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StarPilot/tinygrad_repo/tinygrad/codegen/opt/search.py
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firestar5683 22a8575199 Vendor dependencies and resources for standalone builds
Keep official openpilot ancestry and dependency licenses. Store resources directly in Git, remove LFS setup requirements, and leave the downloadable big model outside the source tree.
2026-10-03 21:01:18 +00:00

173 lines
9.1 KiB
Python

import math, time, traceback, signal
from dataclasses import replace
from tinygrad.uop.ops import sym_infer, AxisType, UOp, Ops
from tinygrad.uop.render import pyrender
from tinygrad.device import Device, Buffer
from tinygrad.helpers import prod, flatten, DEBUG, CACHELEVEL, diskcache_get, diskcache_put, getenv, colored, time_to_str
from tinygrad.helpers import IGNORE_BEAM_CACHE
from tinygrad.codegen.opt import Opt, OptOps, KernelOptError
from tinygrad.engine.realize import time_call
from tinygrad.engine.worker import get_worker_pool, terminate_worker_pool
from tinygrad.codegen import to_program
from tinygrad.codegen.opt.postrange import Scheduler
actions = [Opt(op=OptOps.SPLIT, axis=axis, arg=(amt, at)) for at in (AxisType.UPCAST, AxisType.UNROLL) for amt in [0,2,3,4,5,7] for axis in range(10)]
actions += [Opt(op=OptOps.SPLIT, axis=axis, arg=(amt, at)) for at in (AxisType.LOCAL, AxisType.GROUP_REDUCE)
for amt in [0,2,3,4,8,13,16,29] for axis in range(8)]
actions += [Opt(op=OptOps.SPLIT, axis=axis, arg=(amt, AxisType.GROUP_REDUCE, True)) for amt in [13,16,28,29,32,49,64,256] for axis in range(8)]
if getenv("BEAM_PADTO", 0): actions += [Opt(op=OptOps.PADTO, axis=axis, arg=amt) for amt in [32] for axis in range(7)]
actions += [Opt(op=OptOps.SPLIT, axis=0, arg=(32, at)) for at in (AxisType.LOCAL, AxisType.GROUP_REDUCE)]
actions += [Opt(op=OptOps.TC, axis=0, arg=(-1, 0, getenv("TC", 1)))]
# covers resnet kernels (3 global * 3 reduce)
actions += [Opt(op=OptOps.TC, axis=axis, arg=(-1, getenv("TC_OPT", 2), getenv("TC", 1))) for axis in range(9)]
actions += [Opt(op=OptOps.SWAP, axis=axis_0, arg=axis_1) for axis_0 in range(5) for axis_1 in range(axis_0+1, 5)]
def get_test_global_size(global_size, max_global_size, var_vals):
test_global_size = [sym_infer(sz, var_vals) for sz in global_size]
input_size = prod(test_global_size)
while prod(test_global_size) > max_global_size:
for j in range(len(global_size)-1,-1,-1):
if test_global_size[j] > 16:
test_global_size[j] //= 2
break
return test_global_size, input_size / prod(test_global_size)
def _time_program(prg:UOp, var_vals:dict[str, int], rawbufs:list[Buffer], early_stop:float|None=None,
allow_test_size:int=True, max_global_size:int|None=65536, clear_l2=False, cnt=3, name="test", dev_timeout=False) -> list[float]:
timeout = int(early_stop * 1e3) if dev_timeout and early_stop is not None and early_stop < math.inf else None
factor = 1
if allow_test_size and max_global_size is not None:
global_size, factor = get_test_global_size(prg.arg.global_size, max_global_size, var_vals)
prg = prg.replace(arg=replace(prg.arg, global_size=tuple(global_size)))
call = prg.call(*[UOp.from_buffer(b) for b in rawbufs])
tms, timer = [], time_call(call, var_vals, timeout=timeout, clear_l2=clear_l2)
for _ in range(cnt):
try: tms.append(next(timer) * factor)
except AssertionError: return [math.inf] * cnt
if early_stop is not None and early_stop < min(tms): break
return tms
class TimeoutException(Exception): pass
def timeout_handler(signum, frame):
if DEBUG >= 2: print("*** BEAM COMPILE TIMEOUT")
raise TimeoutException()
def _try_compile(x:tuple[int,Scheduler]) -> tuple[int, tuple[UOp, float]|None]:
if hasattr(signal, "alarm"):
signal.signal(getattr(signal, 'SIGALRM'), timeout_handler)
# set timeout
signal.alarm(getenv("BEAM_TIMEOUT_SEC", 10))
ret = None
try:
st = time.perf_counter()
ast, dev = x[1].copy().get_optimized_ast(name_override="test"), x[1].ren.target.device
prg = to_program(ast.substitute({p: p.replace(arg=replace(p.arg, device=dev)) for p in ast.toposort() if p.op is Ops.PARAM}), x[1].ren)
et = time.perf_counter() - st
uops = prg.src[1].src
if len(uops) >= (uops_max:=getenv("BEAM_UOPS_MAX", 3000)) > 0:
if getenv("BEAM_LOG_SURPASS_MAX"): print(f"too many uops. {len(uops)=}, {uops_max=}")
raise RuntimeError("too many uops")
ret = (prg, et)
except RuntimeError:
if DEBUG >= 4: traceback.print_exc()
except Exception as e:
if getenv("BEAM_STRICT_MODE"): raise e
finally:
if hasattr(signal, "alarm"): signal.alarm(0)
return x[0], ret
