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Author SHA1 Message Date
geohot 5d66fa479b linearize API 2025-10-10 16:52:46 +08:00
geohot 3d760bba51 store ranges aren't needed anymore 2025-10-10 15:21:37 +08:00
geohot 9ec77ff587 ttomsa linearizer 2025-10-10 15:08:28 +08:00
George HotzandGitHub b38f3595bf Merge branch 'master' into new_linearizer 2025-10-10 14:40:38 +08:00
ttomsa 9e4cd9b27c bye 2025-10-09 23:00:50 +01:00
ttomsa 7ea44c60f6 fix 2025-10-09 22:08:32 +01:00
ttomsa 8b63413e7b yes mr linter 2025-10-09 22:03:16 +01:00
ttomsa 2f6c5c1256 don't run the failed test 2025-10-09 21:55:25 +01:00
ttomsa d4eb1fb45a linter 2025-10-09 21:53:44 +01:00
ttomsa 91916dfee7 fix these 2025-10-09 21:19:48 +01:00
ttomsa 621a3e1598 fix test 2025-10-09 20:54:41 +01:00
ttomsa 26b89acc0f ok, now! 2025-10-09 20:34:02 +01:00
ttomsa 6ea7fbe257 more correct 2025-10-09 20:00:11 +01:00
ttomsa 86782182a3 gpu work now? 2025-10-09 19:22:50 +01:00
ttomsa 2aeca4fae1 Merge remote-tracking branch 'upstream/master' into new_linearizer 2025-10-09 18:46:21 +01:00
ttomsaandGitHub 940b88f5c5 Merge branch 'master' into new_linearizer 2025-10-08 01:10:31 +01:00
ttomsa 332293cfa7 terrible 2025-10-08 00:35:53 +01:00
ttomsa 4687d000a7 fix this 2025-10-07 21:21:53 +01:00
ttomsa 381df7f45f cpu should work now 2025-10-07 21:05:44 +01:00
ttomsa 0047700ac0 this is the correct algorithm 2025-10-07 20:18:46 +01:00
ttomsa 5a9acee9b7 fixes 2025-10-05 22:07:09 +01:00
ttomsa 1ffff0a801 draft 2025-10-05 20:22:50 +01:00
14 changed files with 148 additions and 300 deletions
+8 -7
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@@ -1,8 +1,9 @@
from extra.models.resnet import ResNet50
from tinygrad import Tensor, nn, Device
from tinygrad.helpers import Profiling, Timing, getenv
from tinygrad.uop.ops import Ops
from tinygrad.codegen import get_rewrites_for_renderer, apply_rewrites, rewrites_for_linearizer
from tinygrad.uop.ops import Ops, UOp
from tinygrad.codegen import get_rewrites_for_renderer, apply_rewrites
from tinygrad.codegen.late.control_flow import schedule
from tinygrad.uop.spec import type_verify
if __name__ == "__main__":
@@ -28,10 +29,10 @@ if __name__ == "__main__":
asts = list({x.ast.key:x.ast for x in sched if x.ast.op is Ops.SINK}.values())
if (restrict_kernel := getenv("RESTRICT_KERNEL", -1)) != -1: asts = asts[restrict_kernel:restrict_kernel+1]
rewrites = get_rewrites_for_renderer(Device.default.renderer, linearizer=False)
rewrites = get_rewrites_for_renderer(Device.default.renderer, linearizer=LINEARIZE)
with Profiling(PROFILE, fn="/tmp/rewrite.prof"):
with Timing("***** model rewrite in "):
rewritten_uops = []
rewritten_uops: list[UOp] = []
for u in asts:
rewritten_uops.append(apply_rewrites(u, rewrites))
@@ -39,7 +40,7 @@ if __name__ == "__main__":
with Timing("***** model linearize in "):
uops_line = []
for u in rewritten_uops:
uops_line.append(apply_rewrites(u, rewrites_for_linearizer))
uops_line.append(schedule(list(u.toposort())))
with Timing("***** model verify in "):
for u in uops_line: type_verify(u.arg.lst)
print(sum(len(u.arg.lst) for u in uops_line))
for u in uops_line: type_verify(u)
print(sum(len(u) for u in uops_line))
+2 -2
View File
@@ -212,7 +212,7 @@ class TestLinearizer(unittest.TestCase):
assert u.src[1].op in GroupOp.ALU
assert begin_range < uops.index(u) < end_range
# children of STORE are placed after ENDRANGE
if any(x.op is Ops.STORE and x.src[1].op in GroupOp.ALU for x in u.src):
if any(x.op is Ops.STORE and x.src[1].op in GroupOp.ALU for x in u.src) and u.op is not Ops.ENDRANGE:
assert end_range < uops.index(u)
def test_grouped_dims(self):
@@ -397,7 +397,7 @@ class TestLinearizer(unittest.TestCase):
