "dl4j_config" / "pathToSaveModel" "demo/dl4j_iris.model" STR; #Save the model;
json iobject "dl4j_config" / "pathToSaveNormalizer" "demo/dl4j_iris.normz" STR; #Save the normalizer;
json iobject "dl4j_config" / "numClasses" "3" STR; #The number of classes;
json iobject "dl4j_config" / "labelIndex" "4" STR; #Where is the position of the label index (starts with 0);
json iobject "dl4j_config" / "iterations" "3000" STR; #The number of iterations;
json iobject "dl4j_config" / "epochs" "1" STR; #The number of fit;
json iobject "dl4j_config" / "seed" "123" STR; #Random number;
json iobject "dl4j_config" / "learningRate" 0.01 STR;
json iobject "dl4j_config" / "l2" 1e-4 STR;
json iobject "dl4j_config" / "regularization" true STR;
json iobject "dl4j_config" / "activation" "TANH" STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
json iobject "dl4j_config" / "weightInit" "XAVIER" STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#------------------------------------------;
# ADDITIONAL GLOBAL PARAMETERS ;
#------------------------------------------;
#json iobject "dl4j_config" / "optimizationAlgo" null STR; #STOCHASTIC_GRADIENT_DESCENT|LINE_GRADIENT_DESCENT|LBFGS|HESSIAN_FREE|CONJUGATE_GRADIENT;
#json iobject "dl4j_config" / "biasInit" null STR;
#json iobject "dl4j_config" / "biasLearningRate" null STR;
#json iobject "dl4j_config" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_config" / "lrPolicyDecayRate" null STR;
#json iobject "dl4j_config" / "lrPolicyPower" null STR;
#json iobject "dl4j_config" / "lrPolicySteps" null STR;
#json iobject "dl4j_config" / "l1" null STR;
#json iobject "dl4j_config" / "l1Bias" null STR;
#json iobject "dl4j_config" / "l2Bias" null STR;
#json iobject "dl4j_config" / "maxNumLineSearchIterations" null STR;
#json iobject "dl4j_config" / "miniBatch" null STR;
#json iobject "dl4j_config" / "minimize" null STR;
#json iobject "dl4j_config" / "useDropConnect" null STR;
#json iobject "dl4j_config" / "dropOut" null STR;
#json iobject "dl4j_config" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_config" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iobject "dl4j_config" / "cacheMode" null STR; #NONE|HOST|DEVICE;
#json iobject "dl4j_config" / "convolutionMode" null STR; #Truncate|Strict|Same;
#json iobject "dl4j_config" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_config" / "gradientNormalizationThreshold" null STR;
#------------------------------------------;
# BUILD LAYERS ;
#------------------------------------------;
json iobject "dl4j_config" / "layers" "[]" ARRAY;
#------------------------------------------;
json load "dl4j_hidden_layer01" "{}";
json iobject "dl4j_hidden_layer01" / "type" "DenseLayer" STR;
json iobject "dl4j_hidden_layer01" / "nIn" "4" STR;
json iobject "dl4j_hidden_layer01" / "nOut" "3" STR;
json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer01") OBJ;
#------------------------------------------;
json load "dl4j_hidden_layer02" "{}";
json iobject "dl4j_hidden_layer02" / "type" "DenseLayer" STR;
json iobject "dl4j_hidden_layer02" / "nIn" "3" STR;
json iobject "dl4j_hidden_layer02" / "nOut" "3" STR;
json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer02") OBJ;
#------------------------------------------;
json load "dl4j_hidden_layer03" "{}";
json iobject "dl4j_hidden_layer03" / "type" "OutputLayer" STR;
json iobject "dl4j_hidden_layer03" / "nIn" "3" STR;
json iobject "dl4j_hidden_layer03" / "nOut" "3" STR;
json iobject "dl4j_hidden_layer03" / "activation" "SOFTMAX" STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
