Instructions to use SZLHOLDINGS/szl-kernels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Kernels
How to use SZLHOLDINGS/szl-kernels with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("SZLHOLDINGS/szl-kernels") - Notebooks
- Google Colab
- Kaggle
| # SPDX-License-Identifier: Apache-2.0 | |
| """Suite tests for szl_kernels — cross-kernel provenance, advisory Λ, MEASURED energy.""" | |
| import sys, os, json | |
| sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "build", "torch-universal")) | |
| import torch | |
| import szl_kernels as sk | |
| def test_selfcheck_all_pass(): | |
| r = sk.selfcheck() | |
| assert r["ok"] is True, r | |
| assert all(r["checks"].values()), r["checks"] | |
| assert r["kernels_touched"] == ["governed_norm", "lambda_gate", "energy_core"] | |
| def test_one_chain_spans_three_kernels(): | |
| chain = sk.UnifiedReceiptChain() | |
| x = torch.randn(2, 32) | |
| sk.governed_rms_norm(chain, x, eps=1e-6) | |
| sk.governed_lambda_gate(chain, torch.tensor([0.9, 0.8, 0.95]), threshold=0.5) | |
| sk.governed_measure_energy(chain) | |
| ok, depth, brk = chain.verify() | |
| assert ok and depth == 3 and brk == -1 | |
| assert chain.kernels_touched() == ["governed_norm", "lambda_gate", "energy_core"] | |
| def test_lambda_is_advisory(): | |
| chain = sk.UnifiedReceiptChain() | |
| g = sk.governed_lambda_gate(chain, torch.tensor([0.9, 0.9, 0.9])) | |
| assert g["advisory"] is True | |
| rec = chain.tail(1)[0] | |
| assert rec["attrs"]["advisory"] is True | |
| assert "Conjecture 1" in rec["attrs"]["lambda_status"] | |
| def test_energy_measured_only_never_fabricated(): | |
| chain = sk.UnifiedReceiptChain() | |
| e = sk.governed_measure_energy(chain) # no NVML in CI | |
| assert e["joules"] is None | |
| assert e["label"] == "UNAVAILABLE_NO_NVML" | |
| def test_tamper_is_detected(): | |
| chain = sk.UnifiedReceiptChain() | |
| x = torch.randn(2, 16) | |
| sk.governed_rms_norm(chain, x, eps=1e-6) | |
| sk.governed_measure_energy(chain) | |
| recs = json.loads(chain.to_json()) | |
| recs[0]["attrs"]["eps"] = 9.99e-3 | |
| ok, _, brk = sk.UnifiedReceiptChain.verify_json(json.dumps(recs)) | |
| assert ok is False and brk == 0 | |
| def test_governed_block_composes_and_verifies(): | |
| blk = sk.GovernedBlock() | |
| res = blk.forward(torch.randn(2, 32), gov_axes=torch.tensor([0.95, 0.9, 0.92])) | |
| assert res["chain_ok"] and res["chain_depth"] == 4 | |
| assert res["kernels_touched"][-1] == "governed_block" | |
| def test_norm_matches_reference(): | |
| chain = sk.UnifiedReceiptChain() | |
| x = torch.randn(4, 64); w = torch.randn(64) | |
| y = sk.governed_rms_norm(chain, x, weight=w, eps=1e-6) | |
| ref = (x * torch.rsqrt(x.pow(2).mean(-1, keepdim=True) + 1e-6)) * w | |
| assert torch.allclose(y, ref, rtol=1e-5, atol=1e-5) | |
| if __name__ == "__main__": | |
| import traceback | |
| fns = [v for k, v in sorted(globals().items()) if k.startswith("test_")] | |
| p = f = 0 | |
| for fn in fns: | |
| try: | |
| fn(); print(f" PASS {fn.__name__}"); p += 1 | |
| except Exception: | |
| print(f" FAIL {fn.__name__}"); traceback.print_exc(); f += 1 | |
| print(f"\n{p} passed, {f} failed") | |
| sys.exit(1 if f else 0) | |