From 97d8c1eda0a57c4faaa21e20441611382f2daa68 Mon Sep 17 00:00:00 2001
From: tgupta6 <tgupta6@illinois.edu>
Date: Mon, 19 Sep 2016 15:53:23 -0500
Subject: [PATCH] wrap_elementwise_multiply
---
answer_classifier_cached_features/inference.py | 2 +-
constants_crunchy.py | 12 ++++++------
object_attribute_classifier_cached_features/eval.py | 3 ++-
visual_util/visualize_relevance.py | 2 +-
4 files changed, 10 insertions(+), 9 deletions(-)
diff --git a/answer_classifier_cached_features/inference.py b/answer_classifier_cached_features/inference.py
index 1011142..d599de1 100644
--- a/answer_classifier_cached_features/inference.py
+++ b/answer_classifier_cached_features/inference.py
@@ -38,7 +38,7 @@ class AnswerInference():
else:
reuse_vars = True
- num_regions = self.object_feat[j].get_shape()[0].value
+ num_regions = 100
q_feat = tf.reshape(
self.question_vert_concat[j],
diff --git a/constants_crunchy.py b/constants_crunchy.py
index 6ae0955..9ae185b 100644
--- a/constants_crunchy.py
+++ b/constants_crunchy.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_classifier_joint_pretrain_wordvec_xform' #'QA_joint_pretrain_genome_split'
+experiment_name = 'QA_classifier_joint_pretrain_wordvec_xform_large_obj_atr_wt' #'QA_joint_pretrain_genome_split'
# Global output directory (all subexperiments will be saved here)
global_output_dir = '/home/tanmay/Code/GenVQA/Exp_Results/VQA'
@@ -195,7 +195,7 @@ answer_obj_atr_loss_wt = 0.1
answer_regularization_coeff = 1e-5
answer_queue_size = 500
answer_embedding_dim = 600
-answer_lr = 1e-3
+answer_lr = 1.0*1e-3
answer_log_every_n_iter = 500
answer_output_dir = os.path.join(
global_experiment_dir,
@@ -215,12 +215,12 @@ answer_model = os.path.join(
num_regions_with_labels = 100
# Answer fine tune params
-answer_fine_tune_from_iter = 13000
+answer_fine_tune_from_iter = 29500
answer_fine_tune_from = answer_model + '-' + str(answer_fine_tune_from_iter)
# Answer eval params
answer_eval_on = 'val'
-answer_model_to_eval = answer_model + '-20000'
+answer_model_to_eval = answer_model + '-28000'
vqa_results_dir = os.path.join(
answer_output_dir,
@@ -238,8 +238,8 @@ answer_eval_results_json = os.path.join(
# Select best model
models_dir = answer_output_dir
-start_model = 40000
-step_size = 2000
+start_model = 20000
+step_size = 4000
model_accuracies_txt = os.path.join(
answer_output_dir,
'model_accuracies.txt')
diff --git a/object_attribute_classifier_cached_features/eval.py b/object_attribute_classifier_cached_features/eval.py
index a022e2a..17ccfe9 100644
--- a/object_attribute_classifier_cached_features/eval.py
+++ b/object_attribute_classifier_cached_features/eval.py
@@ -291,8 +291,9 @@ if __name__=='__main__':
initializer = create_initializer(
graph,
sess,
+ constants.pretrained_model)
#constants.answer_model_to_eval)
- constants.region_model_to_eval)
+ #constants.region_model_to_eval)
print 'Creating feed dict creator...'
feed_dict_creator = train.create_feed_dict_creator(graph.plh)
diff --git a/visual_util/visualize_relevance.py b/visual_util/visualize_relevance.py
index be332af..695b6d3 100644
--- a/visual_util/visualize_relevance.py
+++ b/visual_util/visualize_relevance.py
@@ -200,7 +200,7 @@ if __name__=='__main__':
'mscoco_val2014_annotations_with_parsed_questions.json')
exp_dir = '/home/tanmay/Code/GenVQA/Exp_Results/VQA/' + \
- 'QA_classifier_wordvec_xform/'
+ 'QA_classifier_joint_pretrain_wordvec_xform/'
eval_data_json = os.path.join(
exp_dir,
--
GitLab