json iobject "dl4j_hidden_layer03" / "lossFunction" "NEGATIVELOGLIKELIHOOD" STR; #XENT|SQUARED_LOSS|SQUARED_HINGE|RMSE_XENT|RECONSTRUCTION_CROSSENTROPY|POISSON|NEGATIVELOGLIKELIHOOD|MSE|MEAN_SQUARED_LOGARITHMIC_ERROR|MEAN_ABSOLUTE_PERCENTAGE_ERROR|MEAN_ABSOLUTE_ERROR|MCXENT|L2|L1|KL_DIVERGENCE|HINGE|CUSTOM|EXPLL|COSINE_PROXIMITY;
json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer03") OBJ;
#------------------------------------------;
# EXAMPLE LAYERS ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "SubsamplingLayer" STR;
#json iobject "dl4j_hidden_layer00" / "kernelSize" "5:5" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "stride" "5:5" STR;
#json iobject "dl4j_hidden_layer00" / "padding" "5:5" STR;
#json iobject "dl4j_hidden_layer00" / "convolutionMode" null STR; #Truncate|Strict|Same;
#json iobject "dl4j_hidden_layer00" / "eps" null STR;
#json iobject "dl4j_hidden_layer00" / "pnorm" null STR;
#json iobject "dl4j_hidden_layer00" / "poolingType" null STR; #SUM|PNORM|NONE|MAX|AVG;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "RBM" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iobject "dl4j_hidden_layer00" / "hiddenUnit" null STR; #SOFTMAX|RECTIFIED|IDENTITY|GAUSSIAN|BINARY;
#json iobject "dl4j_hidden_layer00" / "k" null STR;
#json iobject "dl4j_hidden_layer00" / "lossFunction" null STR; #XENT|SQUARED_LOSS|SQUARED_HINGE|RMSE_XENT|RECONSTRUCTION_CROSSENTROPY|POISSON|NEGATIVELOGLIKELIHOOD|MSE|MEAN_SQUARED_LOGARITHMIC_ERROR|MEAN_ABSOLUTE_PERCENTAGE_ERROR|MEAN_ABSOLUTE_ERROR|MCXENT|L2|L1|KL_DIVERGENCE|HINGE|CUSTOM|EXPLL|COSINE_PROXIMITY;
#json iobject "dl4j_hidden_layer00" / "preTrainIterations" null STR;
#json iobject "dl4j_hidden_layer00" / "sparsity" null STR;
#json iobject "dl4j_hidden_layer00" / "visibleBiasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "visibleUnit" null STR; #SOFTMAX|LINEAR|IDENTITY|GAUSSIAN|BINARY;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "LSTM" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iobject "dl4j_hidden_layer00" / "forgetGateBiasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "gateActivationFunction" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "LocalResponseNormalization" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "alpha" null STR;
#json iobject "dl4j_hidden_layer00" / "beta" null STR;
#json iobject "dl4j_hidden_layer00" / "k" null STR;
#json iobject "dl4j_hidden_layer00" / "n" null STR;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "GravesLSTM" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iobject "dl4j_hidden_layer00" / "forgetGateBiasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "gateActivationFunction" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "GravesBidirectionalLSTM" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "forgetGateBiasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "gateActivationFunction" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "AutoEncoder" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iobject "dl4j_hidden_layer00" / "corruptionLevel" null STR;
#json iobject "dl4j_hidden_layer00" / "preTrainIterations" null STR;
#json iobject "dl4j_hidden_layer00" / "sparsity" null STR;
#json iobject "dl4j_hidden_layer00" / "visibleBiasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "lossFunction" null STR; #XENT|SQUARED_LOSS|SQUARED_HINGE|RMSE_XENT|RECONSTRUCTION_CROSSENTROPY|POISSON|NEGATIVELOGLIKELIHOOD|MSE|MEAN_SQUARED_LOGARITHMIC_ERROR|MEAN_ABSOLUTE_PERCENTAGE_ERROR|MEAN_ABSOLUTE_ERROR|MCXENT|L2|L1|KL_DIVERGENCE|HINGE|CUSTOM|EXPLL|COSINE_PROXIMITY;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "BatchNormalization" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iobject "dl4j_hidden_layer00" / "eps" null STR;
#json iobject "dl4j_hidden_layer00" / "beta" null STR;
