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kernel is call (#14577)

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* call is kernel

* closer

* fix bugs

* dedup

* pm_gate_kernel_sink

* better

* Revert "better"

This reverts commit b4c799b810.

* Reapply "better"

This reverts commit e53f094ce7.

* cleanups

* work

* remove junk

* subtle fix

* index

* viz cleanups

* disable assert for now
This commit is contained in:
George Hotz
2026-02-07 10:10:14 +08:00
committed by GitHub
parent d87ae1c84c
commit ca6604eae2
10 changed files with 38 additions and 44 deletions
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1
test/test_profiler.py
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@@ -212,6 +212,7 @@ class TestProfiler(unittest.TestCase):
for ge in graphs:
self.assertEqual(len(ge.ents), len(graphs))
@unittest.skip("this test is flaky")
def test_trace_metadata(self):
with Context(TRACEMETA=1):
a = Tensor.empty(1)+2

2
tinygrad/codegen/__init__.py
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@@ -112,7 +112,7 @@ def full_rewrite_to_sink(sink:UOp, ren:Renderer|None=None, optimize:bool=True) -
# inject IF/ENDIF. only needed if device doesn't support gated stores
pm_linearize_cleanups = PatternMatcher([
# if statements are not allowed in the graph
(UPat((Ops.IF, Ops.ENDIF)), lambda: panic(RuntimeError("if not allowed in graph"))),
(UPat((Ops.IF, Ops.ENDIF)), lambda: panic(RuntimeError, "if not allowed in graph")),
# gated INDEX becomes IF-STORE-ENDIF. this is the only use of IF-ENDIF
(UPat(Ops.STORE, name="u", src=(UPat(Ops.INDEX, src=(UPat(), UPat(), UPat(name="gate", dtype=dtypes.bool))).or_casted(), UPat())),
lambda u, gate: (u, [mif:=UOp(Ops.IF, src=(gate, u.src[0])), u, UOp(Ops.ENDIF, src=(mif,))]))

14
tinygrad/engine/schedule.py
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@@ -1,7 +1,7 @@
import time
from typing import cast
from collections import deque
from tinygrad.uop.ops import UOp, Ops, buffers, UOpMetaClass, track_rewrites, PatternMatcher, UPat, graph_rewrite, graph_rewrite_map, Kernel
from tinygrad.uop.ops import UOp, Ops, buffers, UOpMetaClass, track_rewrites, PatternMatcher, UPat, graph_rewrite, graph_rewrite_map, gate_kernel_sink
from tinygrad.uop.spec import type_verify, tensor_spec
from tinygrad.device import Buffer, MultiBuffer
from tinygrad.helpers import DEBUG, cpu_profile, TracingKey, SPEC, flatten, pluralize, SCACHE, Metadata
@@ -22,14 +22,14 @@ def create_schedule(sched_sink:UOp) -> tuple[list[ExecItem], UOp]:
# build kernel dependency graph: edges from producer kernel to consumer kernels
children: dict[UOp, list[UOp]] = {}
in_degree: dict[UOp, int] = {}
for u in sched_sink.toposort():
for u in sched_sink.toposort(gate_kernel_sink):
if u.op is Ops.RANGE: in_degree.setdefault(u, 0)
if u.op is not Ops.AFTER: continue
if (k:=u.src[1]).op is Ops.RANGE: continue # RANGEs are scheduled directly, not through dependency graph
assert k.op in {Ops.KERNEL, Ops.END}, f"AFTER src[1] should be KERNEL or END, not {k.op}"
in_degree.setdefault(k, 0)
if k.op is Ops.END: assert k.src[0].op is Ops.KERNEL, f"END src[0] should be KERNEL, not {k.src[0].op}"
for s in k.src[0].src if k.op is Ops.END else k.src:
for s in k.src[0].src[1:] if k.op is Ops.END else k.src[1:]:
match (s := _unwrap_src(s)).op:
case Ops.AFTER:
children.setdefault(s.src[1], []).append(k)
@@ -57,10 +57,10 @@ def create_schedule(sched_sink:UOp) -> tuple[list[ExecItem], UOp]:
assert k.op in {Ops.RANGE, Ops.KERNEL}, f"unexpected op in queue: {k.op}"
if k.op is Ops.RANGE: schedule.append(k)
elif k.op is Ops.KERNEL:
ast = (kernel:=cast(Kernel, k.arg)).ast
buf_uops = tuple(_unwrap_src(s).buf_uop for s in k.src if s.op is not Ops.BIND)
bound_ranges = tuple(s for s in k.src if s.op is Ops.BIND and len(s.src) > 1 and s.src[1].op is Ops.RANGE)
sched_item[k] = (ast, buf_uops, kernel.metadata, bound_ranges)
ast = k.src[0]
buf_uops = tuple(_unwrap_src(s).buf_uop for s in k.src[1:] if s.op is not Ops.BIND)
bound_ranges = tuple(s for s in k.src[1:] if s.op is Ops.BIND and len(s.src) > 1 and s.src[1].op is Ops.RANGE)
sched_item[k] = (ast, buf_uops, k.arg.metadata, bound_ranges)
schedule.append(k)
if rk.op is Ops.END: schedule.append(rk)
for x in children.get(rk, []):

