| """Session-shape sweep on free CPU: what the shipped planner actually does at each candidate rate. |
| |
| The D-018 decision is not only "12,977 tok/s or 9,696 tok/s" -- it is how many billed sessions the run |
| becomes and whether the remaining weekly quota covers them. Both are computed by the launcher's own `plan()`, |
| so this runs that function rather than re-deriving the arithmetic in prose: import the pinned launcher, walk |
| the schedule leg by leg at each rate, and print the legs, the session count, the stepping hours and the |
| hours the week still owes. |
| |
| It mutates the module globals between walks, which is exactly what the environment variables do at launch, |
| so nothing here is a model of the planner -- it is the planner. |
| """ |
| import hashlib |
| import importlib.util |
| import json |
| import os |
| import subprocess |
| import sys |
|
|
| REV = "c237b478076f68da43dabd3403daa5639286899e" |
| SHA = "5fb14bc3597d999a21772a66b6f409f01f722019dc78da313feddb2f9c769c48" |
| os.chdir("/kaggle/working") |
| url = f"https://huggingface.co/Cion-lab/ounce100m-code/resolve/{REV}/kernels/phase4_session.py" |
| assert subprocess.run(["curl", "-sfL", url, "-o", "phase4_session.py"]).returncode == 0, "fetch launcher" |
| got = hashlib.sha256(open("phase4_session.py", "rb").read()).hexdigest() |
| assert got == SHA, ("LAUNCHER SHA MISMATCH", got[:16], SHA[:16]) |
| print("pinned launcher", got[:12], flush=True) |
|
|
| spec = importlib.util.spec_from_file_location("phase4_session", "phase4_session.py") |
| S = importlib.util.module_from_spec(spec) |
| spec.loader.exec_module(S) |
|
|
| RATES = [(9358.0, "checkpointed, the Gate 3 P3 measurement"), |
| (12300.0, "D-018's planning rate: sustained across probe 2's two legs"), |
| (12977.0, "no checkpointing, the optimistic 20-step progress-bar rate")] |
| QUOTAS = [26.3, 24.5, 22.0] |
|
|
| for rate, why in RATES: |
| S.PLANNING_TOK_PER_S = rate |
| sec_per_step = S.TOKENS_PER_STEP / rate |
| for quota in QUOTAS: |
| S.QUOTA_LEFT_HOURS = quota |
| legs, start, guard = [], 0, 0 |
| while start < S.HORIZON_STEPS and guard < 30: |
| guard += 1 |
| pl = S.plan(start, 19.5) |
| n = pl["planned_steps"] |
| if not n: |
| legs.append((start, "REFUSED", pl["usable_hours"])) |
| break |
| end = S.HORIZON_STEPS if pl["stop_after_steps"] == 0 else pl["stop_after_steps"] |
| legs.append((start, end, end - start)) |
| start = end |
| trained = sum(l[1] - l[0] for l in legs if isinstance(l[1], int)) |
| hours = trained * sec_per_step / 3600.0 |
| sessions = len(legs) |
| print("RATE %6.0f (%s) QUOTA %5.1f h -> %d sessions, %d/%d steps, %.2f h stepping; %s" % ( |
| rate, why, quota, sessions, trained, S.HORIZON_STEPS, hours, |
| "FITS" if trained == S.HORIZON_STEPS and hours <= quota else "DOES NOT FIT"), flush=True) |
| print(" legs", json.dumps(legs), flush=True) |
| if trained != S.HORIZON_STEPS: |
| print(" shortfall %d steps = %.2f h at this rate" % ( |
| S.HORIZON_STEPS - trained, (S.HORIZON_STEPS - trained) * sec_per_step / 3600.0), flush=True) |
| print("PLAN_SWEEP_DONE", flush=True) |
|
|
