Files
axolotl/scripts/benchmarks/deepseek_v3_moe_sweep.py
Dan Saunders 8d8fa834a2 sweep
2025-09-25 14:27:34 -04:00

170 lines
4.4 KiB
Python

#!/usr/bin/env python
# mypy: ignore-errors
"""Sweep a set of DeepSeek V3 MoE benchmark configurations."""
from __future__ import annotations
import argparse
import csv
from pathlib import Path
from types import SimpleNamespace
from scripts.benchmarks.deepseek_v3_moe import (
DTYPE_MAP,
benchmark_deepseek_v3,
)
DEFAULT_SWEEP = [
{
"batch": 4,
"seq_len": 1024,
"hidden_size": 2048,
"moe_intermediate_size": 4096,
"n_experts": 64,
"top_k": 4,
"groups": 4,
},
{
"batch": 8,
"seq_len": 2048,
"hidden_size": 2048,
"moe_intermediate_size": 4096,
"n_experts": 64,
"top_k": 4,
"groups": 4,
},
{
"batch": 8,
"seq_len": 2048,
"hidden_size": 4096,
"moe_intermediate_size": 8192,
"n_experts": 128,
"top_k": 8,
"groups": 8,
},
{
"batch": 8,
"seq_len": 2048,
"hidden_size": 4096,
"moe_intermediate_size": 8192,
"n_experts": 256,
"top_k": 8,
"groups": 8,
},
]
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
"--dtype",
choices=DTYPE_MAP.keys(),
default="bf16",
help="Computation dtype for all benchmarks",
)
parser.add_argument(
"--device",
default="auto",
choices=["auto", "cpu", "cuda"],
help="Execution device",
)
parser.add_argument("--warmup", type=int, default=3, help="Warmup iterations")
parser.add_argument("--iters", type=int, default=15, help="Benchmark iterations")
parser.add_argument("--seed", type=int, default=0, help="Random seed")
parser.add_argument(
"--group-size",
type=int,
default=128,
help="GROUP_SIZE_M used by the Triton kernel",
)
parser.add_argument(
"--uniform-routing",
action="store_true",
help="Force uniform routing for every configuration",
)
parser.add_argument(
"--output",
type=Path,
help="Optional CSV file to store results",
)
return parser.parse_args()
def make_namespace(base: dict, args: argparse.Namespace) -> SimpleNamespace:
combined = dict(base)
combined.update(
{
"dtype": args.dtype,
"device": args.device,
"warmup": args.warmup,
"iters": args.iters,
"seed": args.seed,
"group_size": args.group_size,
"uniform_routing": args.uniform_routing,
}
)
return SimpleNamespace(**combined)
def main() -> None: # pragma: no cover - utility script
args = parse_args()
header = (
"batch",
"seq_len",
"hidden_size",
"moe_intermediate",
"n_experts",
"top_k",
"baseline_ms",
"patched_ms",
"speedup",
"min_tokens",
"max_tokens",
"max_diff",
)
rows = []
print(
f"Running sweep on device={args.device} dtype={args.dtype} uniform_routing={args.uniform_routing}"
)
print(
f"{'batch':>5} {'seq':>5} {'hidden':>7} {'experts':>7} {'topk':>4} {'baseline':>12} {'patched':>12} {'speedup':>8}"
)
for cfg in DEFAULT_SWEEP:
ns = make_namespace(cfg, args)
result = benchmark_deepseek_v3(ns)
rows.append(
(
cfg["batch"],
cfg["seq_len"],
cfg["hidden_size"],
cfg["moe_intermediate_size"],
cfg["n_experts"],
cfg["top_k"],
result["baseline_ms"],
result["patched_ms"],
result["speedup"],
result["min_tokens"],
result["max_tokens"],
result["max_diff"],
)
)
print(
f"{cfg['batch']:>5} {cfg['seq_len']:>5} {cfg['hidden_size']:>7} {cfg['n_experts']:>7} {cfg['top_k']:>4}"
f" {result['baseline_ms']:>11.3f} ms {result['patched_ms']:>11.3f} ms {result['speedup']:>7.2f}x"
)
if args.output:
args.output.parent.mkdir(parents=True, exist_ok=True)
with args.output.open("w", newline="") as fp:
writer = csv.writer(fp)
writer.writerow(header)
writer.writerows(rows)
print(f"Results written to {args.output}")
if __name__ == "__main__":
main()