def _ensure_buffer_alloc(bufs:list[Buffer]) -> list[Buffer]: return [buf.ensure_allocated() if buf is not None else buf for buf in bufs]
# *** external API ***
# get dictionary of all possible actions
def get_kernel_actions(s:Scheduler, include_0=True, max_up:int|None=None) -> dict[int, Scheduler]:
acted, max_up, max_lcl = {0:s} if include_0 else {}, getenv("BEAM_UPCAST_MAX", 256) if max_up is None else max_up, getenv("BEAM_LOCAL_MAX", 1024)
for i,a in enumerate(actions):
if a.axis is not None and a.op is not OptOps.TC:
if (a.axis >= s.shape_len) or (a.op is OptOps.SPLIT and isinstance(arg:=a.arg, tuple) and s.full_shape[a.axis] == arg[0]
and replace(a, arg=(0,)+arg[1:]) in actions): continue
s2 = s.copy()
try:
s2.apply_opt(a)
up, lcl, tc_up = 1, 1, prod(tc.dims)//tc.threads if (tc:=s2.tensor_core) else 1
for x,t in zip(s2.full_shape, s2.axis_types):
if t in (AxisType.UPCAST, AxisType.UNROLL): up *= x
elif t in (AxisType.WARP, AxisType.LOCAL, AxisType.GROUP_REDUCE): lcl *= x
if up//tc_up > max_up or lcl > max_lcl:
if getenv("BEAM_LOG_SURPASS_MAX"): print(f"too many upcast/local. {up//tc_up=}, {max_up=}, {lcl=}, {max_lcl=}")
continue
acted[i+1] = s2
except KernelOptError: pass
return acted
BEAM_DEBUG = getenv("BEAM_DEBUG")
def beam_search(s:Scheduler, rawbufs:list[Buffer], var_vals:dict[str,int], amt:int, allow_test_size=True):
key = {"ast": s.ast.key, "amt": amt, "allow_test_size": allow_test_size, "device": s.ren.target.device, "suffix": s.ren.suffix}
if not IGNORE_BEAM_CACHE and CACHELEVEL >= 1 and (val:=diskcache_get("beam_search", key)) is not None:
ret = s.copy()
for o in val[len(s.applied_opts):]: ret.apply_opt(o)
return ret
beam: list[tuple[Scheduler, float]] = [(s, float("inf"))]
seen_libs = set()
pool = get_worker_pool()
min_progress = getenv("BEAM_MIN_PROGRESS", 0.01)/1e6
if BEAM_DEBUG:
print("BEAM_SEARCH:")
print(pyrender(s.ast.replace(arg=None)))
if DEBUG >= 2: print(f" 0.00s: from 1 -> 1 actions {s.colored_shape()}")
try:
rawbufs = _ensure_buffer_alloc(rawbufs)
exiting, st = False, time.perf_counter()
dev = Device[s.ren.target.device]
while not exiting:
candidates: list[Scheduler] = flatten([get_kernel_actions(si, include_0=False).values() for si,_ in beam])
timed: list[tuple[Scheduler, float]] = []
least_compute_ops = math.inf
for i, proc in ((map if pool is None else pool.imap_unordered)(_try_compile, enumerate(candidates))):
if proc is None: continue
prg, compile_et = proc
if (lib:=prg.src[3].arg) in seen_libs: continue
# filter out kernels that use 1000x more compute than the smallest
estimates = prg.src[0].arg.estimates
least_compute_ops = min(this_compute_ops:=sym_infer(estimates.ops if estimates is not None else 0, var_vals), least_compute_ops)
if least_compute_ops*1000 < this_compute_ops:
if getenv("BEAM_LOG_SURPASS_MAX"): print(f"too much compute. {this_compute_ops} when least is {least_compute_ops}")
continue
seen_libs.add(lib)
try: tms = _time_program(prg, var_vals, rawbufs, early_stop=beam[0][1]*3 if len(beam) else 1.0,
allow_test_size=allow_test_size, clear_l2=hasattr(dev, 'invalidate_caches'),
dev_timeout=getenv("BEAM_DEV_TIMEOUT", 1))
except Exception as e:
if BEAM_DEBUG: print(f"BEAM failed for opts: {candidates[i].applied_opts}\n{e}")
if isinstance(e, RuntimeError): continue
raise
timed.append((candidates[i], min(tms)))
if BEAM_DEBUG > 1:
print(f"{time.perf_counter() - st:7.2f}s: {i:5d} {len(prg.src[1].src):5d} uops",
f"{time_to_str(compile_et, w=12)} compile/{time_to_str(timed[-1][1], w=12)} run",
f" {len(timed):4d}/{len(candidates):4d} {timed[-1][0].colored_shape()}")
elif DEBUG >= 2:
print(f"\r{time.perf_counter() - st:7.2f}s: {time_to_str(timed[-1][1], w=12)}",
f" {len(timed):4d}/{len(candidates):4d} {timed[-1][0].colored_shape()}\033[K", end="")
# done
opts = sorted(timed, key=lambda x: x[1])
exiting = len(opts) == 0 or (opts[0][1] < min_progress) or (len(beam) > 0 and ((beam[0][1]-opts[0][1]) < min_progress))
if not exiting: beam = opts[:amt]
elif len(opts) > 0 and opts[0][1] < beam[0][1]: beam = opts[:1]
if DEBUG >= 2:
print(f"\r{time.perf_counter() - st:7.2f}s:", colored(time_to_str(beam[0][1], w=12), "green" if exiting else None),
f"from {len(candidates):3d} -> {len(opts):3d} actions\033[K", beam[0][0].colored_shape())
except KeyboardInterrupt as e:
terminate_worker_pool()
raise e
if CACHELEVEL >= 1: diskcache_put("beam_search", key, beam[0][0].applied_opts)
if BEAM_DEBUG: print(f"BEAM_SEARCH: final tm={time_to_str(beam[0][1], w=0)}, applied_opts={beam[0][0].applied_opts}")
return beam[0][0]