commaai
/
tinygrad
mirror of https://github.com/commaai/tinygrad.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

big graph var_vals as rewrite context (#7007) 

* var_vals as rewrite context

* no default arg

* add st var_vals

* delete some stuff

* add the rewrite rule again

* extra

* this whole part is preschedule

* test with a second context

* redo

* i always forget tensor variable
This commit is contained in:
qazal 2024-10-16 07:31:44 +03:00 committed by GitHub
parent 390171d686
commit 40f33c110b
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 23 additions and 25 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
test/external/process_replay/process_replay.py vendored
View File

@ -30,7 +30,7 @@ if REF == "master": SKIP_PROCESS_REPLAY = True
# *** recreators
def recreate_sched(sink:UOp, ctx, _) -> UOp: return full_ast_rewrite(sink, ctx)
def recreate_sched(sink:UOp, ctx, _) -> UOp: return full_ast_rewrite(sink, ctx, {})
def recreate_kernel(ast:UOp, opts:Renderer, applied_opts:List[Opt], name:str, ctx:ProcessReplayContext, _) -> str:
with Context(**{k:v for k,v in ctx.ctx_vars.items() if k in ContextVar._cache and k != "DEBUG"}):
k = Kernel(ast, opts=opts)

46
tinygrad/engine/schedule.py
View File

@ -121,7 +121,14 @@ view_right = merge_views+PatternMatcher([
(UPat(UOps.REDUCE_AXIS, src=(UPat(UOps.REDUCE_AXIS, name="first_reduce"),), name="root"), merge_double_reduce),
])
enumerate_bufs = PatternMatcher([(UPat(UOps.BUFFER, name="x"), lambda ctx,x: UOp(UOps.DEFINE_GLOBAL, x.dtype, (), ctx.index(x.arg[0])))])
def simplify_and_unbind(ctx, x:UOp) -> Optional[UOp]:
if (st:=unwrap(x.st)) in ctx[2]: return None
st, var_vals = st.simplify().unbind()
ctx[0].update(var_vals)
ctx[2].add(st)
return st.to_uop()
append_vars = PatternMatcher([(UPat(UOps.VIEW, name="x"), simplify_and_unbind)])
enumerate_bufs = PatternMatcher([(UPat(UOps.BUFFER, name="x"), lambda ctx,x: UOp(UOps.DEFINE_GLOBAL, x.dtype, (), ctx[1].index(x.arg[0])))])
PROCESS_REPLAY_CAPTURE: List[Tuple[UOp, Tuple[int, ...], UOp]] = []
if getenv("RUN_PROCESS_REPLAY"):
@ -130,15 +137,15 @@ if getenv("RUN_PROCESS_REPLAY"):
for base_sink,ctx,ret in PROCESS_REPLAY_CAPTURE: diskcache_put("schedule_process_replay", str(base_sink.key), (base_sink, ctx, ret))
@track_rewrites
def full_ast_rewrite(base_sink:UOp, bufs:Tuple[int, ...]) -> UOp:
def full_ast_rewrite(base_sink:UOp, bufs:Tuple[int, ...], var_vals:Dict[Variable, int]) -> UOp:
sink = graph_rewrite(graph_rewrite(base_sink, view_left), view_right)
ret = graph_rewrite(sink, enumerate_bufs, bufs)
ret = graph_rewrite(sink, append_vars+enumerate_bufs, (var_vals, bufs, set()))
PROCESS_REPLAY_CAPTURE.append((base_sink, bufs, ret))
return ret
# *** List[LazyBuffer] lowering to ScheduleItem ***
def _recursive_uop(buf:LazyBuffer, st:ShapeTracker, outputs:Tuple[LazyBuffer, ...], var_vals:Dict[Variable, int], inputs:List[LazyBuffer],
def _recursive_uop(buf:LazyBuffer, st:ShapeTracker, outputs:Tuple[LazyBuffer, ...], inputs:List[LazyBuffer],
buf_uops:Dict[Buffer, UOp], cache:Dict[Tuple[LazyBuffer, ShapeTracker], UOp]) -> UOp:
"""recursively create a UOp"""
if buf is not buf.base: st, buf = buf.st+st, buf.base
@ -149,17 +156,13 @@ def _recursive_uop(buf:LazyBuffer, st:ShapeTracker, outputs:Tuple[LazyBuffer, ..
# buffer ops define ShapeTracker
# if it's realized, it's a load and we add it to the inputs
if (ubuf:=buf_uops.get(buf.buffer)) is not None and buf not in outputs:
unbound_st, st_var_vals = st.simplify().unbind()
var_vals.update(st_var_vals)
if buf.op is MetaOps.CONST:
if isinstance(val:=buf.arg, UOp): var_vals.update([val.unbind()])
return ubuf.view(unbound_st)
if buf.op is MetaOps.CONST: return ubuf.view(st)
if not any(x.buffer is buf.buffer for x in outputs) and buf not in inputs: inputs.append(buf)
return UOp(UOps.LOAD, dtype, (ubuf, unbound_st.to_uop()))
return UOp(UOps.LOAD, dtype, (ubuf, st.to_uop()))
# only reduceop changes shape
src_st = ShapeTracker.from_shape(buf.srcs[0].shape) if buf.op in ReduceOps else st
src: List[UOp] = [_recursive_uop(x, src_st, outputs, var_vals, inputs, buf_uops, cache) for x in buf.srcs]
src: List[UOp] = [_recursive_uop(x, src_st, outputs, inputs, buf_uops, cache) for x in buf.srcs]
if buf.op in ReduceOps: ret = src[0].r(buf.op, buf.arg).view(st)
