I am working with tensor flow fold tree LSTM code. Before applying tree LSTM I'm doing some preprocessing on the sentence in tensorflow. To be concrete through preprocessing I'm getting a matrix (say R) of size NxMxD where N is the batch size, M is the max sentence length, D the representation dimension.
Now I want to apply TREE LSTM on this matrix R s.t. R_TL = TreeLSTM(R).
While using the sentiment.py code I'm facing problem while writing the word2vec code as now my vec representation are dynamic ( represented through R). For any word, it's vector representation would be R(batch_idx, word_inx, : ).
If batch consists of 2 setences : 0: It is a good day 1: He is a very good player.
Then for the word good I will need R(0,3,:) one time and R(1, 4, :) other time.
I can give word_idx info with parse tree but how do I get the batch_idx info ?
Any other approach to this problem is also acceptable (My problem being how to take vec rep from a dynamic matrix)
Hi,
I am working with tensor flow fold tree LSTM code. Before applying tree LSTM I'm doing some preprocessing on the sentence in tensorflow. To be concrete through preprocessing I'm getting a matrix (say R) of size NxMxD where N is the batch size, M is the max sentence length, D the representation dimension.
Now I want to apply TREE LSTM on this matrix R s.t. R_TL = TreeLSTM(R).
While using the sentiment.py code I'm facing problem while writing the word2vec code as now my vec representation are dynamic ( represented through R). For any word, it's vector representation would be R(batch_idx, word_inx, : ).
If batch consists of 2 setences : 0: It is a good day 1: He is a very good player. Then for the word good I will need R(0,3,:) one time and R(1, 4, :) other time.
I can give word_idx info with parse tree but how do I get the batch_idx info ?
Any other approach to this problem is also acceptable (My problem being how to take vec rep from a dynamic matrix)
Thanks