Created
October 14, 2021 15:14
-
-
Save msjgriffiths/f87d9b71462af75ff6a86ebca1114c08 to your computer and use it in GitHub Desktop.
Example sentence embedding
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| using Flux | |
| # Input data, of (features, examples, time_step) | |
| # We ignore masking | |
| x = randn(Float32, 32, 100, 12) | |
| hidden_states = Chain( | |
| # A 4-layer stacked LSTM | |
| LSTM(32, 64), | |
| LSTM(64, 64), | |
| LSTM(64, 64), | |
| LSTM(64, 32), | |
| ) | |
| attention = Chain( | |
| # We want to compute attention. See arxiv@1703.03130. | |
| x -> permutedims(x, (1, 3, 2)), | |
| Parallel( | |
| ⊠, # NNlib.batched_mul | |
| identity, | |
| # A = softmax(Wₛ₂tanh(Wₛ₁Hᵀ)); note we take care of transpose with permutedims | |
| Chain( | |
| softmax ∘ Dense(12, 1, false) ∘ Dense(32, 12, false, tanh), | |
| x -> permutedims(x, (2, 1, 3)) | |
| ) | |
| ), | |
| x -> permutedims(x, (3, 1, 2)), | |
| x -> reshape(x, (100, 32)) | |
| ) | |
| sentence_embedding = Chain(hidden_states, attention) | |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment