Fix:NP

Author: abilng

sample_config/MNIST/CNN/model_conf.json

@@ -1,6 +1,6 @@
 {
 	"nnetType" : "CNN",
-	"wdir" : "wdir",
+	"wdir" : "MNIST_CNN",
 	"data_spec" : "data_spec.json",
 	"nnet_spec" : "nnet_spec.json",
 	"output_file" : "conv_out.model",
@@ -16,7 +16,7 @@
 		"scale_by" : 0.5,
 		"min_derror_decay_start" : 0.05,
 		"min_derror_stop" : 0.0005,
-		"min_epoch_decay_start" : 15
+		"min_epoch_decay_start" : 5
 	},
 	"export_path":"data/cnn/",
 	"plot_path":"plot/",

sample_config/MNIST/CNN/nnet_spec.json

@@ -26,16 +26,12 @@
     "mlp" : {  
         "hidden_layers": [50],
         "adv_activation" : null,
-		"max_col_norm":null,
-		"l1_reg":null,
-		"l2_reg":null,
-		"do_dropout" : true,
-		"dropout_factor" : [0.2],
-		"activation" : "tanh"
-    },
-    "a" : {
-			"method":"maxout",
-			"pool_size":1
-		}
+	"max_col_norm":null,
+	"l1_reg":null,
+	"l2_reg":null,
+	"do_dropout" : true,
+	"dropout_factor" : [0.2],
+	"activation" : "tanh"
+    }
 
 }

sample_config/MNIST/DBN/model_conf.json

@@ -1,6 +1,6 @@
 {
     "nnetType" : "RBM",
-    "wdir" : "wdir",
+    "wdir" : "MNIST_DBN",
     "data_spec" : "data_spec.json",
     "nnet_spec" : "rbm_spec.json",
     "output_file" : "rbm_out.model",

sample_config/MNIST/DBN/rbm_spec.json

@@ -1,7 +1,7 @@
 
 {
-  "hidden_layers": [1000, 1000, 1000],
+  "hidden_layers": [500, 500],
   "activation" : "sigmoid",
-  "pretrained_layers" : 3,
+  "pretrained_layers" : 2,
   "first_layer_type" : "gb"
 }

sample_config/MNIST/DNN/dnn_spec.json

@@ -1,6 +1,6 @@
 {
 
-  "hidden_layers": [1000, 1000, 1000],
+  "hidden_layers": [500, 500, 500],
   "activation" : "sigmoid",
   "pretrained_layers" : 3,
   "max_col_norm":null,

sample_config/MNIST/SDA/model_conf.json

@@ -1,6 +1,6 @@
 {
     "nnetType" : "SDA",
-    "wdir" : "wdir",
+    "wdir" : "MNIST_SDA",
     "data_spec" : "data_spec.json",
     "nnet_spec" : "sda_spec.json",
     "output_file" : "sda_out.model",
@@ -16,7 +16,7 @@
     "finetune_params" : {
         "method":"C",
         "learning_rate" : 0.08,
-        "epoch_num" : 10,
+        "epoch_num" : 5,
         "start_rate" : 0.08,
         "scale_by" : 0.5,
         "min_derror_decay_start" : 0.05,

sample_config/MNIST/SDA/sda_spec.json

@@ -1,6 +1,6 @@
 {
 
-    "hidden_layers": [1000, 1000, 1000],
-    "corruption_levels":  [0.1, 0.2, 0.3],
+    "hidden_layers": [500, 500],
+    "corruption_levels":  [0.1, 0.2],
     "activation" : "tanh"
 }

src/models/cnn.py

@@ -141,7 +141,7 @@ def plot_layer_output(self,plot_spec,plot_path,max_images=10):
 			img_plot_remaining = max_images;
 			layer_out_fn = self.getLayerOutFunction(layer_idx);
 			logger.info('Plotting the layer %d'%layer_idx);
-			file_reader =read_dataset(plot_spec,pad_zeros=True)[0];
+			file_reader =read_dataset(plot_spec,pad_zeros=True);
 			while not file_reader.is_finish():
 				for batch_index in xrange(file_reader.cur_frame_num/batch_size):
 					s_idx = batch_index * batch_size; e_idx = s_idx + batch_size
@@ -277,7 +277,7 @@ def __init__(self, numpy_rng, theano_rng, batch_size, n_outs,conv_layer_configs,
 				dropout_conv_input = self.dropout_layers[-1].dropout_output;
 
 			config = conv_layer_configs[i]
-			activation = conv_activation
+			conv_activation= parse_activation(config['activation'])
 			dropout_conv_layer = DropoutConvLayer(numpy_rng=numpy_rng, input=dropout_conv_input,
 				input_shape=config['input_shape'],filter_shape=config['filter_shape'],poolsize=config['poolsize'],
 				activation = conv_activation, use_fast = use_fast,dropout_factor=conv_layer_configs[i]['dropout_factor'])

src/run/run_DBN.py

@@ -167,26 +167,17 @@ def runRBM(arg):
     ########################
     if model_config['processes']['testing']:
         testing(dbn,data_spec)
-
     ##########################
-    ##   Export Features    ##
+    #   Export Features	##
     ##########################
     if model_config['processes']['export_data']:
-        exportFeatures(dbn,model_config,data_spec)
-        export_path = model_config['export_path']+'.re'
-        data_spec_testing = data_spec['testing']
-
-        out_function = getFunction(dbn)
-        export_data(data_spec_testing,export_path,out_function,
-                    model_config['n_ins']);
+	exportFeatures(dbn,model_config,data_spec)
 
 
-    logger.info('Saving model to ' + str(model_config['output_file']) + ' ....')
-    dbn.save(filename=model_config['output_file'], withfinal=True);
+    logger.info('Saving model to ' + str(model_config['output_file']) + '....')
+    dbn.save(filename=model_config['output_file'])
     logger.info('Saved model to ' + str(model_config['output_file']))
 
-
-
 if __name__ == '__main__':
     import sys
     setLogger();