siemanko

"""Short and sweet LSTM implementation in Tensorflow.

Motivation:
When Tensorflow was released, adding RNNs was a bit of a hack - it required
building separate graphs for every number of timesteps and was a bit obscure
to use. Since then TF devs added things like `dynamic_rnn`, `scan` and `map_fn`.
Currently the APIs are decent, but all the tutorials that I am aware of are not
making the best use of the new APIs.

Advantages of this implementation:

inexorabletash

This demonstrates the implementation of full text search for documents in Indexed DB.

• Word-breaking and stemming is used to create a list of terms for each document.
• Document records are annotated with the list of terms when added to the database.
• A multi-entry index on the list of terms is populated.
• A query is similarly processed into a list of terms.
• A join over the terms is implemented using multiple cursors on the index.

The necessity of annotating records with the word list to populate the index is a limitation of the current Indexed DB API. A feature request to support custom