Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

Output
[Sentence: "The Hatter was the first to break the silence . ` What
day of the month is it ? ' he said , turning to Alice : he had taken
his watch out of his pocket , and was looking at it uneasily ,
shaking it every now and then , and holding it to his ear ." [
Tokens: 58],
Sentence: "Alice thought this a very curious thing , and she went
nearer to watch them , and just as she came up to them she heard one
of them say , ` Look out now , Five ! Do n't go splashing paint over
me like that !" [ Tokens: 48]]
Now, each document (a Sentence object) will have its own overall embedding:
documents[0].embedding
Output
tensor([-6.4245e-02, 3.5365e-01, -2.4962e-01, -5.3912e-01,
-1.9917e-01, -2.7712e-01, 1.6942e-01, 1.0867e-01,
...
7.4661e-02, -3.4777e-01, 1.5740e-01, 3.4407e-01,
-5.0272e-01, 1.7432e-01, 7.9398e-01, 7.3562e-01],
device='cuda:0',
grad_fn=<CatBackward>)
Notice that the individual tokens don’t get their own embeddings anymore:
documents[0].tokens[31].embedding
Output
tensor([], device='cuda:0')
960 | Chapter 11: Down the Yellow Brick Rabbit Hole