TODO:
The project can be split into 3 parts:
1. encoder
    - embedding layer; Glove, etc.
    - FOR BSC: need to binarize the encodings into {-1, 1}. See equations (2.5-2.8) in text. Graidents can be passed through channel or leave them unchanged.
    - FOR AWGN: leave the output as is.
    - encodings will need to be variable length, see page 34
2. channel
    - AWGN (additive white gaussian noise); just add Gaussian noise with 0 mean and ∑ variance.
    - BSC (binary symmetric channel); use element-wise vector product between noise and codeword. The noise vector will have (modified) Bernoulli density at each index. So, for each index i, we have P(x=-1) = π and P(x = 1) = 1-π.
    - BEC (binary erasure channel); use a dropout layer, recieved codeword will have values {-1, 0, 1} where 0 is the erasure.
3. decoder
    - I would suggest using an auto-regressive output
    - output message doesn't need to be the same size as the input.