Alpha Relase

Author: abilng

run/run_CNN.py

@@ -23,7 +23,7 @@
 import theano.tensor as T
 from theano.tensor.shared_randomstreams import RandomStreams
 
-from utils.load_conf import load_model,load_conv_spec,load_mlp_spec,load_data_spec
+from utils.load_conf import load_model,load_conv_spec,load_data_spec
 from io_modules.file_reader import read_dataset
 from utils.learn_rates import LearningRate
 from utils.utils import parse_activation
@@ -43,8 +43,10 @@ def runCNN(arg):
 	else :
 		model_config = load_model(arg,'CNN')
 
-	conv_config,conv_layer_config,mlp_config = load_conv_spec(model_config['nnet_spec'],model_config['batch_size'],
-				model_config['input_shape'])
+	conv_config,conv_layer_config,mlp_config = load_conv_spec(
+			model_config['nnet_spec'],
+			model_config['batch_size'],
+			model_config['input_shape'])
 
 	data_spec =  load_data_spec(model_config['data_spec']);
 
@@ -59,6 +61,7 @@ def runCNN(arg):
 	createDir(model_config['wdir']);
 	#create working dir
 
+	batch_size = model_config['batch_size'];
 	cnn = CNN(numpy_rng,theano_rng,conv_layer_configs = conv_layer_config, batch_size = batch_size,
 			n_outs=model_config['n_outs'],hidden_layers_sizes=mlp_config['layers'], 
 			conv_activation = conv_activation,hidden_activation = hidden_activation,
@@ -68,7 +71,6 @@ def runCNN(arg):
 
 		#learning rate, batch-size and momentum
 		lrate = LearningRate.get_instance(model_config['l_rate_method'],model_config['l_rate']);
-		batch_size = model_config['batch_size'];
 		momentum = model_config['momentum']
 
 		train_sets, train_xy, train_x, train_y = read_dataset(data_spec['training'],model_config['batch_size'])

utils/load_conf.py

@@ -24,7 +24,15 @@ def load_model(input_file,nnetType=None):
 		logger.critical(" 'nnetType' is missing in model properties file..")
 		exit(1)
 
-	if checkConfig(data,nnetType):
+	requiredKeys = ['data_spec','wdir','processes','nnet_spec','output_file','n_outs']
+	if not isKeysPresents(data,requiredKeys):
+		logger.critical(" the mandatory arguments are missing in model properties file..")
+		exit(1)
+		
+	if data.has_key('n_ins') or data.has_key('input_shape'):
+		pass
+	else:
+		logger.error('Neither n_ins nor input_shape is present')
 		logger.critical(" the mandatory arguments are missing in model properties file..")
 		exit(1)
 
@@ -69,19 +77,6 @@ def correctPath(data,keys,basePath):
 			data[key] = makeAbsolute(data[key],basePath)
 	return data
 
-def checkConfig(data,nnetType):
-	requiredKeys = [
-		'data_spec','wdir','processes',
-		'nnet_spec','output_file','n_outs'
-		]
-	if isKeysPresents(data,requiredKeys):
-		return False
-	if data.has_key('n_ins') or data.has_key('input_shape'):
-		return True
-	else:
-		logger.error('Neither n_ins nor input_shape is present')
-		return False
-
 def isKeysPresents(data,requiredKeys):
 	for key in requiredKeys:
 		if not data.has_key(key):
@@ -114,11 +109,6 @@ def load_data_spec(input_file):
 	return data
 
 
-def load_mlp_spec(input_file):
-	logger.info("Loading mlp properties from %s ...",input_file)
-	return load_json(input_file);
-
-
 #############################################################################
 #CNN
 #############################################################################