We want to design a neural network that segments an English word into
prefixes, root, and suffixes using a BIO labelling scheme.
For example,
“unprepossessing”
Copyright By PowCoder代写 加微信 powcoder
has the labelling: (“u”, B-pre)
(“n”, I-pre), (“p”, B-pre), (“p”, I-pre), (“”, I-pre), (“p”, B-root), (“o”, I-
root), (“s”, I-root), (“s”,
I-root), (“e”, I-root), (“s”, I-root), (“s’, I-root)
(“”, B-suf), (“n”, I-suf), (“g”, I-suf). Note that due to the nature of the
application, O will not be used.
Fully specify a neural network to solve this problem. Describe:
• how the inputs and outputs are encoded
• the structure of the network
• the loss function used
Describe the network in enough detail that one could implement it using
PyTorch. You may describe it in terms of common abstractions (e.g.
standard LSTM cell of such-and-such size”) if that’s useful.
You do not need to define batch sizes, learning rates, and other optimization
parameters.
You may assume that the input contains only lowercase Latin letters.
程序代写 CS代考 加微信: powcoder QQ: 1823890830 Email: powcoder@163.com