Print something for #218

examples/ResNet/imagenet-resnet.py

@@ -87,12 +87,13 @@ def get_config(fake=False, data_format='NCHW'):
     nr_tower = max(get_nr_gpu(), 1)
     global BATCH_SIZE
     BATCH_SIZE = TOTAL_BATCH_SIZE // nr_tower
-    logger.info("Running on {} towers. Batch size per tower: {}".format(nr_tower, BATCH_SIZE))
 
     if fake:
+        logger.info("For benchmark, batch size is fixed to 64 per tower.")
         dataset_train = dataset_val = FakeData(
             [[64, 224, 224, 3], [64]], 1000, random=False, dtype='uint8')
     else:
+        logger.info("Running on {} towers. Batch size per tower: {}".format(nr_tower, BATCH_SIZE))
         dataset_train = get_data('train')
         dataset_val = get_data('val')
 

tensorpack/callbacks/saver.py

@@ -45,6 +45,7 @@ class ModelSaver(Callback):
         self.var_collections = var_collections
         if checkpoint_dir is None:
             checkpoint_dir = logger.LOG_DIR
+        assert checkpoint_dir is not None
         assert tf.gfile.IsDirectory(checkpoint_dir), checkpoint_dir
         self.checkpoint_dir = checkpoint_dir
 
@@ -150,7 +151,6 @@ class MinSaver(Callback):
         files_to_copy = glob.glob(path + '*')
         for file_to_copy in files_to_copy:
             shutil.copy(file_to_copy, file_to_copy.replace(path, newname))
-        #shutil.copy(path, newname)
         logger.info("Model with {} '{}' saved.".format(
             'maximum' if self.reverse else 'minimum', self.monitor_stat))