Conversation
This patch improves the speed at which samples are drawn from gaussian distributions. The improvement is activate for matrices with more than 2500 components (roughly 32x32x3 and above). For large matrices (224x224x3 and above) the expected speedup is up to 3x.
This improves the performance of sampling using RNG.uniform(). The speedup is activated for matrices with 12500+ components and is around 2x for large images (224x224x3).
This removes a few ":func:" tags in docstrings for functions that pointed to numpy.
This file contains hidden or 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
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
This patch improves the speed at which samples are drawn from
gaussian distributions. The improvement is activate for matrices
with more than 2500 components (roughly 32x32x3 and above).
For large matrices (224x224x3 and above) the expected speedup is
up to 3x.
This patch also improves the performance of sampling using
RNG.uniform().
The speedup is activated for matrices with 12500+ components
and is around 2x for large images (224x224x3).