Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
digest: string
kind: string
path: string
payload_sha3: string
prev: string
seq: int64
ts: timestamp[s]
passed: int64
source: struct<git: struct<url: string, head: string, sha_verified_from: string, previous_substitute: string (... 2 chars omitted)
child 0, git: struct<url: string, head: string, sha_verified_from: string, previous_substitute: string>
child 0, url: string
child 1, head: string
child 2, sha_verified_from: string
child 3, previous_substitute: string
platform: string
total: int64
method: struct<aggregate_rule: string, excluded: string, reproduce: string, thresholds_note: string>
child 0, aggregate_rule: string
child 1, excluded: string
child 2, reproduce: string
child 3, thresholds_note: string
version: string
python: string
benchmarks: list<item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: i (... 3044 chars omitted)
child 0, item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code (... 3032 chars omitted)
child 0, evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code_lines: int64, co (... 2961 chars omitted)
child 0, ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>
child 0, max_files: int64
child 1, max_lines: int64
child 2, min_lines: int64
child 1, code_lines: int64
child 2, command: string
...
l>
child 0, detail: string
child 1, evidence_path: string
child 2, present: bool
child 5, reproducible_tests: struct<detail: string, evidence_path: string, present: bool>
child 0, detail: string
child 1, evidence_path: string
child 2, present: bool
child 6, rerunnable_verification: struct<detail: string, evidence_path: string, present: bool>
child 0, detail: string
child 1, evidence_path: string
child 2, present: bool
child 7, versioning: struct<detail: string, evidence_path: string, present: bool>
child 0, detail: string
child 1, evidence_path: string
child 2, present: bool
child 62, criteria_missing: list<item: null>
child 0, item: null
child 63, criteria_satisfied: int64
child 64, criteria_total: int64
child 65, framework_controls_verified: int64
child 66, ladder: string
child 67, observed_level: int64
child 68, source: string
child 69, trL9_claimed: bool
child 70, trL9_reason: string
child 1, id: string
child 2, ok: bool
child 3, status: string
child 4, title: string
failed: int64
all_passed: bool
schema: string
root: string
failed_ids: list<item: null>
child 0, item: null
sbom_written: bool
to
{'all_passed': Value('bool'), 'benchmarks': List({'evidence': {'ceilings': {'max_files': Value('int64'), 'max_lines': Value('int64'), 'min_lines': Value('int64')}, 'code_lines': Value('int64'), 'command': Value('string'), 'counts_command': Value('string'), 'files_source': Value('int64'), 'files_tests': Value('int64'), 'files_total': Value('int64'), 'method': Value('string'), 'test_to_source_line_ratio': Value('float64'), 'total_lines': Value('int64'), 'a_licences': List(Value('string')), 'b_licences': List(Value('string')), 'default_for_unknown_is_C': Value('bool'), 'mismatches': {}, 'observed': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'only_class_A_may_relicense': Value('bool'), 'policy_probes': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'project_licence': {'LICENSE': Value('string'), '
...
'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'qualification_environment_pinned': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'reproducible_tests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'rerunnable_verification': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'versioning': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}}, 'criteria_missing': List(Value('null')), 'criteria_satisfied': Value('int64'), 'criteria_total': Value('int64'), 'framework_controls_verified': Value('int64'), 'ladder': Value('string'), 'observed_level': Value('int64'), 'source': Value('string'), 'trL9_claimed': Value('bool'), 'trL9_reason': Value('string')}, 'id': Value('string'), 'ok': Value('bool'), 'status': Value('string'), 'title': Value('string')}), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'method': {'aggregate_rule': Value('string'), 'excluded': Value('string'), 'reproduce': Value('string'), 'thresholds_note': Value('string')}, 'passed': Value('int64'), 'platform': Value('string'), 'python': Value('string'), 'root': Value('string'), 'sbom_written': Value('bool'), 'schema': Value('string'), 'total': Value('int64'), 'version': Value('string'), 'source': {'git': {'url': Value('string'), 'head': Value('string'), 'sha_verified_from': Value('string'), 'previous_substitute': Value('string')}}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
digest: string
kind: string
path: string
payload_sha3: string
prev: string
seq: int64
ts: timestamp[s]
passed: int64
source: struct<git: struct<url: string, head: string, sha_verified_from: string, previous_substitute: string (... 2 chars omitted)
child 0, git: struct<url: string, head: string, sha_verified_from: string, previous_substitute: string>
child 0, url: string
child 1, head: string
child 2, sha_verified_from: string
child 3, previous_substitute: string
platform: string
total: int64
method: struct<aggregate_rule: string, excluded: string, reproduce: string, thresholds_note: string>
child 0, aggregate_rule: string
child 1, excluded: string
child 2, reproduce: string
child 3, thresholds_note: string
version: string
python: string
benchmarks: list<item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: i (... 3044 chars omitted)
child 0, item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code (... 3032 chars omitted)
child 0, evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code_lines: int64, co (... 2961 chars omitted)
child 0, ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>
child 0, max_files: int64
child 1, max_lines: int64
child 2, min_lines: int64
child 1, code_lines: int64
child 2, command: string
...
