{"abstract":"Sparse gradient coordinates are combined by list position.","category":"Distributed training aggregation","checks":6,"contract":"Rows [worker, [(coordinate,value),...]]; sum values by coordinate and return sorted pairs; empty coordinates omitted.","contract_signature":"rows","evaluation_group":"w3-dta-gradient-coordinate-align","failed_approach":"Replacing positional IDs with explicit IDs but overwriting duplicate coordinates discards another worker’s contribution.","family":"w3-distributed-training-aggregation-gradient-coordinate-align","id":"FA-99291","implementations":{"attempt":{"sha256":"933b123046997c2ca34a77ace0d03b6f06d72bb4c893f57340464bd66769749f","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(rows):\n    d={}\n    for w,vals in rows:\n        for j,v in vals: d[j]=v\n    return [[j,d[j]] for j in sorted(d)]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('sparse order differs',solve([['a',[[2,N],[0,1]]],['b',[[0,3],[2,4]]]]),[[0,4],[2,N+4]])\ncheck('empty workers',solve([]),[])\ncheck('empty coordinate rows',solve([['a',[]]]),[])\ncheck('one coordinate',solve([['a',[[N,N]]]]),[[N,N]])\ncheck('negative coordinate values',solve([['a',[[-1,N]]],['b',[[-1,-N]]]]),[[-1,0]])\ncheck('missing coordinate treated zero',solve([['a',[[1,2]]],['b',[[3,4]]]]),[[1,2],[3,4]])\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"44809c03c23b597ec94ca7daa9ab85d5f7d5bc97fca360277b234bcf64574ba3","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(rows):\n    return [[j,sum(vals[j][1] for w,vals in rows if j<len(vals))] for j in range(max((len(vals) for w,vals in rows),default=0))]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncheck('sparse order differs',solve([['a',[[2,N],[0,1]]],['b',[[0,3],[2,4]]]]),[[0,4],[2,N+4]])\ncheck('empty workers',solve([]),[])\ncheck('empty coordinate rows',solve([['a',[]]]),[])\ncheck('one coordinate',solve([['a',[[N,N]]]]),[[N,N]])\ncheck('negative coordinate values',solve([['a',[[-1,N]]],['b',[[-1,-N]]]]),[[-1,0]])\ncheck('missing coordinate treated zero',solve([['a',[[1,2]]],['b',[[3,4]]]]),[[1,2],[3,4]])\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"Inputs are already materialized Python values from a fixed toy collective; no transport, failure recovery, optimizer state, or real model behavior is represented. This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"w3-distributed-training-aggregation-gradient-coordinate-align","generated_at":"2026-09-30T16:48:22.633383+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"A toy distributed-training contract makes replica and shard contribution rules explicit without claiming framework compatibility or performance.","root_cause":"Workers may emit sparse coordinates in different orders, but the reducer uses each pair’s position as its parameter ID.","sha256":"2ecf2459731ad253493f23733ec9a70dfe0121d921d9f943c5f288da93ddcb4f","title":"Sparse gradient coordinates are combined by list position · case 01","variant":1,"variant_policy":"The fixture code references N, supplied as 1 through 5. Fixed boundary checks may repeat. These records share one mechanism and must remain together in evaluation splits.","verified":true,"visibility":"public","verification":{"attempt":{"elapsed_ms":27.525,"exit_code":1,"observations":[{"actual":[[0,3],[2,4]],"check":"sparse order differs","expected":[[0,4],[2,5]],"passed":false},{"actual":[],"check":"empty workers","expected":[],"passed":true},{"actual":[],"check":"empty coordinate rows","expected":[],"passed":true},{"actual":[[1,1]],"check":"one coordinate","expected":[[1,1]],"passed":true},{"actual":[[-1,-1]],"check":"negative coordinate values","expected":[[-1,0]],"passed":false},{"actual":[[1,2],[3,4]],"check":"missing coordinate treated zero","expected":[[1,2],[3,4]],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"sparse order differs\", \"actual\": [[0, 3], [2, 4]], \"expected\": [[0, 4], [2, 5]], \"passed\": false}, {\"check\": \"empty workers\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"empty coordinate rows\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"one coordinate\", \"actual\": [[1, 1]], \"expected\": [[1, 1]], \"passed\": true}, {\"check\": \"negative coordinate values\", \"actual\": [[-1, -1]], \"expected\": [[-1, 0]], \"passed\": false}, {\"check\": \"missing coordinate treated zero\", \"actual\": [[1, 2], [3, 4]], \"expected\": [[1, 2], [3, 4]], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":29.353,"exit_code":1,"observations":[{"actual":[[0,4],[1,5]],"check":"sparse order differs","expected":[[0,4],[2,5]],"passed":false},{"actual":[],"check":"empty workers","expected":[],"passed":true},{"actual":[],"check":"empty coordinate rows","expected":[],"passed":true},{"actual":[[0,1]],"check":"one coordinate","expected":[[1,1]],"passed":false},{"actual":[[0,0]],"check":"negative coordinate values","expected":[[-1,0]],"passed":false},{"actual":[[0,6]],"check":"missing coordinate treated zero","expected":[[1,2],[3,4]],"passed":false}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"sparse order differs\", \"actual\": [[0, 4], [1, 5]], \"expected\": [[0, 4], [2, 5]], \"passed\": false}, {\"check\": \"empty workers\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"empty coordinate rows\", \"actual\": [], \"expected\": [], \"passed\": true}, {\"check\": \"one coordinate\", \"actual\": [[0, 1]], \"expected\": [[1, 1]], \"passed\": false}, {\"check\": \"negative coordinate values\", \"actual\": [[0, 0]], \"expected\": [[-1, 0]], \"passed\": false}, {\"check\": \"missing coordinate treated zero\", \"actual\": [[0, 6]], \"expected\": [[1, 2], [3, 4]], \"passed\": false}], \"passed\": false}\n"}},"member_only":{"stages":["fixed"],"fields":["implementations.fixed","verification.fixed","harness","repair"],"note":"The verified repair, its recorded checks, the repair description, and the scoring harness are available to members."}}