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from __future__ import annotations
import itertools
import random
from typing import Any, Dict, Optional
from edgeeda.agents.base import Action, Agent
from edgeeda.config import Config
from edgeeda.utils import sanitize_variant_prefix, stable_hash
class RandomSearchAgent(Agent):
def __init__(self, cfg: Config):
self.cfg = cfg
self.counter = 0
self.variant_prefix = sanitize_variant_prefix(cfg.experiment.name)
def _sample_knobs(self) -> Dict[str, Any]:
out: Dict[str, Any] = {}
for name, spec in self.cfg.tuning.knobs.items():
if spec.type == "int":
out[name] = random.randint(int(spec.min), int(spec.max))
else:
out[name] = float(spec.min) + random.random() * (float(spec.max) - float(spec.min))
out[name] = round(out[name], 3)
return out
def propose(self) -> Action:
self.counter += 1
knobs = self._sample_knobs()
variant = f"{self.variant_prefix}_t{self.counter:05d}_{stable_hash(str(knobs))}"
fidelity = self.cfg.flow.fidelities[0] # always start cheap
return Action(variant=variant, fidelity=fidelity, knobs=knobs)
def observe(self, action: Action, ok: bool, reward: Optional[float], metrics_flat: Optional[Dict[str, Any]]) -> None:
# Random agent doesn't adapt.
return
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