BENCH: Add a relatable 2D benchmark for block #12001
Closed
Conversation
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
eric-wieser
reviewed
Sep 21, 2018
| def setup(self, shape, dtype, n_chunks): | ||
|
|
||
| self.block_list = [ | ||
| [np.full(shape=[s//n_chunk for s, n_chunk in zip(shape, n_chunks)], |
There was a problem hiding this comment.
Why full and not just ones?
There was a problem hiding this comment.
Honestly, I think it is more obvious what we are trying to do with full since it implies array traversal in the name. ones, zeros and emtpy are ambiguous since they do different things.
2ccfc32 to
656b90c
Compare
|
@eric-wieser re That said, benchmarking isn't always obvious, so I think the note I added in the earlier PR will help with this. |
7be351c to
4742d3f
Compare
|
@eric-wieser ready to merge? |
4742d3f to
114bf43
Compare
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
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Outdated suggestions cannot be applied.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.
The existing benchmarks for block are not easy to understand in terms of what they might mean for common use cases in the case of 2D blocking.
These benchmarks make the performance of common use cases more clear in terms of final array size and dtype used
xref #11991
cc: @eric-wieser