Add train dropout to normalizer
diff --git a/tf-ner-poc/src/main/python/normalizer/normalizer.py b/tf-ner-poc/src/main/python/normalizer/normalizer.py
index b4cc674..8286ce1 100644
--- a/tf-ner-poc/src/main/python/normalizer/normalizer.py
+++ b/tf-ner-poc/src/main/python/normalizer/normalizer.py
@@ -91,6 +91,9 @@
encoder_emb_inp = tf.nn.embedding_lookup(encoder_embedding_weights, encoder_char_ids_ph)
+ if "TRAIN" == mode:
+ encoder_emb_inp = tf.nn.dropout(encoder_emb_inp, 0.7)
+
encoder_emb_inp = tf.transpose(encoder_emb_inp, perm=[1, 0, 2])
encoder_cell = tf.nn.rnn_cell.BasicLSTMCell(num_units)
@@ -144,8 +147,6 @@
outputs, _, _ = tf.contrib.seq2seq.dynamic_decode(decoder, output_time_major=True, swap_memory=True )
- # TODO: Use attention to improve training performance ...
-
logits = outputs.rnn_output
train_prediction = outputs.sample_id
@@ -232,7 +233,7 @@
eval_sess = tf.Session(graph=eval_graph)
- for epoch in range(1):
+ for epoch in range(20):
print("Epoch " + str(epoch))
with train_graph.as_default():