4
tinygrad/helpers.py
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@@ -86,7 +86,9 @@ def word_wrap(x, wrap=80):
while len(ansistrip(x[:i])) < wrap and i < len(x): i += 1
return x[:i] + "\n" + word_wrap(x[i:], wrap)
def pad_bytes(b:bytes, align:int) -> bytes: return b + b'\x00' * ((align - (len(b) % align)) % align)
def panic(e:Exception|None=None): raise e if e is not None else RuntimeError("PANIC!")
# NOTE: you must create the exception inside the function where it's raised or you will get a GC cycle!
def panic(e:type[Exception]|None=None, *arg): raise e(*arg) if e is not None else RuntimeError("PANIC!")
@functools.cache
def canonicalize_strides(shape:tuple[T, ...], strides:tuple[T, ...]) -> tuple[T, ...]:

6
tinygrad/schedule/indexing.py
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@@ -3,7 +3,7 @@ import functools, itertools
from dataclasses import dataclass, field
from tinygrad.dtype import dtypes, AddrSpace
from tinygrad.uop.ops import PatternMatcher, UPat, Ops, UOp, resolve, GroupOp, graph_rewrite, sint, AxisType, profile_matches
from tinygrad.uop.ops import consumer_map_from_toposort
from tinygrad.uop.ops import consumer_map_from_toposort, gate_kernel_sink, pm_gate_kernel_sink
from tinygrad.uop.symbolic import symbolic, pm_simplify_valid, pm_drop_and_clauses
from tinygrad.helpers import argsort, all_same, cpu_profile, PCONTIG, colored
@@ -17,7 +17,7 @@ def realize_srcs(ctx:dict[UOp, None], rb:UOp) -> None:
for s in rb.src:
if s.base.op not in ALWAYS_CONTIGUOUS: ctx[s] = None
pm_generate_realize_map = PatternMatcher([
pm_generate_realize_map = pm_gate_kernel_sink+PatternMatcher([
# always realize SINK src
(UPat(Ops.SINK, name="s"), lambda ctx,s: ctx.update((x.base, None) for x in s.src if x.base.op not in ALWAYS_CONTIGUOUS)),
# always realize
@@ -159,7 +159,7 @@ def run_rangeify(tsink:UOp, debug:bool=False) -> tuple[UOp, IndexingContext]:
# get the consumer map
with cpu_profile("consumer map in rangeify", "TINY"):
consumer_map = consumer_map_from_toposort(tsink_toposort:=tsink.toposort())
consumer_map = consumer_map_from_toposort(tsink_toposort:=tsink.toposort(gate_kernel_sink))
# explicit rangeify
ending_ranges: dict[UOp, list[UOp]] = {}