#json iobject "dl4j_hidden_layer00" / "decay" null STR;
#json iobject "dl4j_hidden_layer00" / "gamma" null STR;
#json iobject "dl4j_hidden_layer00" / "lockGammaBeta" null STR; #Boolean;
#json iobject "dl4j_hidden_layer00" / "minibatch" null STR; #Boolean;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "GlobalPoolingLayer" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "poolingType" null STR; #SUM|PNORM|NONE|MAX|AVG;
#json iobject "dl4j_hidden_layer00" / "pnorm" null STR;
#json iobject "dl4j_hidden_layer00" / "collapseDimensions" null STR; #Boolean;
#json iobject "dl4j_hidden_layer00" / "poolingDimensions" null STR; #3:3;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "EmbeddingLayer" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "DropoutLayer" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "ActivationLayer" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "DenseLayer" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "ConvolutionLayer" STR;
#json iobject "dl4j_hidden_layer00" / "kernelSize" "5:5" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "stride" "5:5" STR;
#json iobject "dl4j_hidden_layer00" / "padding" "5:5" STR;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "epsilon" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "momentum" null STR;
#json iobject "dl4j_hidden_layer00" / "rho" null STR;
#json iobject "dl4j_hidden_layer00" / "rmsDecay" null STR;
#json iobject "dl4j_hidden_layer00" / "convolutionMode" null STR; #Truncate|Strict|Same;
#json iobject "dl4j_hidden_layer00" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iobject "dl4j_hidden_layer00" / "adamMeanDecay" null STR;
#json iobject "dl4j_hidden_layer00" / "adamVarDecay" null STR;
#json iobject "dl4j_hidden_layer00" / "cudnnAlgoMode" null STR; #USER_SPECIFIED|PREFER_FASTEST|NO_WORKSPACE;
#json iobject "dl4j_hidden_layer00" / "cudnnBwdDataMode" null STR; #WINOGRAD_NONFUSED|WINOGRAD|FFT_TILING|FFT|COUNT|ALGO_1|ALGO_0;
#json iobject "dl4j_hidden_layer00" / "cudnnBwdFilterMode" null STR; #WINOGRAD_NONFUSED|WINOGRAD|FFT_TILING|FFT|COUNT|ALGO_3|ALGO_1|ALGO_0;
#json iobject "dl4j_hidden_layer00" / "cudnnFwdMode" null STR; #WINOGRAD_NONFUSED|WINOGRAD|IMPLICIT_PRECOMP_GEMM|IMPLICIT_GEMM|GEMM|FFT_TILING|FFT|DIRECT|COUNT;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "OutputLayer" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iobject "dl4j_hidden_layer00" / "lossFunction" null STR; #XENT|SQUARED_LOSS|SQUARED_HINGE|RMSE_XENT|RECONSTRUCTION_CROSSENTROPY|POISSON|NEGATIVELOGLIKELIHOOD|MSE|MEAN_SQUARED_LOGARITHMIC_ERROR|MEAN_ABSOLUTE_PERCENTAGE_ERROR|MEAN_ABSOLUTE_ERROR|MCXENT|L2|L1|KL_DIVERGENCE|HINGE|CUSTOM|EXPLL|COSINE_PROXIMITY;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "CenterLossOutputLayer" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "alpha" null STR;
#json iobject "dl4j_hidden_layer00" / "lambda" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientCheck" null STR; #Boolean;
#json iobject "dl4j_hidden_layer00" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iobject "dl4j_hidden_layer00" / "lossFunction" null STR; #XENT|SQUARED_LOSS|SQUARED_HINGE|RMSE_XENT|RECONSTRUCTION_CROSSENTROPY|POISSON|NEGATIVELOGLIKELIHOOD|MSE|MEAN_SQUARED_LOGARITHMIC_ERROR|MEAN_ABSOLUTE_PERCENTAGE_ERROR|MEAN_ABSOLUTE_ERROR|MCXENT|L2|L1|KL_DIVERGENCE|HINGE|CUSTOM|EXPLL|COSINE_PROXIMITY;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
#json load "dl4j_hidden_layer00" "{}";
#json iobject "dl4j_hidden_layer00" / "type" "RnnOutputLayer" STR;
#json iobject "dl4j_hidden_layer00" / "nIn" "3" STR;
#json iobject "dl4j_hidden_layer00" / "nOut" "3" STR;
#json iobject "dl4j_hidden_layer00" / "dropOut" "0.25" STR;
