We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
https://github.com/ZhixiuYe/MLMAN/blob/master/models/MLMAN.py#L63 input_mask = (input['mask'] != 0).float()
input_mask = (input['mask'] != 0).float()
这里只取了非零即文本长度的mask,且bool结果都为1,所以原先data_loader里的2,3值没有用上?
https://github.com/ZhixiuYe/MLMAN/blob/master/models/data_loader.py#L172 self.data_mask[i][j] = 2
self.data_mask[i][j] = 2
The text was updated successfully, but these errors were encountered:
是的,这里的self.data_mask[i][j] = 1,2,3只是为了标定每个词相对于两个entitiy的位置,如果做piece-wise pooling的话是需要用到这些mask的(之前一些方法是这么做的)。 我这里并不是用的这种方式,我只需要区别mask和非mask。
self.data_mask[i][j] = 1,2,3
piece-wise pooling
Sorry, something went wrong.
No branches or pull requests
https://github.com/ZhixiuYe/MLMAN/blob/master/models/MLMAN.py#L63
input_mask = (input['mask'] != 0).float()
这里只取了非零即文本长度的mask,且bool结果都为1,所以原先data_loader里的2,3值没有用上?
https://github.com/ZhixiuYe/MLMAN/blob/master/models/data_loader.py#L172
self.data_mask[i][j] = 2
The text was updated successfully, but these errors were encountered: