Model_Config

Model Config

• nnetType : (Mandatory) Type of Network (CNN/RBM/SDA/DNN)

• train_data : (Mandatory) The working directory containing data configuration and output

• wdir : (Mandatory) Working Directory.

• data_spec : (Mandatory) The path of the data sepification relative to model_config.json

• nnet_spec : (Mandatory) The path of network configuration specification relative to model_config.json

• output_file : (Mandatory) The path of RBM network output file relative to wdir

• input_file : The path of PreTrained/FineTuned network input file relative to wdir.(Mandatory for DNN)

• logger_level : Level of Logger.Valid Values are "INFO","DEBUG" and "ERROR"

• batch_size : specify the mini batch size while training, default 128

• n_ins :Dimension of input (Mandatory for all except CNN)

• n_outs :(Mandatory) Dimension of output (No: of Classes)

• input_shape: The input shape of a given feature vector.(Mandatory For CNN).Should be an Array.

• finetune_method : Two methods are supported

1. C: Constant learning rate.
2. E: Exponential decay.

• finetune_rate : Configuration of learning method.Contains a json object with following params

param	description	default value	learning method
learning_rate		0.08	C
epoch_num		10	C
start_rate		0.08	E
scale_by		0.5	E
min_derror_decay_start		0.05	E
min_derror_stop		0.05	E
min_epoch_decay_start		15	E

• finetune_momentum : The momentum factor while finetuning
• export_path : path (realative to wdir) for writting (bottleneck) features.
• processes : Process should be run by program.Contains a json object with following params

• pretraining : whether Pre-Training is needed.(invalid for DNN and CNN).(Default value = false)
• finetuning : whether Fine Tuning is needed.(Default value = false)
• testing : whether Fine Tuning is needed.(Default value = false)
• export_data : whether extracted features should written to file.If true,export_path is required.(Default value = false).

######Specific to DBN(RBM)######

• gbrbm_learning_rate : Pretraining learning rate for gbrbm layer.(Default Value = 0.005)

• pretraining_learning_rate : Pretraining learning rate for all layers except gbrbm layer.(Default Value = 0.08)

• pretraining_epochs :No of Pretraining epochs(Default Value = 10)

• initial_pretrain_momentum :The initial momentum factor while pre-training (Default Value = 0.5)

• final_pretrain_momentum :The final momentum factor while pre-training (Default Value = 0.9)

• initial_pretrain_momentum_epoch : No: of epochs with the initial momentum factor before switching to final momentum factor.(Default Value = 5)

• keep_layer_num: From which layer Pre-Trainig Should Start.(Default Value = 0).If non-Zero layer is intilaized with weights from input_file

######Specific to SDA######

• pretrain_lr :learning rate to be used during pre-training (Default Value = 0.08).

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Also See:

• Example-CNN
• Example-RBM
• Example-SDA