I am going through the docs:
https://pytorch.org/docs/stable/nn.html#torch.nn.LSTM
but am a little confused:
Is seq_len the number of time units or number of words in a sentence
and input_size the embedding size or features?
I am going through the docs:
https://pytorch.org/docs/stable/nn.html#torch.nn.LSTM
but am a little confused:
Is seq_len the number of time units or number of words in a sentence
and input_size the embedding size or features?
Yes, in case of sentences, input_size
derives from the size of your word or character embeddings. For example, if you use Word2Vec or GloVe embeddings of size 300 (i.e., each word is represented as a vector with 300 dimensions), the input_size
of your LSTM needs to be 300.