{"push_id":1460295416,"size":1,"distinct_size":1,"ref":"refs/heads/dynamic","head":"fb991456ee224a7d6cd8df67d69ab8e95a99f1ba","before":"7740be27af8499ee913118acaeec37a3f5a5c4d7","commits":[{"sha":"fb991456ee224a7d6cd8df67d69ab8e95a99f1ba","author":{"name":"pltrdy","email":"361ed97bad8d831d44e3669a79faf883b54fb794@gmail.com"},"message":"Dynamic RNN using sentences instead of fixed length sequences\n\t- We now feed the RNN with sentences\n\n\t- We use the Datasets class built which give some\n\tabstraction over 'reader.py' to manipulate our data\n\tand process the batching.\n\n\t- Batches has variable length i.e. length of the\n\tlongest sentence in the batch.\n\n\t- We use 'dynamic_rnn' which accepts variable length\n\tsequence and is faster than regular 'rnn'.","distinct":true,"url":"https://api.github.com/repos/pltrdy/tf_rnnlm/commits/fb991456ee224a7d6cd8df67d69ab8e95a99f1ba"}]}
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