#json iobject "dl4j_hidden_layer00" / "activation" null STR; #TANH|SOFTSIGN|SOFTPLUS|SOFTMAX|SIGMOID|SELU|RRELU|RELU|RECTIFIEDTANH|RATIONALTANH|LEAKYRELU|IDENTITY|HARDTANH|HARDSIGMOID|ELU|CUBE;
#json iobject "dl4j_hidden_layer00" / "weightInit" null STR; #ZERO|XAVIER_UNIFORM|XAVIER_LEGACY|XAVIER_FAN_IN|XAVIER|UNIFORM|SIGMOID_UNIFORM|RELU_UNIFORM|RELU|DISTRIBUTION;
#json iobject "dl4j_hidden_layer00" / "dist" null STR; #BinomialDistribution:0:1|NormalDistribution:0:1|UniformDistribution:0:1;
#json iobject "dl4j_hidden_layer00" / "biasInit" null STR;
#json iobject "dl4j_hidden_layer00" / "biasLearningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "l1" null STR;
#json iobject "dl4j_hidden_layer00" / "l1Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "l2" null STR;
#json iobject "dl4j_hidden_layer00" / "l2Bias" null STR;
#json iobject "dl4j_hidden_layer00" / "gradientNormalization" null STR; #RenormalizeL2PerParamType|RenormalizeL2PerLayer|None|ClipL2PerParamType|ClipL2PerLayer|ClipElementWiseAbsoluteValue;
#json iobject "dl4j_hidden_layer00" / "gradientNormalizationThreshold" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRate" null STR;
#json iobject "dl4j_hidden_layer00" / "learningRateDecayPolicy" null STR; #TorchStep|Step|Sigmoid|Score|Schedule|Poly|None|Inverse|Exponential;
#json iobject "dl4j_hidden_layer00" / "updater" null STR; #SGD|RMSPROP|NONE|NESTEROVS|NADAM|ADAMAX|ADAM|ADAGRAD|ADADELTA;
#json iobject "dl4j_hidden_layer00" / "lossFunction" null STR; #XENT|SQUARED_LOSS|SQUARED_HINGE|RMSE_XENT|RECONSTRUCTION_CROSSENTROPY|POISSON|NEGATIVELOGLIKELIHOOD|MSE|MEAN_SQUARED_LOGARITHMIC_ERROR|MEAN_ABSOLUTE_PERCENTAGE_ERROR|MEAN_ABSOLUTE_ERROR|MCXENT|L2|L1|KL_DIVERGENCE|HINGE|CUSTOM|EXPLL|COSINE_PROXIMITY;
#json iarray "dl4j_config" /layers (json doc "dl4j_hidden_layer00") OBJ;
#------------------------------------------;
# END GLOBAL PARAMETERS ;
#------------------------------------------;
json iobject "dl4j_config" / "backprop" true STR;
json iobject "dl4j_config" / "pretrain" false STR;
#------------------------------------------;
# Train and save the model/serializer ;
#------------------------------------------;
dl4j csv_train_and_save_model (json doc "dl4j_config");
mentdb
1
dl4j csv_load_model <dl4jId> <json_config>
Description
Load a DL4J model and normalizer into the memory
Parameters
dl4jId: The memory key to get the DL4J model - string - required
json_config: The JSON configuration - string - required
admin
#------------------------------------------;
# Load the model and the normalizer ;
#------------------------------------------;
dl4j csv_load_model "dl4jId1" (json doc "dl4j_config");
mentdb
1
dl4j csv_predict <dl4jId> <json_config> <csv_file> <nb_line_to_predict>
Description
Make a prediction from a DL4J model
Parameters
dl4jId: The memory key to get the DL4J model - string - required
json_config: The JSON configuration - string - required
csv_file: The CSV file to predict - string - required
nb_line_to_predict: The number of line to predict - number - required
admin
#------------------------------------------;
# Make predictions ;
#------------------------------------------;
dl4j csv_predict "dl4jId1" (json doc "dl4j_config") "demo/dl4j_iris_test.csv" 3;
mentdb
[
{
"probs": [
0.97952205,
0.01892847,
0.0015495354
],
"prob_class": "class1",
"prob_index": 0
},
{
"probs": [
0.9793347,
0.01910426,
0.0015610401
],
"prob_class": "class1",
"prob_index": 0
},
{
"probs": [
0.97940457,
0.019038359,
0.0015570737
],
"prob_class": "class1",
"prob_index": 0
}
]
dl4j show
Description
To show all DL4J networks.
dl4j exist <dl4jId>
Description
To check if a DL4J network was already loaded.
