RequestHunt is a community-driven platform that collects and curates feature requests from X (Twitter), Reddit, and GitHub. We help product teams discover what features real users are asking for, making it easier to validate product ideas and prioritize feature development based on actual user demand.

How does RequestHunt collect feature requests?

RequestHunt uses AI-powered extraction to automatically collect feature requests from social media platforms including X, Reddit, and GitHub. The platform monitors discussions, issues, and posts to identify genuine user feature requests, extracting key information like the requested feature, product mentioned, and user sentiment.

Who uses RequestHunt?

RequestHunt is used by product managers, founders, developers, and product teams who want to discover what features real users are requesting. It's particularly valuable for startups looking to validate ideas, established companies prioritizing their roadmap, and developers building products that solve real user problems.

Is RequestHunt free to use?

Yes, browsing and searching feature requests on RequestHunt is completely free. We also offer API access for developers who want to integrate feature request data into their own applications. Check our pricing page for API plan details.

How often is RequestHunt data updated?

RequestHunt continuously collects feature requests from Reddit, X (Twitter), and GitHub. You can also trigger on-demand scraping via the API or web interface to get the freshest data for any topic.

[NiftyNet] Implement Fully Connected Weight Tying

There is no clean way to tie weights of two Fully Connected layers. The request is to extend the Fully Connected layer to allow construction with a TensorFlow variable as its weight matrix, enabling weight tying.

Original Source

@@danieltudosiu | 0 pts | 4/17/2019

**This issue is to track progress on new features for the Fully Connected Weight Tying** At the moment there is no clean way of tying the weights of two Fully Connected layers. One must define them manually to be able to do so. The solution would be the ability to instantiate a Fully Connected layer given a Tensorflow variable for its weights. - [ ] Extend the Fully Connected layer to have the option of being constructed with a Variable as its weight matrix - [ ] Create a simple test where a pair of tied layers are being trained for a few batches and then their weights are being checked

Discussion

Loading comments...