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completed_instances: 0 for ALL submissions — evaluation containers failing server-side (swe-bench_lite test) #27

Description

@suhail-akhtar

Bug: All submitted predictions return completed_instances: 0

Every submission we make to SWE-bench Lite (test) returns completed_instances: 0 and failed_instances: N — regardless of prediction quality, patch format, or run ID. This has been consistent across 4 separate submissions.

Evidence — All 4 Runs Return Identical Failure

Run ID Submitted Completed Failed Resolved
automotive-300-v1 299 0 299 0
automotive_v3 300 0 300 0
automotive_v3_final 300 0 300 0
automotive_v3_final2 300 0 300 0

Report Sample (automotive_v3_final2)

{
  "total_instances": 300,
  "submitted_instances": 300,
  "completed_instances": 0,
  "failed_instances": 300,
  "resolved_instances": 0,
  "schema_version": 2
}

Predictions Format — Verified Correct

  • Valid JSON array, 300 entries
  • Each entry has: instance_id, model_patch (standard unified diff diff --git format), model_name_or_path
  • LF line endings confirmed (no CRLF)
  • Only 1 empty patch out of 300

Local Harness Confirms Patches Are Valid

Running the same predictions.json through the local SWE-bench harness (swebench 4.1.0, WSL):

14/299 evaluated → ✓=14, ✖=0, error=0

14 out of 14 evaluated instances were resolved — confirming the patches are valid and apply correctly. The issue is server-side, not with our predictions.

What We Believe Is Happening

Based on reading the get_report.py source:

  • failed_instances = evaluation Docker containers that crashed/failed to start on the server
  • NOT test failures (those would appear as unresolved_instances)
  • completed_instances: 0 = the evaluation infrastructure couldn't run a single job for our account

The "Evaluating predictions... 100%" message in the sb-cli output completes in ~4 seconds for 300 instances — impossibly fast, suggesting the server moves jobs to a failed state immediately rather than running them.

Request

  1. Can you investigate why evaluation jobs fail immediately for run ID automotive_v3_final2?
  2. If the predictions are valid (which local harness confirms they are), can you re-trigger evaluation server-side for our existing submission?
  3. Is there a known issue with evaluation infrastructure for certain accounts?

Thank you!

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