18
tinygrad/schedule/rangeify.py
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@@ -1,8 +1,8 @@
from dataclasses import dataclass, field, replace
import itertools
from tinygrad.dtype import dtypes, PtrDType, ImageDType, AddrSpace
from tinygrad.uop.ops import PatternMatcher, UPat, Ops, UOp, resolve, GroupOp, _substitute, KernelInfo
from tinygrad.uop.ops import graph_rewrite, identity_element, sint, AxisType, BottomUpGate, Kernel, _remove_all_tags, range_str
from tinygrad.uop.ops import PatternMatcher, UPat, Ops, UOp, resolve, GroupOp, _substitute, KernelInfo, pm_gate_kernel_sink
from tinygrad.uop.ops import graph_rewrite, identity_element, sint, AxisType, BottomUpGate, _remove_all_tags, range_str
from tinygrad.uop.symbolic import symbolic
from tinygrad.helpers import argsort, prod, all_same, getenv, flatten, dedup, all_int, DEBUG, SPLIT_REDUCEOP, DEBUG_RANGEIFY
from tinygrad.helpers import PCONTIG, partition, get_single_element
@@ -72,7 +72,7 @@ mop_cleanup = PatternMatcher([
def resolve_custom_kernel(ck:UOp) -> UOp:
placeholders = [UOp.placeholder_like(s, slot=i) for i,s in enumerate(ck.src)]
return UOp(Ops.KERNEL, src=ck.src, arg=Kernel(ck.arg.fxn(*placeholders)))
return ck.arg.fxn(*placeholders).call(*ck.src)
def resolve_call(c:UOp) -> UOp|None:
# don't resolve real kernel calls, sink or program
@@ -525,10 +525,9 @@ def split_store(ctx:list[UOp], x:UOp) -> UOp|None:
else: ret = ret.sink(arg=KernelInfo(opts_to_apply=lctx.opts))
metadata = tuple(dedup(flatten([x for x in metadatas if x is not None])))[::-1]
kernel_arg = Kernel(ret, metadata)
kernel = UOp(Ops.KERNEL, src=tuple(lctx.map.values())+tuple(lctx.vars.keys()), arg=kernel_arg)
if ret.op is Ops.SINK and not all_same([x.device for x in kernel.src if x.op is not Ops.BIND]):
raise RuntimeError(f"all buffers must be on the same device: {tuple(b.buf_uop for b in kernel.src)}")
kernel = ret.call(*lctx.map.values(), *lctx.vars.keys(), metadata=metadata)
if ret.op is Ops.SINK and not all_same([x.device for x in kernel.src[1:] if x.op is not Ops.BIND]):
raise RuntimeError(f"all buffers must be on the same device: {tuple(b.buf_uop for b in kernel.src[1:])}")
return kernel
split_kernels = PatternMatcher([
@@ -588,8 +587,9 @@ def get_rangeify_map(sink:UOp) -> dict[UOp, UOp]:
# bufferize -> store
lunique_start: int = max([-1]+[x.arg for x in tsink.toposort() if x.op is Ops.LUNIQUE]) + 1
tsink = graph_rewrite(tsink, pm_add_buffers+pm_add_range_tags, ctx=itertools.count(lunique_start), bottom_up=True, name="bufferize to store")
tsink = graph_rewrite(tsink, split_kernels, ctx=uop_list, bottom_up=True, name="split kernels")
tsink = graph_rewrite(tsink, pm_gate_kernel_sink+pm_add_buffers+pm_add_range_tags, ctx=itertools.count(lunique_start), bottom_up=True,
name="bufferize to store")
tsink = graph_rewrite(tsink, pm_gate_kernel_sink+split_kernels, ctx=uop_list, bottom_up=True, name="split kernels")
# if a kernel depends on a buffer, and that buffer is later assigned to, make the assign depend on the kernel's assign
kernel_assign: dict[UOp, UOp] = {}

