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Author SHA1 Message Date
geohot c9f1ed10c3 gate MULTIOUTPUT 2025-10-21 18:25:38 +08:00
George HotzandGitHub 483cd44cbf Merge branch 'master' into multioutput 2025-10-21 18:16:34 +08:00
geohot aecd51f54a start multioutput support 2025-10-20 11:17:00 +08:00
6 changed files with 48 additions and 6 deletions
+11
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@@ -2414,5 +2414,16 @@ class TestUOpBecome(unittest.TestCase):
b.shrink(((0,4),)).assign(a_view).realize()
self.assertListEqual(b.tolist(), [0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0])
class TestScheduleMultioutput(unittest.TestCase):
def test_simplest_multioutput(self):
with Context(MULTIOUTPUT=1):
a = Tensor.ones(256, 256).contiguous().realize()
r = a.sum(axis=1)
b = r+1
c = r+2
run_schedule(check_schedule([b, c], 1))
np.testing.assert_allclose(b.numpy(), 257)
np.testing.assert_allclose(c.numpy(), 258)
if __name__ == '__main__':
unittest.main(verbosity=2)
+1 -1
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@@ -86,7 +86,7 @@ def do_merge_ends(s:UOp):
replaces = {}
for k,v in stacked.items():
if len(v) == 1: continue
rep = UOp(v[0].op, src=tuple([k] + [y for x in v for y in x.src[1:]]), arg=x[0].arg)
rep = UOp(v[0].op, src=tuple([k] + [y for x in v for y in x.src[1:]]), arg=v[0].arg)
for x in v: replaces[x] = rep
if not len(replaces) and not len(dangling_ifs): return None
ret = s.substitute(replaces)
+2
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@@ -170,6 +170,8 @@ SPEC = ContextVar("SPEC", 0)
# TODO: disable by default due to speed
IGNORE_OOB = ContextVar("IGNORE_OOB", 1)
PCONTIG = ContextVar("PCONTIG", 0) # partial contiguous in rangeify
MULTIOUTPUT = ContextVar("MULTIOUTPUT", 0)
DEBUG_RANGEIFY = ContextVar("DEBUG_RANGEIFY", 0)
@dataclass(frozen=True)
class Metadata:
+26 -2
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@@ -1,10 +1,10 @@
from typing import Iterator
from typing import Iterator, cast
import functools, operator, 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.symbolic import symbolic, pm_simplify_valid, pm_drop_and_clauses
from tinygrad.helpers import argsort, all_same, cpu_profile, PCONTIG, colored
from tinygrad.helpers import argsort, all_same, cpu_profile, PCONTIG, colored, MULTIOUTPUT
ALWAYS_CONTIGUOUS: set[Ops] = {Ops.CONTIGUOUS, Ops.ASSIGN, Ops.COPY, Ops.BUFFER, Ops.BUFFER_VIEW,
Ops.CONST, Ops.BIND, Ops.DEVICE, Ops.MSELECT, Ops.MSTACK, Ops.DEFINE_GLOBAL,
@@ -141,6 +141,7 @@ def apply_movement_op(op:Ops, in_shape:tuple[sint,...], arg:tuple, rngs:tuple[UO
@profile_matches
def run_rangeify(tsink:UOp, debug:bool=False) -> tuple[UOp, IndexingContext]:
if debug: print("**************************")
rctx = IndexingContext()
# get ops to realize
@@ -252,5 +253,28 @@ def run_rangeify(tsink:UOp, debug:bool=False) -> tuple[UOp, IndexingContext]:
# assign to the range map. rngs are the input ranges, out_rngs are the output ranges, from the x op.
rctx.range_map[x] = (rngs, out_rngs)
if MULTIOUTPUT:
# second forward pass to fuse children
replaced_ranges = {}
for x in tsink.toposort():
if x not in rctx.realize_map: continue
out_rngs = rctx.range_map[x][1]
_realize_axis = cast(list[int], rctx.realize_map[x])
consumers = [rctx.range_map[u][0] for u in consumer_map[x] if u in rctx.range_map]
if len(consumers) < 2: continue
assert all(len(out_rngs) == len(rr) for rr in consumers)
for i,c in enumerate(zip(*consumers)):
out_rng = out_rngs[i]
# check if they are all simple ranges
if not all(y.op is Ops.RANGE and y.vmax == out_rng.vmax for y in c): continue
for r in c: replaced_ranges[r] = out_rngs[i]
_realize_axis.remove(i)
if len(_realize_axis) == 0: del rctx.realize_map[x]
else: rctx.realize_map[x] = _realize_axis
# do all the replaces
for k,(v0,v1) in rctx.range_map.items():
rctx.range_map[k] = (tuple(x.substitute(replaced_ranges) for x in v0), tuple(x.substitute(replaced_ranges) for x in v1))
tsink = graph_rewrite(tsink, pm_apply_rangeify, ctx=rctx, bottom_up=True, name="apply rangeify")
return tsink, rctx
+5 -2
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@@ -4,9 +4,11 @@ from tinygrad.dtype import dtypes, PtrDType, ImageDType, AddrSpace
from tinygrad.uop.ops import PatternMatcher, UPat, Ops, UOp, resolve, GroupOp, _substitute, ssimplify, KernelInfo
from tinygrad.uop.ops import track_rewrites, graph_rewrite, identity_element, sint, AxisType, BottomUpGate
from tinygrad.uop.symbolic import symbolic_flat
from tinygrad.helpers import argsort, prod, all_same, pluralize, getenv, flatten, dedup, all_int, DEBUG, SPLIT_REDUCEOP, Metadata
from tinygrad.helpers import argsort, prod, all_same, pluralize, getenv, flatten, dedup, all_int, DEBUG, SPLIT_REDUCEOP, \
Metadata, DEBUG_RANGEIFY, MULTIOUTPUT
from tinygrad.codegen.simplify import pm_flatten_range, pm_reduce_unparented
from tinygrad.codegen.opt import Opt
from tinygrad.codegen.late.control_flow import pm_merge_ends
from tinygrad.schedule.indexing import run_rangeify, BufferizeOpts, ALWAYS_CONTIGUOUS, IndexingContext, apply_movement_op
# creation can recurse a lot
@@ -477,7 +479,7 @@ def get_rangeify_map(sink:UOp) -> dict[UOp, UOp]:
tsink = graph_rewrite(tsink, earliest_rewrites+replace_contiguous, ctx={}, name="earliest rewrites")
# convert movement ops to ranges
tsink, rctx = run_rangeify(tsink, getenv("DEBUG_RANGEIFY", 0))
tsink, rctx = run_rangeify(tsink, DEBUG_RANGEIFY)
# NOTE: sym (vs symbolic_simple) breaks things here because ranges with len 1 aren't handled right
tsink = graph_rewrite(tsink, symbolic_flat+pm_reduce_unparented, name="symbolic") # this supports const folding
@@ -494,6 +496,7 @@ def get_rangeify_map(sink:UOp) -> dict[UOp, UOp]:
# bufferize -> store
tsink = graph_rewrite(tsink, pm_add_buffers, bottom_up=True, name="bufferize to store")
if MULTIOUTPUT: tsink = graph_rewrite(tsink, pm_merge_ends, name="merge end ranges")
tsink = graph_rewrite(tsink, split_kernels, ctx=uop_list, 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
+3 -1
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@@ -362,7 +362,9 @@ class UOp(MathTrait, metaclass=UOpMetaClass):
def load(self, *src:UOp, **kwargs): return UOp(Ops.LOAD, dtype=kwargs.pop("dtype", self.dtype.base), src=(self,)+src, **kwargs)
def store(self, *src:UOp, **kwargs): return UOp(Ops.STORE, kwargs.pop("dtype", dtypes.void), (self,)+src, **kwargs)
def end(self, *src:UOp, ends:Sequence[UOp]):
if len(ends) == 0: return self
if len(ends) == 0:
if len(src): return UOp(Ops.NOOP, src=(self,*src))
return self
return UOp(Ops.END, src=(*ends, self, *src), arg=len(ends))
def after(self, *src:UOp): return UOp(Ops.AFTER, self.dtype, (self,)+src)
def assign(self, x:UOp): return UOp(Ops.ASSIGN, self.dtype, (self, x))