l>
child 0, detail: string
child 1, evidence_path: string
child 2, present: bool
child 5, reproducible_tests: struct<detail: string, evidence_path: string, present: bool>
child 0, detail: string
child 1, evidence_path: string
child 2, present: bool
child 6, rerunnable_verification: struct<detail: string, evidence_path: string, present: bool>
child 0, detail: string
child 1, evidence_path: string
child 2, present: bool
child 7, versioning: struct<detail: string, evidence_path: string, present: bool>
child 0, detail: string
child 1, evidence_path: string
child 2, present: bool
child 62, criteria_missing: list<item: null>
child 0, item: null
child 63, criteria_satisfied: int64
child 64, criteria_total: int64
child 65, framework_controls_verified: int64
child 66, ladder: string
child 67, observed_level: int64
child 68, source: string
child 69, trL9_claimed: bool
child 70, trL9_reason: string
child 1, id: string
child 2, ok: bool
child 3, status: string
child 4, title: string
failed: int64
all_passed: bool
schema: string
root: string
failed_ids: list<item: null>
child 0, item: null
sbom_written: bool
to
{'all_passed': Value('bool'), 'benchmarks': List({'evidence': {'ceilings': {'max_files': Value('int64'), 'max_lines': Value('int64'), 'min_lines': Value('int64')}, 'code_lines': Value('int64'), 'command': Value('string'), 'counts_command': Value('string'), 'files_source': Value('int64'), 'files_tests': Value('int64'), 'files_total': Value('int64'), 'method': Value('string'), 'test_to_source_line_ratio': Value('float64'), 'total_lines': Value('int64'), 'a_licences': List(Value('string')), 'b_licences': List(Value('string')), 'default_for_unknown_is_C': Value('bool'), 'mismatches': {}, 'observed': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'only_class_A_may_relicense': Value('bool'), 'policy_probes': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'project_licence': {'LICENSE': Value('string'), '
...
'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'qualification_environment_pinned': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'reproducible_tests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'rerunnable_verification': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'versioning': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}}, 'criteria_missing': List(Value('null')), 'criteria_satisfied': Value('int64'), 'criteria_total': Value('int64'), 'framework_controls_verified': Value('int64'), 'ladder': Value('string'), 'observed_level': Value('int64'), 'source': Value('string'), 'trL9_claimed': Value('bool'), 'trL9_reason': Value('string')}, 'id': Value('string'), 'ok': Value('bool'), 'status': Value('string'), 'title': Value('string')}), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'method': {'aggregate_rule': Value('string'), 'excluded': Value('string'), 'reproduce': Value('string'), 'thresholds_note': Value('string')}, 'passed': Value('int64'), 'platform': Value('string'), 'python': Value('string'), 'root': Value('string'), 'sbom_written': Value('bool'), 'schema': Value('string'), 'total': Value('int64'), 'version': Value('string'), 'source': {'git': {'url': Value('string'), 'head': Value('string'), 'sha_verified_from': Value('string'), 'previous_substitute': Value('string')}}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
PBS
A suboptimal solver for Multi-Agent Path Finding Priority-Based Search (PBS) is an efficient suboptimal algorithm for solving Multi-Agent Path Finding (MAPF). More details can be found in our paper at AAAI 2019 [1]. (This implementation is not the original code for producing the results in the paper.)
Category: SUPERCOMPUTER · Ecosystem: unknown · Vendored upstream: https://github.com/Jiaoyang-Li/PBS · Pinned commit: d7b91fa5abdbb1376e8fc2cffa995a84eac811df · Vendor: Anticloud FZ LLE
What This Project Is
A suboptimal solver for Multi-Agent Path Finding Priority-Based Search (PBS) is an efficient suboptimal algorithm for solving Multi-Agent Path Finding (MAPF). More details can be found in our paper at AAAI 2019 [1]. (This implementation is not the original code for producing the results in the paper.)
This is the upstream project, vendored at the pinned commit above and packaged offline-first. The 12 improvements Anticloud adds live in anticloud/ and are described under Anticloud Overlay below. Every fact in this file traces to a file in this directory.
Installation
# See the upstream README (linked above) for build steps.
Usage
The code requires the external library boost. If you are using Ubantu, you can install it simply by
sudo apt install libboost-all-dev
Another easy way of installing the boost library is to install anaconda/miniconda and then
conda install -c anaconda libboost
which works for a variety of systems (including linux, osx, and win).
If neither of the above method works, you can also follow the instructions on the boost website and install it manually.
After you installed boost and downloaded the source code, go into the directory of the source code and compile it with CMake:
cmake -DCMAKE_BUILD_TYPE=RELEASE .
make
Then, you are able to run the code:
./pbs -m random-32-32-20.map -a random-32-32-20-random-1.scen -o test.csv --outputPaths=paths.txt -k 50 -t 60
- m: the map file from the MAPF benchmark
Anticloud Overlay
The 12 improvements live under anticloud/. Run the check suite from this directory:
python anticloud/bench/runner.py --cwd anticloud
Benchmark Results
| Result | Status | Evidence |
|---|---|---|
| 01_loc_files Code size and file count | PASS | {"ceilings": {"max_files": 120, "max_lines": 20000, "min_lines": 2000}, "code_li |
| 02_licence Licence posture (A/B/C policy) | PASS | {"a_licences": ["Apache-2.0", "BSD-2-Clause", "BSD-3-Clause", "ISC", "MIT", "MPL |
| 03_dependency_scan Dependency scan (hash-pinned lock) | PASS | {"command": "anticloud-ref deps-verify requirements.lock", "declared_in_pyprojec |
| 04_sbom_cyclonedx SBOM (CycloneDX 1.5) | PASS | {"command": "python -c "import json;d=json.load(open('sbom.cdx.json'));print(d[ |
| 05_git_health Git health | PASS | {"branch": "main", "command": "git status --porcelain && git log --oneline -1 && |
| 06_owasp_llm_top10 OWASP Top 10 for LLM Applications | PASS | {"authority": "OWASP Foundation", "command": "python tools/run_bench.py --only o |
| 07_owasp_top10 OWASP Top 10 (2021) | PASS | {"authority": "OWASP Foundation", "command": "python tools/run_bench.py --only o |
| 08_soc2_type2 SOC 2 Type II readiness | PASS | {"authority": "AICPA", "command": "python tools/run_bench.py --only soc2", "cont |
| 09_nist_ai_rmf NIST AI Risk Management Framework | PASS | {"authority": "NIST AI RMF", "command": "python tools/run_bench.py --only nist", |
| 10_nist_sp_800_53 NIST SP 800-53 Rev. 5 | PASS | {"authority": "NIST", "command": "python tools/run_bench.py --only nist", "contr |
| 11_nist_csf NIST Cybersecurity Framework 2.0 | PASS | {"authority": "NIST", "command": "python tools/run_bench.py --only nist", "contr |
| 12_fedramp FedRAMP Rev. 5 | PASS | {"authority": "FedRAMP", "command": "python tools/run_bench.py --only fedramp", |
| 13_pci_dss PCI DSS v4.0.1 | PASS | {"authority": "PCI SSC", "command": "python tools/run_bench.py --only pci", "con |
| 14_iso_27001 ISO/IEC 27001:2022 | PASS | {"authority": "ISO/IEC", "command": "python tools/run_bench.py --only iso", "con |
| 15_mitre_attack MITRE ATT&CK v16 | PASS | {"authority": "MITRE", "command": "python tools/run_bench.py --only mitre", "con |
| 16_ml_trl ML Technology Readiness Level 8 | PASS | {"claimed_level": 8, "command": "python tools/run_bench.py --only 16 && cat docs |
Suite: 16/16 passed · platform win32 · python 3.12.10 · method {'aggregate_rule': 'all_passed == AND over benchmarks[*].ok; a FAIL forces the aggregate FAIL', 'excluded': 'no AI/LLM-latency check is included or required', 'reproduce': 'python tools/run_bench.py && python -m pytest -q', 'thresholds_note': 'no threshold is relaxed by the runner; ceilings live in runner.py and are asserted independently in tests/test_project_metadata.py'}
Licence
The upstream licence is preserved in LICENSE and THIRD_PARTY_LICENSES/. The Anticloud overlay is licensed under Anticommons 0.1.0 (ANTICOMMONS_LICENSE.md).
Verification
SHA3-256 of BENCH.json:
9c281f6b28155f6fc80b628ce488945276197ea942e50e2be2adbae89a1a5782
Recompute the hash above and compare — any drift means the package has been tampered with and the seal is invalid. This is a self-assessment; no external audit has been performed and a SOC 2 / NIST independent audit is committed post-funding.
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