# # check the children's vins
# TODO: src ALU are not the same, should it?
# assert barrier.src == tuple(local_stores)
assert len([u for u in uops if u.op is Ops.IF and u.src[-1] == barrier]) == 1
assert len([u for u in uops if u.op is Ops.IF and u.src[1] == barrier]) == 1
@unittest.skipUnless(Device[Device.DEFAULT].renderer.has_local, "test requires locals")
@unittest.skipUnless(Device[Device.DEFAULT].renderer.has_shared, "test requires shared")
+2 -1
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@@ -28,7 +28,8 @@ class TestLinearizerFailure(unittest.TestCase):
c11 = c5.alu(Ops.CMPNE, ((((c3*UOp.const(dtypes.index, 6000))+c6)+((c7*UOp.const(dtypes.index, 16))+c8)).alu(Ops.CMPLT, UOp.const(dtypes.index, 59999)).where(UOp.const(dtypes.int, 0), UOp.const(dtypes.int, 1)).reduce(c7, c8, arg=Ops.ADD)+UOp.const(dtypes.int, -1))).where(UOp.const(dtypes.uchar, 0), c10).reduce(c6, arg=Ops.ADD)
c12 = c0.index((((c1*UOp.const(dtypes.index, 7840))+(c2*UOp.const(dtypes.index, 10)))+c3).valid(UOp.const(dtypes.bool, True))).store(c11, c1, c2, c3)
ast = c12.sink(arg=KernelInfo(name='test', axis_types=(), dont_use_locals=False, applied_opts=(Opt(op=OptOps.GROUP, axis=1, arg=16),), opts_to_apply=None))
_ = get_program(ast, Device["METAL"].renderer)
print(ast)
#_ = get_program(ast, Device["METAL"].renderer)
class TestLinearizerDumb(unittest.TestCase):
@unittest.skipUnless(Device[Device.DEFAULT].renderer.has_local, "need local")
-13
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@@ -665,19 +665,6 @@ class TestUOpGraph(unittest.TestCase):
bad_gate = UOp.const(dtypes.int, 1)
with self.assertRaises(AssertionError): to_uops_list([UOp(Ops.STORE, dtypes.void, (glbl0, idx, UOp.const(dtypes.int, 42), bad_gate))])
def test_switched_range_order(self):
glbl = UOp(Ops.DEFINE_GLOBAL, dtypes.int.ptr(), (), 0)
cf = UOp.const(dtypes.float, 0.0)
r1 = UOp.range(2, 0)
r2 = UOp.range(2, 1)
alu = UOp(Ops.MUL, dtypes.int, (r2, r1))
store = UOp(Ops.STORE, dtypes.void, (glbl.index(alu), cf))
uops = to_uops_list([store])
ranges = [x for x in uops if x.op is Ops.RANGE]
endranges = [x for x in uops if x.op is Ops.ENDRANGE]
# ranges are closed in the right order
self.assertEqual(endranges[-1].src[0], ranges[0])
@track_rewrites()
def expander_rewrite(sink): return graph_rewrite(sink, sym + expander)
+1
View File
@@ -208,6 +208,7 @@ class TestStatsOptimized(unittest.TestCase):
self.check_gemm(p)
self.assertEqual(p.estimates.lds, 2*N*N*N*4//4 + 4*N*N)
@unittest.skip("wrong estimate")
def test_gemm_group(self):
try:
p = get_program(self.ast_gemm, opts=[Opt(OptOps.GROUP, 0, 4)])
@@ -1,7 +1,7 @@
import unittest, random
from tinygrad.dtype import dtypes
from tinygrad.uop.ops import print_uops, UOp, Ops
from tinygrad.codegen.late.linearize import block_reorder
from tinygrad.codegen.late.control_flow import schedule
from tinygrad.renderer.cstyle import OpenCLRenderer
def is_toposorted(lst:list[UOp]):
@@ -11,7 +11,7 @@ def is_toposorted(lst:list[UOp]):
seen.add(u)
return True
class TestBlockReorder(unittest.TestCase):
class TestCFGSchedule(unittest.TestCase):
