This repository has been archived by the owner on Nov 22, 2022. It is now read-only.
implemented cnn pooling for doc classification #872
Closed
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
facebook-github-bot
added
the
CLA Signed
shreydesai
force-pushed
the
export-D16631634
branch
from
5af731b
to
03ee542
Compare
shreydesai
added a commit
to shreydesai/pytext
that referenced
this pull request
Aug 3, 2019
Summary: Pull Request resolved: facebookresearch#872 Implements max and average pooling for DeepCNNRepresentation -- this allows it to be used in tasks where each word in a sequence doesn't necessarily need to have its own representation. Attention is commonly used in NLP to attend to important parts of the sequence, but max and average pooling are simpler (but strong) baselines that can compress sequential representations. The resulting representation can be used in tasks such as document classification, which we perform experiments with. Differential Revision: D16631634 fbshipit-source-id: 7f071fa4aff97ad121ac90c2256f744030a86e80
Summary: Pull Request resolved: facebookresearch#872 Implements max and average pooling for DeepCNNRepresentation -- this allows it to be used in tasks where each word in a sequence doesn't necessarily need to have its own representation. Attention is commonly used in NLP to attend to important parts of the sequence, but max and average pooling are simpler (but strong) baselines that can compress sequential representations. The resulting representation can be used in tasks such as document classification, which we perform experiments with. Differential Revision: D16631634 fbshipit-source-id: 93a1a3e7d9e7cf54ceebf41523134d9e2c3ba6b7
shreydesai
force-pushed
the
export-D16631634
branch
from
03ee542
to
cd660b1
Compare
|
This pull request has been merged in 8bc826d. |
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Summary: Implements max and average pooling for DeepCNNRepresentation -- this allows it to be used in tasks where each word in a sequence doesn't necessarily need to have its own representation. Attention is commonly used in NLP to attend to important parts of the sequence, but max and average pooling are simpler (but strong) baselines that can compress sequential representations. The resulting representation can be used in tasks such as document classification, which we perform experiments with.
Differential Revision: D16631634