Parameters
dl4jId: The dl4j id - string - required
admin
dl4j exist "dl4jId1";
mentdb
1
dl4j delete <dl4jId>
Description
To delete a DL4J network from the memory.
Parameters
dl4jId: The dl4j id - string - required
admin
dl4j delete "dl4jId1";
mentdb
1
dl n_bayesian create_train_file
Description
To get a train file.
admin
file create "demo/train.txt" "transfer VIR RECU 854526,VIR RECU 8545269324 DE: OCTO TECHNOLOGY MOTIF: VIREMENT SALAIRES JUIN 11
withdrawal CARTE X2052 RETRAI,CARTE X2052 RETRAIT DAB 22/06 21H37 CIC PARIS SAINT ROCH 10859A00
payment CARTE X2052 21/06 ,CARTE X2052 21/06 PHIE LA BOETIE
fees OPTION TRANQUILLIT,OPTION TRANQUILLITE
fees COTISATION JAZZ,COTISATION JAZZ
atmfees FRAIS PAIEMENT HOR,FRAIS PAIEMENT HORS ZONE EURO 1 PAIEMENT A 1.00 EUR NT 38.06 EUR A 2.70
atmfees FRAIS PAIEMENT HOR,FRAIS PAIEMENT HORS ZONE EURO 1 PAIEMENT A 1.00 EUR NT 3.33 EUR A";
mentdb
dl n_bayesian show
Description
To show all Naive Bayesian networks.
admin
dl n_bayesian show
mentdb
[]
dl n_bayesian exist <key>
Description
To check if a Naive Bayesian network already exist.
Parameters
key: The network key - string - required
admin
dl n_bayesian exist "bayesian1";
mentdb
1
dl n_bayesian create_model <lang> <train_file_path> <iterations_param> <model_file_path_to_save>
Description
To create a new Naive Bayesian network model.
Parameters
lang: The language - string - required
train_file_path: The train file path - string - required
iterations_param: The iterations param - number (ex: 10) - required
model_file_path_to_save: The model file path to save - string - required
admin
dl n_bayesian create_model "en" "demo/train.txt" 10 "demo/model.bin";
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1
dl n_bayesian load <key> <model_file_path>
Description
To load a Naive Bayesian network model.
Parameters
key: The network key - string - required
model_file_path: The model file path - string - required
admin
dl n_bayesian load "bayesian1" "demo/model.bin";
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1
dl n_bayesian predict <key> <sentence>
Description
To predict a sentence.
Parameters
key: The network key - string - required
sentence: The sentence - string - required
admin
dl n_bayesian predict "bayesian1" "21/06 PHIE LA BOETIE";
mentdb
{
"input": "I\u0027m happy",
"prediction": "positif",
"best_percent": "66,666667 %",
"best_index": 0,
"probabilities": [
{
"prob_double": 0.6666666666666666,
"index": 0,
"prob_percent": "66,666667 %",
"key": "positif"
},
{
"prob_double": 0.3333333333333333,
"index": 1,
"prob_percent": "33,333333 %",
"key": "negatif"
}
],
"best_double": 0.6666666666666666
}
dl n_bayesian delete <key>
Description
To delete a Naive Bayesian network.
Parameters
key: The network key - string - required
admin
dl n_bayesian delete "bayesian1";
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1
dl bayesian show
Description
To show all Bayesian networks.
admin
dl bayesian show
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[]
dl bayesian exist <key>
Description
To check if a Bayesian network already exist.
Parameters
key: The network key - string - required
admin
dl bayesian exist "bayesian1";
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1
dl bayesian create <key> <cats>
Description
To create a new Bayesian network.
Parameters
key: The network key - string - required
cats: The categories (JSON array) - string - required
admin
dl bayesian create "bayesian1" "[\"positif\", \"negatif\"]";
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1
dl bayesian add_sentence <key> <cat> <sentence>
Description
To create a new Bayesian network.
Parameters
key: The network key - string - required
cat: The category key - string - required
sentence: The sentence - string - required
admin
dl bayesian add_sentence "bayesian1" "positif" "I'm happy";
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1
dl bayesian init <key> <laplace_int>
Description
To init a Bayesian network.
Parameters
key: The network key - string - required
laplace_int: The Laplace int - number - required
admin
dl bayesian init "bayesian1" 1;
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1
dl bayesian predict <key> <sentence>
Description
To predict a sentence.
Parameters
key: The network key - string - required
sentence: The sentence - string - required
admin
dl bayesian predict "bayesian1" "I'm happy";
mentdb
{
"input": "I\u0027m happy",
"prediction": "positif",
"best_percent": "66,666667 %",
"best_index": 0,
"probabilities": [
{
"prob_double": 0.6666666666666666,
"index": 0,
"prob_percent": "66,666667 %",
"key": "positif"
},
{
"prob_double": 0.3333333333333333,
"index": 1,
"prob_percent": "33,333333 %",
"key": "negatif"
}
],
"best_double": 0.6666666666666666
}
dl bayesian delete <key>
Description
To delete a Bayesian network.
Parameters
key: The network key - string - required
admin
dl bayesian delete "bayesian1";
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1
dl csv execute_config <jsonConfig>
Description
Train a CSV file.
Parameters
jsonConfig: The train JSON configuration - string - required
admin
json load "csv_config" "{}";
json iobject "csv_config" / "filePath" "demo/iris.data.txt" STR;
json iobject "csv_config" / "modelPath" "demo/iris.md" STR;
json iobject "csv_config" / "helperPath" "demo/iris.hl" STR;
json iobject "csv_config" / "nbLoop" "6" STR;
json iobject "csv_config" / "validationPercent" "0.3" STR;
json iobject "csv_config" / "shuffle" "true" STR;
json iobject "csv_config" / "seed" "1001" STR;
json iobject "csv_config" / "cols" "[]" ARRAY;
json load "col" "{}";
json iobject "col" / "index" "0" STR;
json iobject "col" / "title" "sepal-length" STR;
json iobject "col" / "type" "in" STR;
json iarray "csv_config" "/cols" (json doc "col") OBJ;
json load "col" "{}";
json iobject "col" / "index" "1" STR;
json iobject "col" / "title" "sepal-width" STR;
json iobject "col" / "type" "in" STR;
json iarray "csv_config" "/cols" (json doc "col") OBJ;
json load "col" "{}";
json iobject "col" / "index" "2" STR;
json iobject "col" / "title" "petal-length" STR;
json iobject "col" / "type" "in" STR;
json iarray "csv_config" "/cols" (json doc "col") OBJ;
json load "col" "{}";
json iobject "col" / "index" "3" STR;
json iobject "col" / "title" "petal-width" STR;
json iobject "col" / "type" "in" STR;
json iarray "csv_config" "/cols" (json doc "col") OBJ;
json load "col" "{}";
json iobject "col" / "index" "4" STR;
json iobject "col" / "title" "species" STR;
json iobject "col" / "type" "out" STR;
json iarray "csv_config" "/cols" (json doc "col") OBJ;
dl csv execute_config (json doc "csv_config");
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1
dl csv load_network <modelFilePath> <helperFilePath>
Description
Load the model and the helper into the memory.
Parameters
modelFilePath: The model file path - string - required
helperFilePath: The helper file path - string - required
admin
dl csv load_network "demo/iris.md" "demo/iris.hl";
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1
dl csv predict <jsonArrayInput>
Description
Predict from the model.
Parameters
jsonArrayInput: The JSON array that contains input values - string - required
admin
json load "input" "[5.9, 3.0, 5.1, 1.8]";
dl csv predict (json doc "input");
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Iris-virginica
admin
json load "input" "[5.6, 2.9, 3.6, 1.3]";
dl csv predict (json doc "input");
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Iris-versicolor
dl img step1 create_training <writerId> <width> <height> <isRGB>
Description
Create a training file.
Parameters
writerId: The writer id - string - required
width: The image width - number - required
height: The image height - number - required
isRGB: Is RGB ? (true, false) - bool - required
admin
#Create the training file;
file writer_open "w1" "demo/animals/imgTrainConfig.txt" true TEXT "utf-8";
dl img step1 create_training "w1" 100 100 true;
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1
dl img step2 add_image <writerId> <imgPath> <identity>
Description
Add image into the training file.