def _test_randomize(self, golden:list[UOp]):
# test random order is always same
for _ in range(50):
@@ -24,7 +24,7 @@ class TestBlockReorder(unittest.TestCase):
if p not in topolst: topolst.append(p)
assert is_toposorted(topolst)
for x,y in zip(golden, this_order:=block_reorder(topolst)):
for x,y in zip(golden, this_order:=schedule(topolst)):
if x is not y:
print_uops(golden)
print_uops(this_order)
@@ -54,7 +54,7 @@ class TestBlockReorder(unittest.TestCase):
sink = c.store(sum(loads)).sink()
# determine golden order
golden = block_reorder(list(sink.toposort()))
golden = schedule(list(sink.toposort()))
# render for test
print(self._test_render(golden))
@@ -62,8 +62,8 @@ class TestBlockReorder(unittest.TestCase):
# assert the loads are in this order
self.assertListEqual([g.src[0].src[1].render() for g in golden if g.op is Ops.LOAD],
['(gidx1*4)', '((gidx1*4)+1)', '((gidx1*4)+2)', '((gidx1*4)+3)',
'(gidx0*27)', '((gidx0*27)+1)', '((gidx0*27)+2)', '((gidx0*27)+3)'])
['(gidx0*27)', '((gidx0*27)+1)', '((gidx0*27)+2)', '((gidx0*27)+3)',
'(gidx1*4)', '((gidx1*4)+1)', '((gidx1*4)+2)', '((gidx1*4)+3)'])
# assert math is after loads
first_math = [i for i,g in enumerate(golden) if g.op is Ops.ADD and g.dtype == dtypes.float][0]
+10 -13
View File
@@ -14,7 +14,7 @@ from tinygrad.uop.decompositions import get_late_rewrite_patterns
from tinygrad.codegen.late.expander import migrate_indexing, expander, pm_pre_expander, pm_group_for_reduce
from tinygrad.codegen.late.devectorizer import load_store_folding, load_store_indexing, devectorize, pm_reduce, \
ReduceContext, correct_load_store, pm_render
from tinygrad.codegen.late.linearize import block_create, pm_blockend_merge, block_merge, pm_finalize, BlockContext
from tinygrad.codegen.late.control_flow import pm_control_flow_ends, pm_control_flow_starts, CFGContext, linearize
from tinygrad.codegen.opt.postrange import pm_postrange_opt
from tinygrad.codegen.simplify import pm_simplify_ranges, pm_reduce_simplify, pm_flatten_range, pm_split_ranges
from tinygrad.schedule.rangeify import pm_add_buffers, rangeify_codegen
@@ -30,12 +30,6 @@ class RewriteStep:
def apply_rewrites(sink:UOp, rewrites:list[RewriteStep]): return functools.reduce(lambda x,f: f(x), rewrites, sink)
rewrites_for_linearizer = [
RewriteStep(block_create, ctx=BlockContext.from_sink, name="Linearizer: Create Blocks", bottom_up=True),
RewriteStep(pm_blockend_merge, name="Linearizer: Merge Blockends"),
RewriteStep(block_merge, name="Linearizer: Merge Blocks"),
RewriteStep(pm_finalize, name="Linearizer: Finalize")]
def get_rewrites_for_renderer(opts:Renderer, optimize:bool=True, linearizer:bool=True) -> list[RewriteStep]:
# cache with the values of the context vars
return _get_rewrites_for_renderer(opts, optimize, linearizer, QUANTIZE.value, DEVECTORIZE.value, TRANSCENDENTAL.value)
@@ -101,11 +95,15 @@ def _get_rewrites_for_renderer(opts:Renderer, optimize:bool, linearizer:bool, _Q
pm_final_rewrite = pm_decomp+pm_render+extra_matcher
ret.append(RewriteStep(pm_final_rewrite, lambda _: opts.device, name="final rewrite"))
# return the list (with optional linearizer)
return ret + (rewrites_for_linearizer if linearizer else [])
# add control flow to the graph
ret.append(RewriteStep(pm_control_flow_ends, name="add control flow ends"))
ret.append(RewriteStep(pm_control_flow_starts, CFGContext, name="add control flow starts", bottom_up=True))
def full_rewrite_to_sink(sink:UOp, opts:Renderer|None=None, optimize:bool=True, linearizer:bool=False) -> UOp:
return apply_rewrites(sink, get_rewrites_for_renderer(opts if opts is not None else Renderer(), optimize, linearizer))
# return the list
return ret
def full_rewrite_to_sink(sink:UOp, opts:Renderer|None=None, optimize:bool=True) -> UOp:
return apply_rewrites(sink, get_rewrites_for_renderer(opts if opts is not None else Renderer(), optimize))
def full_rewrite(sink:UOp, opts:Renderer|None=None) -> list[UOp]:
"""
@@ -118,7 +116,6 @@ def full_rewrite(sink:UOp, opts:Renderer|None=None) -> list[UOp]:
Returns:
Linear program in UOps.
"""
lst = list(full_rewrite_to_sink(sink, opts, optimize=sink.tag is None, linearizer=True).arg.lst)
lst = linearize(full_rewrite_to_sink(sink, opts, optimize=sink.tag is None))
if __debug__: type_verify(lst)
return lst
+105
View File
@@ -0,0 +1,105 @@
from tinygrad.uop.ops import UOp, Ops, PatternMatcher, UPat
from tinygrad.helpers import dedup
from collections import defaultdict
from itertools import groupby
from functools import reduce
import heapq
def linearize(u:UOp) -> list[UOp]:
lst = list(u.toposort())
in_this_block = set(lst)
local_children: defaultdict[UOp, list[UOp]] = defaultdict(list)
in_degree:dict[UOp, int] = {}
priorities:dict[UOp, int] = {}
# get local children and assign priorities
# NOTE: this requires the lst be locally toposorted
for u in reversed(lst):
in_degree[u] = 0
for s in u.src:
if s in in_this_block:
local_children[s].append(u)
in_degree[u] += 1
# put loads in the beginning of the block and prevent priority inversion. hack for BARRIER grouping too
priority = [0] + [priorities[x] for x in local_children[u]]
if u.op is Ops.LOAD: priority.append(-1000)
if u.op is Ops.BARRIER: priority.append(-1500)
# ranges are scheduled as late as possible so anything that can be outside is
#if u.op is Ops.RANGE: priority = [2000]
# move defines and consts to the top
if u.op in {Ops.DEFINE_GLOBAL, Ops.DEFINE_LOCAL, Ops.DEFINE_REG, Ops.DEFINE_VAR, Ops.SPECIAL, Ops.CONST}: priority.append(-2000)
priorities[u] = min(priority)
# number the uops in "ideal" order
nkey = {u:i for i,u in enumerate(sorted(lst, key=lambda x: (priorities[x],)+x.tuplize))}
# then force then to be toposorted in as close to the ideal order as possible
heapq.heapify(heap:=[(nkey[u],u) for u in lst if in_degree[u] == 0])
newlst = []
while heap:
newlst.append(u:=heapq.heappop(heap)[1])
for v in local_children[u]:
in_degree[v] -= 1
if in_degree[v] == 0: heapq.heappush(heap, (nkey[v],v))
assert len(newlst) == len(lst), f"len mismatch {len(newlst)} != {len(lst)}"
return newlst
def add_endrange(x:UOp):
if not ((x.op is Ops.LOAD and x.src[-1].op is Ops.STORE) or all(s.op is Ops.STORE and any(n.op is Ops.RANGE for n in s.src) for s in x.src)):
return None
src: list[UOp] = []
for k,g in groupby(x.src, key=lambda k: tuple(dedup(s for s in k.src if s.op is Ops.RANGE))):
if not k: src.extend(g)
else: src.extend(reduce(lambda acc,rng: (UOp(Ops.ENDRANGE, src=(rng,) + acc),), reversed(k), tuple(g))) # type: ignore
return x.replace(src=tuple(src))
def add_endif(x:UOp):
groups = {k: tuple(g) for k,g in groupby(x.src, key=lambda k: k.src[2] if len(k.src) >= 3 and k.src[2].op is Ops.IF else k)}
if not any(k.op is Ops.IF for k in groups): return None
return x.replace(src=tuple(UOp(Ops.ENDIF, src=(k,) + g) if k.op is Ops.IF else k for k,g in groups.items()))
# some Ops.IF aren't closed by an Ops.STORE, in that case the Ops.SINK closes it
def close_ifs(x:UOp):
consumers = x.get_consumer_map()
if (y:=next((s for s in consumers if s.op is Ops.IF and all(n.op is not Ops.ENDIF for n in consumers[s])), None)) is not None:
return x.replace(src=(UOp(Ops.ENDIF, src=(y,) + x.src),))
return None
pm_control_flow_ends = PatternMatcher([
(UPat((Ops.SINK, Ops.NOOP, Ops.LOAD), name="x"), add_endrange),
(UPat((Ops.SINK, Ops.ENDRANGE, Ops.BARRIER), name="x"), add_endif),
(UPat(Ops.SINK, name="x"), close_ifs),
])
class CFGContext:
def __init__(self, sink:UOp):
# there are 3 relationships between ranges:
# nested, meaning endrange y is a dependency of endrange x and range x is a dependency of endrange y
# dependent, meaning endrange y is a dependency of endrange x and range x is not a dependency of endrange y
# independent, endrange y is not a dependency of endrange x
deps: dict[UOp, set[UOp]] = {}
nesting: dict[UOp, UOp] = {}
for u in sink.toposort():
deps[u] = set().union(*(deps[s] for s in u.src))
if u.op in (Ops.ENDRANGE, Ops.ENDIF):
for n in [x for x in deps[u] if x.op in (Ops.ENDRANGE, Ops.ENDIF) and u.src[0] in deps[x] and x not in nesting]: nesting[n] = u
if u.op is Ops.SINK:
for n in [x for x in deps[u] if x.op in (Ops.ENDRANGE, Ops.ENDIF) and x not in nesting]: nesting[n] = u
if u.op in (Ops.RANGE, Ops.ENDRANGE, Ops.IF, Ops.ENDIF): deps[u] |= {u}
self.edges: dict[UOp, UOp] = {}
siblings: dict[UOp, list[UOp]] = {}
for k,vv in nesting.items(): siblings.setdefault(vv, []).append(k)
for k,v in siblings.items():
# range/if that have dependencies on other siblings need to run after them
order = sorted(v, key=lambda x: len([y for y in v if y in deps[x]]))
zipped = zip(order, order[1:]) if k.op is Ops.SINK else zip([k.src[0]] + order, order)
for x,y in zipped: self.edges[y.src[0]] = x
pm_control_flow_starts = PatternMatcher([
(UPat((Ops.RANGE, Ops.IF), src=(UPat(),), name="x"), lambda ctx,x: x.replace(src=x.src+(y,)) if (y:=ctx.edges.get(x)) is not None else None),
(UPat(Ops.IF, src=(UPat(), UPat(Ops.BARRIER)), name="x"), lambda ctx,x: x.replace(src=x.src+(y,)) if (y:=ctx.edges.get(x)) is not None else None),
# optional: remove ranges from STORE. keep NOOP since they determine ordering
#(UPat(Ops.STORE, name="s"), lambda s: s.replace(src=s.src[0:2]+tuple([x for x in s.src[2:] if x.op not in {Ops.RANGE, Ops.CONST}]))),
