bug fix: preconditions

data/maker/__init__.py

@@ -248,7 +248,7 @@ class Learner(Process):
         _args = {"schema":self.get_schema(),"data":self._df,"columns":columns}
         if self._map :
             _args['map'] = self._map
-        self._encoder = prepare.Input(**_args)        
+        self._encoder = prepare.Input(**_args)  if self._df.shape[0] > 0 else None     
 class Trainer(Learner):
     """
     This will perform training using a GAN
@@ -263,6 +263,10 @@ class Trainer(Learner):
         self.candidates = int(_args['candidates']) if 'candidates' in _args else 1
     def run(self):
         self.initalize()
+        if self._encoder is None :
+            #
+            # @TODO Log that the dataset was empty or not statistically relevant
+            return 
         _space,_matrix = self._encoder.convert()
         
         _args   = self.network_args
@@ -311,9 +315,15 @@ class Generator (Learner):
         file.close()
     def run(self):
         self.initalize()
+        if self._encoder is None :
+            #
+            # @TODO Log that the dataset was empty or not statistically relevant
+            return 
+        
         #
         # The values will be returned because we have provided _map information from the constructor
         #
+
         values,_matrix = self._encoder.convert()
         _args = self.network_args
         _args['map'] = self._map