feat: support loading stable memory from a file#76
Merged
Conversation
dsarlis
previously approved these changes
Dec 5, 2024
Contributor
|
I think this also suffers from the same issue as #65. Namely that some benchmark is giving different results on different platforms. |
Collaborator
Author
I addressed by making the test only ensure success. We don't actually need to assert on the exact instruction count, as that is quite brittle. |
|
|
dsarlis
approved these changes
Dec 6, 2024
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
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
Problem
Running benchmarks that require a particular stable memory is currently not possible with canbench. I ran into this problem quite often when wanting to benchmark AI models, and I'm sure there are other use-cases for it as well.
Solution
This PR introduces a way to specify a binary file in
canbench.ymlthat will be loaded as the canister's stable memory after initialization.Example: