Open
Conversation
18jeffreyma
commented
Feb 17, 2026
|
|
||
| Follow these steps to improve performance: | ||
| 1. As a first step, activate the testbed environment by running: | ||
| . /opt/miniconda3/etc/profile.d/conda.sh ; conda activate testbed |
Author
There was a problem hiding this comment.
curious on this one, maybe worth publicizing this detail to other benchmark mainttainers: initial runs on SWE-fficiency were spuriously failing since agents didn't have the conda environement already active
Author
|
@enyst would you mind taking a look when you have time? should be a straightforward port of: |
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
2 participants
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
(as title)
tested locally with
SKIP_BUILD=0 uv run swefficiency-infer /home/ubuntu/benchmarks/.llm_config/gemini3flash.json --dataset swefficiency/swefficiency --workspace docker --num-workers 4 --num-cpus-per-worker 4 --mem-limit 32g --n-limit 10