extract word vectors

answer_classifier_cached_features/extract_word_vecs.py

+from word2vec.word_vector_management import word_vector_manager
+import constants
+import ujson
+import numpy as np
+import os
+
+import tensorflow as tf
+
+model = '/home/tanmay/Code/GenVQA/Exp_Results/models_cvpr/' + \
+        'ans_through_obj_atr_rel_bin_feats/answer_classifiers/' + \
+        'model-68000'
+
+sess = tf.InteractiveSession()
+word_vec_mgr = word_vector_manager()
+model_restorer = tf.train.Saver()
+model_restorer.restore(sess, model)
+
+word2vec = word_vec_mgr.pretrained_word_vectors.eval()
+classifier_vecs = word_vec_mgr.word_vectors.eval()
+
+outdir = '/home/tanmay/Code/GenVQA/Exp_Results/models_cvpr/word_vectors'
+constants.mkdir_if_not_exists(outdir)
+
+# word2vec_file = os.path.join(outdir, 'word2vec.txt')
+# np.savetxt(
+#     word2vec_file,
+#     word2vec,
+#     delimiter=',')
+
+# classifier_vecs_file = os.path.join(outdir, 'classifier_vecs.txt')
+# np.savetxt(
+#     classifier_vecs_file,
+#     classifier_vecs,
+#     delimiter=',')
+    
+
+with open(constants.vocab_json) as file:
+    vocab = ujson.load(file)
+
+
+