Automatic_Speech_Recognition
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Performance issues in /speechvalley (by P3)
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Hello! I've found a performance issue in your project:
tf.Sessionbeing defined repeatedly leads to incremental overhead.
You can make your program more efficient by fixing this bug. Here is the Stack Overflow post to support it.
Below is detailed description about tf.Session being defined repeatedly:
- utils/utils.py:
with tf.Session(graph=graph) as session(here) is defined in the functionget_edit_distance(here) which is repeatedly called in the loopfor batch, batchOrigI in enumerate(batchRandIxs)(here). - main/libri_train.py:
with tf.Session(graph=model.graph) as sess(here) is repeatedly called in the loopfor feature_dir, label_dir in zip(feature_dirs, label_dirs)(here). - main/madarian_train.py:
with tf.Session(graph=model.graph) as sess(here) is repeatedly called in the loopfor feature_dir, label_dir in zip(feature_dirs, label_dirs)(here).
tf.Session being defined repeatedly could lead to incremental overhead. If you define tf.Session out of the loop and pass tf.Session as a parameter to the loop, your program would be much more efficient.
Looking forward to your reply. Btw, I am very glad to create a PR to fix it if you are too busy.