Resolve merge

README.md

@@ -11,6 +11,8 @@ To train the model using the code, the following data of the VQA dataset are nee
 - The pre-processed data of text is at http://visualqa.csail.mit.edu/data_vqa_txt.zip
 - The googlenet feature of all the COCO images is at http://visualqa.csail.mit.edu/data_vqa_feat.zip
 
+The pre-trained model used in the paper is at http://visualqa.csail.mit.edu/coco_qadevi_BOWIMG_bestepoch93_final.t7model. It has 55.89 on the Open-Ended and 61.69 on Multiple-Choice for the test-standard of COCO VQA dataset.
+
 Contact Bolei Zhou (zhoubolei@gmail.com) if you have any questions.
 
 Please cite our arXiv note if you use our code:

opensource_base.lua

@@ -1,4 +1,4 @@
-local debugger = require 'fb.debugger'
+--local debugger = require 'fb.debugger'
 local stringx = require 'pl.stringx'
 local file = require 'pl.file'
 

opensource_baseline.lua

@@ -35,7 +35,6 @@ function runTrainVal()
         local params_current, gparams_current = model:parameters()
 
         local config_layers, grad_last = config_layer_params(opt, params_current, gparams_current, 1)
-
     -- Save variables into context so that train_epoch could use.
         local context = {
             model = model,
@@ -87,7 +86,7 @@ function runTrainVal()
         local params_current, gparams_current = model:parameters()
 
         local config_layers, grad_last = config_layer_params(opt, params_current, gparams_current, 1)
-
+        
         local context = {
             model = model,
             criterion = criterion,