Spaces:
Running
Running
File size: 1,643 Bytes
0c6c82c 44745f2 0c6c82c 44745f2 0c6c82c 44745f2 0c6c82c 44745f2 0c6c82c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | from __future__ import annotations
from .optimizer import capacity_search, compare_schedulers, compare_topologies, design_space_search
from .profiles import ACCELERATORS, MODELS
from .simulator import SCHEDULERS, run_simulation
def metadata() -> dict:
return {
"version": "0.3.0",
"models": list(MODELS.keys()),
"accelerators": list(ACCELERATORS.keys()),
"schedulers": sorted(SCHEDULERS),
"topologies": ["colocated", "disaggregated_pd"],
"profile_type": "analytical-reference",
}
def execute(action: str, payload: dict) -> dict:
if action == "simulate":
return run_simulation(payload)
if action == "capacity":
config = payload.get("config", payload)
return capacity_search(
config,
min_rate=float(payload.get("min_rate", 0.25)),
max_rate=float(payload.get("max_rate", 32.0)),
iterations=int(payload.get("iterations", 8)),
repetitions=int(payload.get("repetitions", 2)),
headroom=float(payload.get("headroom", 0.20)),
)
if action == "compare":
config = payload.get("config", payload)
return compare_schedulers(config, payload.get("schedulers"))
if action == "topology_compare":
config = payload.get("config", payload)
return compare_topologies(config)
if action == "design_space":
config = payload.get("config", payload)
return design_space_search(config, bool(payload.get("include_disaggregated", True)))
if action == "metadata":
return metadata()
raise ValueError(f"Unknown action: {action}")
|