Parameters
writerId: The writer id - string - required
imgPath: The image path - string - required
identity: The image tag - string - required
admin
#Load input images;
-> "[dir]" "demo/animals/english_springer";
-> "[id]" "english_springer";
json load "files" (file dir_list [dir]);
-> "[nbFiles]" (json count "files" /);
-> "[iFiles]" 0;
for (-> "[i]" 0) (< [i] [nbFiles]) (++ "[i]") {
-> "[cur_file]" (json select "files" (concat "/[" [i] "]"));
if (string ends_with [cur_file] ".jpg") {
dl img step2 add_image "w1" (concat [dir] "/" [cur_file]) [id];
++ "[iFiles]";
};
};
file writer_flush "w1";
concat [iFiles] " files added."
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1
dl img step3 create_hidden_layer <writerId> <nbNeuron>
Description
Create a hidden layer.
Parameters
writerId: The writer id - string - required
nbNeuron: The number of neuron in the hidden layers - number - required
admin
dl img step3 create_hidden_layer "w1" "100"
file writer_flush "w1";
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1
dl img step4 create_or_load_network <writerId> <activation> <saveNetworkPath>
Description
Create or load a network.
Parameters
writerId: The writer id - string - required
activation: The activation function (ex: BiPolar|BipolarSteepenedSigmoid|ClippedLinear|Competitive|Elliott|ElliottSymmetric|Gaussian|Linear|LOG|Ramp|ReLU|Sigmoid|SIN|SoftMax|SteepenedSigmoid|Step|TANH) - string - required
saveNetworkPath: The path to save the network - string - required
admin
dl img step4 create_or_load_network "w1" "tanh" "demo/animals/network.eg";
file writer_flush "w1";
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dl img step5 train_network <writerId> <mode> <minutes> <strategyError> <strategyCycles> <saveNetworkPath>
Description
Train a network.
Parameters
writerId: The writer id - string - required
mode: The mode (console|gui) - string - required
minutes: The number of minutes - number - required
strategyError: The strategy error (ex: 0.25) - number - required
strategyCycles: The strategy cycles (ex: 50) - number - required
saveNetworkPath: The path to save the network - string - required
admin
dl img step5 train_network "w1" "console" 1 0.25 50 "demo/animals/network.eg";
file writer_flush "w1";
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1
dl img step6 predict <writerId> <imgPath> <identity>
Description
Predict an image from a neural network.
Parameters
writerId: The writer id - string - required
imgPath: The image path - string - required
identity: The image tag - string - required
admin
#Load input images;
-> "[dir]" "demo/animals/english_springer_predict";
-> "[id]" "english_springer";
json load "files" (file dir_list [dir]);
-> "[nbFiles]" (json count "files" /);
-> "[iFiles]" 0;
for (-> "[i]" 0) (< [i] [nbFiles]) (++ "[i]") {
-> "[cur_file]" (json select "files" (concat "/[" [i] "]"));
if (string ends_with [cur_file] ".jpg") {
dl img step6 predict "w1" (concat [dir] "/" [cur_file]) [id];
++ "[iFiles]";
};
};
file writer_flush "w1";
concat [iFiles] " files added.";
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1
dl img step7 close_file <writerId>
Description
Close the config file.
Parameters
writerId: The writer id - string - required
admin
#Close the config file;
file writer_close "w1";
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1
dl img execute_config <trainConfigFilePath>
Description
Execute a config training file
Parameters
trainConfigFilePath: The train config file path - string - required
admin
in editor {
dl img execute_config "demo/animals/imgTrainConfig.txt"
};
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1
dl img load_network <networkPath>
Description
Load a network into the memory
Parameters
networkPath: The network path - string - required
admin
dl img load_network "demo/animals/network.eg";
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1
dl img predict <imagePath> <isRGB> <width> <height> <jsonIdentity>
Description
Predict an image from the network
Parameters
imagePath: The image path - string - required
isRGB: Is RGB ? (true|false) - string - required
width: The image width - string - required
height: The image height - string - required
jsonIdentity: The json identity - string - required
admin
dl img predict "dir/image.jpg" true 100 100 "{
\"0\": \"english_springer\"
}";
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1
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