3
tinygrad/uop/__init__.py
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@@ -79,8 +79,9 @@ class Ops(FastEnum):
# ** 6 -- ops that don't exist in programs **
# tensor graph ops
UNIQUE = auto(); DEVICE = auto(); KERNEL = auto(); ASSIGN = auto()
UNIQUE = auto(); DEVICE = auto(); ASSIGN = auto()
CUSTOM_KERNEL = auto()
KERNEL = CALL
# local unique
LUNIQUE = auto()

19
tinygrad/uop/ops.py
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@@ -236,9 +236,6 @@ class UOp(OpMixin, metaclass=UOpMetaClass):
case Ops.REDUCE | Ops.MSTACK | Ops.MSELECT | Ops.DETACH | Ops.CONTIGUOUS | Ops.CONTIGUOUS_BACKWARD | Ops.AFTER | Ops.END | Ops.CALL:
return self.src[0]._shape
# ops with custom handling
case Ops.KERNEL: return self.arg.ast._shape
# TODO: disallow shape changing bitcast
case Ops.BITCAST:
ps = self.src[0]._shape
@@ -367,9 +364,7 @@ class UOp(OpMixin, metaclass=UOpMetaClass):
@recursive_property
def trace_num(self):
num = next(ucount)
# KERNEL also has a UOp in the arg
arg = type(self.arg)(self.arg.ast.trace_num, self.arg.metadata) if self.op is Ops.KERNEL else self.arg
uop_fields[num] = (self.op, self.dtype, tuple(s.trace_num for s in self.src), arg, self.tag)+((self.metadata,) if TRACEMETA>=2 else ())
uop_fields[num] = (self.op, self.dtype, tuple(s.trace_num for s in self.src), self.arg, self.tag)+((self.metadata,) if TRACEMETA>=2 else ())
return num
# *** uop syntactic sugar ***
@@ -823,7 +818,8 @@ class UOp(OpMixin, metaclass=UOpMetaClass):
return UOp(Ops.PARAM, dtype, src, arg=slot)
def call(self, *srcs:UOp, grad_fxn:Callable|None=None, metadata:tuple[Metadata, ...]=()) -> UOp:
assert len(self.ranges) == 0, f"ranges {self.ranges} are leaking out of the call"
# TODO: reenable this after ENCDEC is fixed
#assert len(self.ranges) == 0, f"ranges {self.ranges} are leaking out of the call in {self.pyrender()}"
return UOp(Ops.CALL, self.dtype, (self,)+srcs, CallInfo(grad_fxn, metadata))
def custom_kernel(*srcs:UOp, fxn:Callable, grad_fxn:Callable|None=None) -> list[UOp]:
contig_srcs = tuple(x.contiguous() if x.op is not Ops.AFTER else x for x in srcs)
@@ -1322,6 +1318,9 @@ def _index_to_concrete_int(u:UOp) -> UOp: return graph_rewrite(u.sink(), pm_lowe
_substitute = PatternMatcher([(UPat(tuple(Ops), name="x"), lambda ctx,x: ctx.get(x,None))])
_remove_all_tags = PatternMatcher([(UPat(GroupOp.All, name="x"), lambda x: x.replace(tag=None) if x.tag is not None else None)])
def gate_kernel_sink(x:UOp) -> bool: return not (x.op is Ops.SINK and isinstance(x.arg, KernelInfo))
pm_gate_kernel_sink = PatternMatcher([(UPat(Ops.SINK, name="sink"), lambda sink: None if gate_kernel_sink(sink) else panic(BottomUpGate))])
def do_unbind(ctx:dict[Variable, int], x:UOp):
v,i = x.unbind()
ctx[v] = i
@@ -1419,7 +1418,6 @@ pm_pyrender_extra = PatternMatcher([
# NOTE: you can remove pm_pyrender_extra and it'll still be correct
pm_pyrender = pm_pyrender_extra+PatternMatcher([
(UPat(Ops.KERNEL, name="u"), lambda ctx,u: f"UOp(Ops.KERNEL, src={srcs(ctx,u.src)}, arg=Kernel({ctx[u.arg.ast]}(), {u.arg.metadata}))"),
(UPat(GroupOp.All, name="u"), lambda ctx,u: f"UOp({u.op}, {u.dtype}, {srcs(ctx,u.src)}"+(f", {repr(u.arg)})" if u.arg is not None else ")")),
])
@@ -1452,11 +1450,6 @@ def pyrender(ast:UOp) -> str:
op_depth = 1 + max([depth[s] for s in u.src], default=0)
if op_depth > 100: to_render.add(u)
depth[u] = 0 if u in to_render else op_depth
# do the rendering
if u.op is Ops.KERNEL:
if u.arg.ast not in kernels:
kernels[u.arg.ast] = (f"k{len(kernels)}", f"def k{len(kernels)}():\n " + pyrender(u.arg.ast).replace('\n', '\n ') + "\n return ast\n\n")
r[u.arg.ast] = kernels[u.arg.ast][0]
ren = cast(str, pm_pyrender.rewrite(u, ctx=r))
assert isinstance(ren, str)
if u.tag is not None: ren += f".rtag({repr(u.tag)})"

