Merge pull request #24 from ragavvenkatesan/dev

PR for the fix with mat2yann
ragavvenkatesan · Feb 23, 2017 · cb8f868 · cb8f868
2 parents 8bc44a2 + a998fd3
commit cb8f868
Show file tree

Hide file tree

Showing 3 changed files with 12 additions and 15 deletions.
diff --git a/pantry/tutorials/mat2yann.py b/pantry/tutorials/mat2yann.py
@@ -55,7 +55,7 @@ def cook_svhn_normalized( location, verbose = 1, **kwargs):
     dataset = setup_dataset(dataset_init_args = data_params,
                             save_directory = save_directory,
                             preprocess_init_args = preprocess_params,
-                            verbose = 3)
+                            verbose = verbose)
     return dataset
 
 if __name__ == '__main__':
@@ -64,4 +64,4 @@ def cook_svhn_normalized( location, verbose = 1, **kwargs):
         raise Exception("Provide Dataset Location")
     else:
         location = sys.argv[1]
-    cook_svhn_normalized(location)
+    cook_svhn_normalized(location, verbose = 3)
diff --git a/yann/network.py b/yann/network.py
@@ -2166,22 +2166,16 @@ def print_status (self, epoch , verbose = 2):
         if self.cooked_datastream is None:
             raise Exception(" Cook first then run this.")
 
-        if verbose >=2 :
-            if len(self.cost) < self.batches2train * self.mini_batches_per_batch[0]:
-                print(".. Cost                : " + str(self.cost[-1]))
-            else:
-                print(".. Cost                : " + str(numpy.mean(self.cost[-1 *
-                                    self.batches2train * self.mini_batches_per_batch[0]:])))
-
-        if verbose >= 3:
-            print("... Learning Rate       : " + str(self.learning_rate.get_value(borrow=\
-                                                                                 self.borrow)))
-            print("... Momentum            : " + str(self.current_momentum(epoch)))
+        if len(self.cost) < self.batches2train * self.mini_batches_per_batch[0]:
+            cost = self.cost[-1]
+        else:
+            cost = numpy.mean(self.cost[-1 *
+                                self.batches2train * self.mini_batches_per_batch[0]:])
 
         lr = self.learning_rate.get_value(borrow =  self.borrow)
         mom = self.current_momentum(epoch)
 
-        self.cooked_resultor.process_results(cost = self.cost,
+        self.cooked_resultor.process_results(cost = cost,
                                            lr = lr,
                                            mom = mom,
                                            verbose = verbose)

diff --git a/yann/utils/dataset.py b/yann/utils/dataset.py
@@ -838,10 +838,11 @@ def __init__(self,
             print(". Setting up dataset ")
 
         self.source              = dataset_init_args [ "source" ]
+
         if self.source == 'skdata':
             self.name = dataset_init_args ["name"]
 
-        elif self.source == 'mat':
+        elif self.source == 'matlab':
             self.location        = dataset_init_args [ "location" ]
 
         if "height" in dataset_init_args.keys():
@@ -959,6 +960,8 @@ def _mat2yann (self, verbose = 2):
                                         self.channels,
                                         self.preprocessor )
 
+                if verbose >=3: 
+                    print ("... Dumping batch " + str(batch))
                 # compute number of minibatches for training, validation and testing
                 f = open(self.root + "/" + type + "/" + 'batch_' + str(batch) + '.pkl', 'wb')
                 obj = (data_x, data_y )