Merge branch 'master' of gitlab-beta.engr.illinois.edu:Vision/GenVQA

constants_vision_gpu_2.py

@@ -5,7 +5,7 @@ def mkdir_if_not_exists(dir_name):
     if not os.path.exists(dir_name):
         os.mkdir(dir_name)
         
-experiment_name = 'QA_explicit_dot_pretrained'
+experiment_name = 'QA_explicit_dot_pretrained_same_lr'
 #experiment_name = 'object_attribute_classifier_large_images'
 # Global output directory (all subexperiments will be saved here)
 global_output_dir = '/home/nfs/tgupta6/projects/GenVQA/Exp_Results/VQA'
@@ -89,7 +89,7 @@ pretrained_vocab_word_vectors_npy = os.path.join(
 # Object Attribute Classifier Training Params
 region_batch_size = 200
 region_num_samples = num_train_regions
-region_num_epochs = 10
+region_num_epochs = 4
 region_offset = 0
 region_queue_size = 400
 region_regularization_coeff = 1e-4
@@ -160,10 +160,11 @@ num_test_questions = 0
 answer_batch_size = 50
 answer_num_epochs = 10
 answer_offset = 0
+answer_obj_atr_loss_wt = 0.0
 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,
@@ -198,4 +199,10 @@ answer_eval_results_json = os.path.join(
     answer_output_dir,
     'eval_' + answer_eval_on + '_results.json')
 
-
+# Select best model
+models_dir = answer_output_dir
+start_model = 1000
+step_size = 2000
+model_accuracies_txt = os.path.join(
+    answer_output_dir,
+    'model_accuracies.txt')