7
tinygrad/uop/validate.py
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@@ -25,9 +25,10 @@ z3_renderer = PatternMatcher([
(UPat(Ops.SPECIAL, name="x"), lambda x,ctx: create_bounded(x.arg, 0, ctx[1][x.src[0]]-1, ctx[0])),
(UPat(Ops.DEFINE_VAR, name="x"), lambda x,ctx: create_bounded(x.arg[0], x.arg[1], x.arg[2], ctx[0])),
(UPat(Ops.RANGE, name="x"), lambda x,ctx: create_bounded(x.render(simplify=False), 0, ctx[1][x.src[0]]-1, ctx[0])),
# loads are variables bounded by the min/max of the dtype
(UPat(Ops.LOAD, dtypes.ints+(dtypes.index,), name="x"), lambda x,ctx: create_bounded(f"load{len(ctx[1])}", x.dtype.min, x.dtype.max, ctx[0])),
(UPat(Ops.LOAD, dtypes.bool, name="x"), lambda x,ctx: (z3.Bool(f"load{len(ctx[1])}", ctx=ctx[0]), None)),
# loads are variables bounded by the min/max of the dtype. non-pointer INDEX is also a LOAD
(UPat((Ops.LOAD, Ops.INDEX), dtypes.ints+(dtypes.index,), name="x"), lambda x,ctx:
create_bounded(f"load{len(ctx[1])}", x.dtype.min, x.dtype.max, ctx[0])),
(UPat((Ops.LOAD, Ops.INDEX), dtypes.bool, name="x"), lambda x,ctx: (z3.Bool(f"load{len(ctx[1])}", ctx=ctx[0]), None)),
# constants
(UPat(Ops.CONST, arg=Invalid, name="x"), lambda x,ctx: (z3.Int("Invalid", ctx=ctx[0]), None)),
(UPat(Ops.CONST, dtypes.ints+(dtypes.index,), name="x"), lambda x,ctx: (z3.IntVal(x.arg, ctx=ctx[0]), None)),

