embedding

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>>> # an Embedding module containing 10 tensors of size 3
>>> embedding = nn.Embedding(10, 3)
>>> # a batch of 2 samples of 4 indices each
>>> input = Variable(torch.LongTensor([[1,2,4,5],[4,3,2,9]]))
>>> embedding(input)

Variable containing:
(0 ,.,.) =
 -1.0822  1.2522  0.2434
  0.8393 -0.6062 -0.3348
  0.6597  0.0350  0.0837
  0.5521  0.9447  0.0498

(1 ,.,.) =
  0.6597  0.0350  0.0837
 -0.1527  0.0877  0.4260
  0.8393 -0.6062 -0.3348
 -0.8738 -0.9054  0.4281
[torch.FloatTensor of size 2x4x3]

>>> # example with padding_idx
>>> embedding = nn.Embedding(10, 3, padding_idx=0)
>>> input = Variable(torch.LongTensor([[0,2,0,5]]))
>>> embedding(input)

Variable containing:
(0 ,.,.) =
  0.0000  0.0000  0.0000
  0.3452  0.4937 -0.9361
  0.0000  0.0000  0.0000
  0.0706 -2.1962 -0.6276
[torch.FloatTensor of size 1x4x3]