...

pipeline.py

@@ -78,6 +78,7 @@ class Components :
 			df = np.array_split(df[columns].values,PART_SIZE)
 			qwriter = factory.instance(type='queue.QueueWriter',args={'queue':'aou.io'})
 			part_index  = 0	
+			
 			#
 			# let's start n processes to listen & train this mother ...
 			# 		
@@ -145,7 +146,7 @@ class Components :
 		_args['max_epochs'] = 150 if 'max_epochs' not in args else int(args['max_epochs'])
 		# _args['num_gpu'] = int(args['num_gpu']) if 'num_gpu' in args else 1 
 		
-		if args['num_gpu'] > 1 :
+		if int(args['num_gpu']) > 1 :
 			_args['gpu'] = int(args['gpu']) if int(args['gpu']) < 8 else np.random.choice(np.arange(8)).astype(int)[0]
 		else:
 			_args['gpu']  = 0
@@ -295,10 +296,17 @@ if __name__ == '__main__' :
 			del args['reader']
 			columns = DATA.columns.tolist()
 			DATA  = np.array_split(DATA[args['columns']],len(content))
+
 			for id in ''.join(content) :
+				if 'focus' in args and int(args['focus']) != int(id) :
+					#
+					# This handles failures/recoveries for whatever reason
+					# If we are only interested in generating data for a given partition 
+					continue
+
 				args['partition'] = id
 				args['data'] = pd.DataFrame(DATA[(int(id))],columns=args['columns'])
-				if args['num_gpu'] > 1 :
+				if int(args['num_gpu']) > 1 :
 					args['gpu'] = id
 				else:
 					args['gpu']=0