misc. update about docs

examples/FasterRCNN/eval.py

@@ -62,7 +62,7 @@ def nms_fastrcnn_results(boxes, probs):
             continue
         probs_k = probs[ids, klass].flatten()
         boxes_k = boxes[ids, :]
-        selected_ids = nms_func(boxes_k[:, [1, 0, 3, 2]], probs_k)
+        selected_ids = nms_func(boxes_k, probs_k)
         selected_boxes = boxes_k[selected_ids, :].copy()
         ret.append(DetectionResult(klass, selected_boxes, probs_k[selected_ids]))
 

examples/GAN/GAN.py

@@ -71,8 +71,9 @@ class GANTrainer(TowerTrainer):
         inputs_desc = model.get_inputs_desc()
         cbs = input.setup(inputs_desc)
 
-        tower_func = TowerFuncWrapper(
-            model.build_graph, inputs_desc)
+        # we need to set towerfunc because it's a TowerTrainer,
+        # and only TowerTrainer supports automatic graph creation for inference during training.
+        tower_func = TowerFuncWrapper(model.build_graph, inputs_desc)
         with TowerContext('', is_training=True):
             tower_func(*input.get_input_tensors())
         opt = model.get_optimizer()
@@ -138,6 +139,7 @@ class MultiGPUGANTrainer(TowerTrainer):
         input = StagingInput(input, list(range(nr_gpu)))
         cbs = input.setup(model.get_inputs_desc())
 
+        # build the graph
         def get_cost(*inputs):
             model.build_graph(inputs)
             return [model.d_loss, model.g_loss]