elif buf.op is MetaOps.CONTIGUOUS: ret = UOp(UOps.CONTIGUOUS, dtype, (buf_uops[buf.buffer], src[0]))
elif buf.op is MetaOps.ASSIGN: ret = UOp(UOps.ASSIGN, dtype, (buf_uops[buf.buffer], src[1]))
@ -169,32 +172,29 @@ def _recursive_uop(buf:LazyBuffer, st:ShapeTracker, outputs:Tuple[LazyBuffer, ..
cache[(buf, st)] = ret
return ret
def _lower_lazybuffer(outs:List[LazyBuffer], buf_uops:Dict[Buffer, UOp]) -> Tuple[LBScheduleItem, Dict[Variable, int]]:
def _lower_lazybuffer(outs:List[LazyBuffer], buf_uops:Dict[Buffer, UOp], var_vals:Dict[Variable, int]) -> LBScheduleItem:
"""describe the computation for a LazyBuffer with UOp + inputs + var_vals"""
if (out:=outs[0]).op in METAOPS:
return LBScheduleItem(UOp(METAOPS[cast(MetaOps, out.op)], out.dtype, (), out.arg), (out,)+tuple(x.base for x in out.srcs),
(out.metadata,) if out.metadata is not None else None), {}
(out.metadata,) if out.metadata is not None else None)
# create the stores
var_vals = merge_dicts([out.st.var_vals.copy() for out in outs])
cache: Dict[Tuple[LazyBuffer, ShapeTracker], UOp] = {}
ast: List[UOp] = []
inputs: List[LazyBuffer] = []
for out in outs:
src = _recursive_uop(out, output_st:=ShapeTracker.from_shape(out.shape), tuple(outs), var_vals, inputs, buf_uops, cache=cache)
src = _recursive_uop(out, output_st:=ShapeTracker.from_shape(out.shape), tuple(outs), inputs, buf_uops, cache=cache)
if out.op is MetaOps.ASSIGN and out.arg:
assert out.arg[0].shape == out.shape, f"ASSIGN must not override output shape {out.arg[0].shape} != {out.shape}"
output_st = out.arg[0]
output_st, vv = output_st.simplify().unbind()
var_vals.update(vv)
ast.append(UOp(UOps.STORE, dtypes.void, (buf_uops[out.buffer], output_st.to_uop(), src)))
sink = full_ast_rewrite(ast[0].sink(*ast[1:]), tuple(buf_uops[x.buffer].arg[0] for x in outs+inputs))
sink = full_ast_rewrite(ast[0].sink(*ast[1:]), tuple(buf_uops[x.buffer].arg[0] for x in outs+inputs), var_vals)
# we also allow masked views. if it has a single view and it's equal when you shrink a contig, it's fine
if len(assign_targets:=[x.src[0] for x in sink.sparents if x.op is UOps.ASSIGN]) != 0:
if not all((s:=x.st_arg).contiguous or (len(s.views) == 1 and (m:=s.views[0].mask) is not None \
and ShapeTracker.from_shape(s.shape).shrink(m) == s.shrink(m)) for x in sink.sparents if x.op is UOps.LOAD and x.src[0] in assign_targets):
raise RuntimeError("self operand of augmented assign must be contiguous.\nhelp: consider using .contiguous():\n"
+colored(" - a += a.T\n", "red")+colored(" + a += a.T.contiguous()", "green"))
return LBScheduleItem(sink, tuple(outs+inputs), tuple(dedup([x.metadata for x,_ in cache if x.metadata and x not in inputs]))), var_vals
return LBScheduleItem(sink, tuple(outs+inputs), tuple(dedup([x.metadata for x,_ in cache if x.metadata and x not in inputs])))
# *** DAG creation: decide which LazyBuffers should realize ***
@ -353,6 +353,7 @@ def _graph_schedule(outs:List[LazyBuffer]) -> \
output_groups: DefaultDict[LazyBuffer, List[LazyBuffer]] = defaultdict(list)
buf_uops: Dict[Buffer, UOp] = {}
var_vals: Dict[Variable, int] = {}
for buf in realizes:
if buf.realized is None and buf.op is not MetaOps.CONST:
output_groups[reduce_for_op[buf] if buf in reduce_for_op and MULTIOUTPUT else buf].append(buf)
@ -368,17 +369,14 @@ def _graph_schedule(outs:List[LazyBuffer]) -> \
buf.buffer.dtype = dtypes.float32
buf.buffer.options = None
if buf.op is MetaOps.CONST:
if isinstance(val:=buf.arg, UOp): var_vals.update([val.unbind()])
uop = UOp(UOps.VALID, dtypes.bool, (buf.st.to_uop(),)).where(v:=UOp.const(buf.dtype.scalar(), buf.arg), v.const_like(0))
# NOTE: UOps.BUFFER creation must come after the ImageDType fixup
else: uop = UOp(UOps.BUFFER, buf.buffer.dtype.ptr(), (), (len(buf_uops), (buf.buffer.device, buf.buffer.size, buf.buffer.dtype)))
buf_uops.setdefault(buf.buffer, uop)
# preschedule all buffers in realizes
prescheduled: List[LBScheduleItem] = []
var_vals: Dict[Variable, int] = {}
for outs in output_groups.values():
prescheduled.append((ret:=_lower_lazybuffer(outs, buf_uops))[0])
var_vals = merge_dicts([var_vals, ret[1]])
prescheduled = [_lower_lazybuffer(outs, buf_uops, var_vals) for outs in output_groups.values()]
schedule_targets = {out:lsi for lsi in prescheduled for out in lsi.outputs}
graph: DefaultDict[LBScheduleItem, List[LBScheduleItem]] = defaultdict(list)