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License: MIT License
Reproducing the results of DCN+ paper submitted for ICLR 2018
License: MIT License
Use #3 to create Q
We need a dedicated preprocessing class to perform tokenization and apply embeddings.
Used in HMN framework
For outputting s_i and e_i
Create L for #6 Coattention Encoder
LSTM_enc
Used in HMN framework
max that creates output for HMN
Create a softmax function that inputs #7 L and outputs A^Q or A^D.
Uses D and #9 A^Q
from torch.nn.utils.rnn import
-->
from torch.nn.utils.rnn import *
Used in HMN framework
Use #3 LSTM_enc to create D
Testing Waffle
Create Bi-LSTM that outputs U
We need a dataset object that inherits from the Pytorch Dataset class in order to use the DataLoader generator during model training
not clear what target is.
target is used when initializing SquadDataset (class defined in src/dataset.py).
args documentation is outdated.
For HMN_start and HMN_end
Needs:
max over output,
r
m^1
m^2
Uses the output of the Coattention Encoder U, LSTM_dec, HMN_start, HMN_end
Uses [Q ; C^Q] A^D
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