add no pretraining qa training script

answer_classifier_cached_features/train.py

@@ -213,7 +213,6 @@ class graph_creator():
                         name = 'embedding_lookup_' + name)
                     noun_embed[name].append(embed)
 
-
             name = 'positive_adjectives'
             adjective_embed[name] = []
             for j in xrange(self.batch_size):
@@ -370,7 +369,7 @@ class graph_creator():
 
         self.regularization_loss = self.regularization()
 
-        self.total_loss = 0.1*(self.object_loss + 1000.0*self.attribute_loss) + \
+        self.total_loss = 0.0*(self.object_loss + 1000.0*self.attribute_loss) + \
                           self.regularization_loss + \
                           self.answer_loss
                           
@@ -755,7 +754,7 @@ if __name__=='__main__':
     print 'Starting a session...'
     config = tf.ConfigProto()
     config.gpu_options.allow_growth = True
-    config.gpu_options.per_process_gpu_memory_fraction = 0.8
+    config.gpu_options.per_process_gpu_memory_fraction = 0.5
     sess = tf.Session(config=config, graph=graph.tf_graph)
 
     print 'Creating initializer...'

constants_vision_gpu_2.py

@@ -160,7 +160,7 @@ answer_offset = 0
 answer_regularization_coeff = 1e-5
 answer_queue_size = 500
 answer_embedding_dim = 600
-answer_lr = 1e-4
+answer_lr = 1e-3
 answer_log_every_n_iter = 500
 answer_output_dir = os.path.join(
     global_experiment_dir,