8
tinygrad/viz/serve.py
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@@ -45,7 +45,7 @@ from tinygrad.dtype import dtypes
uops_colors = {Ops.LOAD: "#ffc0c0", Ops.STORE: "#87CEEB", Ops.CONST: "#e0e0e0", Ops.VCONST: "#e0e0e0", Ops.REDUCE: "#FF5B5B",
Ops.PARAM:"#cb9037", **{x:"#f2cb91" for x in {Ops.DEFINE_LOCAL, Ops.DEFINE_REG}}, Ops.REDUCE_AXIS: "#FF6B6B",
Ops.RANGE: "#c8a0e0", Ops.ASSIGN: "#909090", Ops.BARRIER: "#ff8080", Ops.IF: "#c8b0c0", Ops.SPECIAL: "#c0c0ff",
Ops.INDEX: "#cef263", Ops.WMMA: "#efefc0", Ops.MULTI: "#f6ccff", Ops.KERNEL: "#3e7f55", Ops.CUSTOM_KERNEL: "#3ebf55",
Ops.INDEX: "#cef263", Ops.WMMA: "#efefc0", Ops.MULTI: "#f6ccff", Ops.CUSTOM_KERNEL: "#3ebf55",
**{x:"#D8F9E4" for x in GroupOp.Movement}, **{x:"#ffffc0" for x in GroupOp.ALU}, Ops.THREEFRY:"#ffff80",
Ops.BUFFER_VIEW: "#E5EAFF", Ops.BUFFER: "#B0BDFF", Ops.COPY: "#a040a0", Ops.ENCDEC: "#bf71b6",
Ops.CALL: "#00B7C8", Ops.PARAM: "#14686F",
@@ -106,9 +106,6 @@ def uop_to_json(x:UOp) -> dict[int, dict]:
if u in excluded: continue
argst = codecs.decode(str(u.arg), "unicode_escape")
if u.op in GroupOp.Movement: argst = (mask_to_str if u.op in {Ops.SHRINK, Ops.PAD} else shape_to_str)(u.marg)
if u.op is Ops.KERNEL:
ast_str = f"SINK{tuple(s.op for s in u.arg.ast.src)}" if u.arg.ast.op is Ops.SINK else repr(u.arg.ast.op)
argst = f"<Kernel {len(list(u.arg.ast.toposort()))} {ast_str} {[str(m) for m in u.arg.metadata]}>"
if u.op is Ops.BINARY: argst = f"<{len(u.arg)} bytes>"
label = f"{str(u.op).split('.')[1]}{(chr(10)+word_wrap(argst.replace(':', ''))) if u.arg is not None else ''}"
if u.dtype != dtypes.void: label += f"\n{u.dtype}"
@@ -130,7 +127,7 @@ def uop_to_json(x:UOp) -> dict[int, dict]:
label += "\n"+' '.join([f"{range_str(s, color=True)}({s.vmax+1})" for s in trngs])
except Exception:
label += "\n<ISSUE GETTING LABEL>"
if (ref:=ref_map.get(u.arg.ast) if u.op is Ops.KERNEL else None) is not None: label += f"\ncodegen@{ctxs[ref]['name']}"
if (ref:=ref_map.get(u.src[0]) if u.op is Ops.KERNEL else None) is not None: label += f"\ncodegen@{ctxs[ref]['name']}"
# NOTE: kernel already has metadata in arg
if TRACEMETA >= 2 and u.metadata is not None and u.op is not Ops.KERNEL: label += "\n"+str(u.metadata)
graph[id(u)] = {"label":label, "src":[(i,id(x)) for i,x in enumerate(u.src) if x not in excluded], "color":uops_colors.get(u.op, "#ffffff"),
@@ -140,7 +137,6 @@ def uop_to_json(x:UOp) -> dict[int, dict]:
@functools.cache
def _reconstruct(a:int):
op, dtype, src, arg, *rest = trace.uop_fields[a]
arg = type(arg)(_reconstruct(arg.ast), arg.metadata) if op is Ops.KERNEL else arg
return UOp(op, dtype, tuple(_reconstruct(s) for s in src), arg, *rest)
def get_full_rewrite(ctx:TrackedGraphRewrite) -> Generator[GraphRewriteDetails, None, None]: