Embedding
A simple lookup table that looks up embeddings in a fixed dictionary and size.
nnf_embedding( input, weight, padding_idx = NULL, max_norm = NULL, norm_type = 2, scale_grad_by_freq = FALSE, sparse = FALSE )
input |
(LongTensor) Tensor containing indices into the embedding matrix |
weight |
(Tensor) The embedding matrix with number of rows equal to the maximum possible index + 1, and number of columns equal to the embedding size |
padding_idx |
(int, optional) If given, pads the output with the embedding
vector at |
max_norm |
(float, optional) If given, each embedding vector with norm larger
than |
norm_type |
(float, optional) The p of the p-norm to compute for the |
scale_grad_by_freq |
(boolean, optional) If given, this will scale gradients
by the inverse of frequency of the words in the mini-batch. Default |
sparse |
(bool, optional) If |
This module is often used to retrieve word embeddings using indices. The input to the module is a list of indices, and the embedding matrix, and the output is the corresponding word embeddings.
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