Merge pull request #2 from PaddlePaddle/develop

merge from remote

fluid/faster_rcnn/models/model_builder.py

@@ -269,7 +269,7 @@ class FasterRCNN(object):
             x=rpn_cls_score_reshape, shape=(0, -1, 1))
         rpn_bbox_pred_reshape = fluid.layers.reshape(
             x=rpn_bbox_pred_reshape, shape=(0, -1, 4))
-        score_pred, loc_pred, score_tgt, loc_tgt = \
+        score_pred, loc_pred, score_tgt, loc_tgt, bbox_weight = \
             fluid.layers.rpn_target_assign(
                 bbox_pred=rpn_bbox_pred_reshape,
                 cls_logits=rpn_cls_score_reshape,
@@ -290,7 +290,12 @@ class FasterRCNN(object):
         rpn_cls_loss = fluid.layers.reduce_mean(
             rpn_cls_loss, name='loss_rpn_cls')
 
-        rpn_reg_loss = fluid.layers.smooth_l1(x=loc_pred, y=loc_tgt, sigma=3.0)
+        rpn_reg_loss = fluid.layers.smooth_l1(
+            x=loc_pred,
+            y=loc_tgt,
+            sigma=3.0,
+            inside_weight=bbox_weight,
+            outside_weight=bbox_weight)
         rpn_reg_loss = fluid.layers.reduce_sum(
             rpn_reg_loss, name='loss_rpn_bbox')
         score_shape = fluid.layers.shape(score_tgt)

fluid/faster_rcnn/train.py

@@ -61,7 +61,7 @@ def train():
 
     boundaries = cfg.lr_steps
     gamma = cfg.lr_gamma
-    step_num = len(lr_steps)
+    step_num = len(cfg.lr_steps)
     values = [learning_rate * (gamma**i) for i in range(step_num + 1)]
 
     optimizer = fluid.optimizer.Momentum(

fluid/recommendation/gru4rec/train.py

@@ -120,7 +120,7 @@ def train(train_reader,
     fetch_list = [avg_cost.name]
     for pass_idx in six.moves.xrange(pass_num):
         epoch_idx = pass_idx + 1
-        print "epoch_%d start" % epoch_idx
+        print("epoch_%d start" % epoch_idx)
 
         t0 = time.time()
         i = 0

fluid/text_matching_on_quora/train_and_evaluate.py

@@ -31,8 +31,8 @@ from pretrained_word2vec import Glove840B_300D
 
 parser = argparse.ArgumentParser(description=__doc__)
 
-parser.add_argument('--model_name',       type=str,   default='cdssm',                  help="Which model to train")
-parser.add_argument('--config',           type=str,   default='cdssm.cdssm_base',       help="The global config setting")
+parser.add_argument('--model_name',       type=str,   default='cdssmNet',                  help="Which model to train")
+parser.add_argument('--config',           type=str,   default='cdssm_base',       help="The global config setting")
 
 DATA_DIR = os.path.join(os.path.expanduser('~'), '.cache/paddle/dataset')
 

fluid/text_matching_on_quora/train_and_evaluate.sh

-source ~/mapingshuo/.bash_mapingshuo_fluid
-
-export CUDA_VISIBLE_DEVICES=1
-
-fluid train_and_evaluate.py  \
-    --model_name=cdssmNet  \
-    --config=cdssm_base
-
-#fluid train_and_evaluate.py \
-#    --model_name=DecAttNet  \
-#    --config=decatt_glove
-
-#fluid train_and_evaluate.py \
-#    --model_name=DecAttNet  \
-#    --config=decatt_word
-
-
-#fluid train_and_evaluate.py  \
-#    --model_name=ESIMNet  \
-#    --config=esim_seq