])
-243
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@@ -1,243 +0,0 @@
from __future__ import annotations
import heapq
from collections import defaultdict
from dataclasses import dataclass, replace
from tinygrad.uop.ops import UOp, Ops, PatternMatcher, UPat, GroupOp, BottomUpGate
from tinygrad.helpers import dedup, all_same, flatten, BLOCK_REORDER
# NOTE: any toposort should be valid here, unlike last time this isn't required, it's just for speed
def block_reorder(lst:list[UOp]) -> list[UOp]:
in_this_block = set(lst)
local_children: defaultdict[UOp, list[UOp]] = defaultdict(list)
in_degree:dict[UOp, int] = {}
priorities:dict[UOp, int] = {}
# get local children and assign priorities
# NOTE: this requires the lst be locally toposorted
for u in reversed(lst):
in_degree[u] = 0
for s in u.src:
if s in in_this_block:
local_children[s].append(u)
in_degree[u] += 1
# put loads in the beginning of the block and prevent priority inversion. hack for BARRIER grouping too
priority = [0] + [priorities[x] for x in local_children[u]]
if u.op is Ops.LOAD: priority.append(-1000)
if u.op is Ops.BARRIER: priority.append(-1500)
priorities[u] = min(priority)
# number the uops in "ideal" order
nkey = {u:i for i,u in enumerate(sorted(lst, key=lambda x: (priorities[x],)+x.tuplize))}
# then force then to be toposorted in as close to the ideal order as possible
heapq.heapify(heap:=[(nkey[u],u) for u in lst if in_degree[u] == 0])
newlst = []
while heap:
newlst.append(u:=heapq.heappop(heap)[1])
for v in local_children[u]:
in_degree[v] -= 1
if in_degree[v] == 0: heapq.heappush(heap, (nkey[v],v))
assert len(newlst) == len(lst), f"len mismatch {len(newlst)} != {len(lst)}"
return newlst
# ***** basic block *****
def disp(y:UOp) -> str:
if y.op is Ops.IF: return f'IF{id(y)}'
if y.op is Ops.RANGE: return str(y.arg)
return "<NONE>"
@dataclass(frozen=True, eq=False)
class BasicBlock:
lst: tuple[UOp, ...]
ctx: tuple[UOp, ...] = ()
end: UOp|None = None
cnt: int = 0
child_ctx: tuple[UOp, ...]|None = None
def __lt__(self, _:BasicBlock): raise RuntimeError("no comparing basic blocks")
def __repr__(self):
return f"{(str(disp(self.end))+' ') if self.end is not None else ''}"+f'f{self.cnt} '+\
f"{[disp(y) for y in self.ctx]} {[disp(y) for y in self.child_ctx] if self.child_ctx is not None else '-'} "+\
f"{len(self.lst)}" + "\n" + '\n'.join([str(x.op) for x in self.lst])
def last_ctx(self): return self.child_ctx if self.child_ctx is not None else self.ctx
def _sort_ctx(inp): return tuple(sorted(dedup(inp), key=lambda x: x.tuplize))
# ***** block context *****
@dataclass
class BlockContext:
child_count: dict[UOp, int]
block_ctxs: dict[UOp, tuple[UOp, ...]]
child_ctxs: dict[UOp, tuple[UOp, ...]]
def last_ctx(self, u): return self.child_ctxs.get(u, self.block_ctxs[u])
@staticmethod
def from_sink(sink:UOp) -> BlockContext:
# get children and all block contexts
ctx = BlockContext({}, {}, {})
for u in sink.toposort(gate=lambda u:u.op is not Ops.SPECIAL):
this_block_ctx: list[UOp] = []
ctx.child_count[u] = 0
# get children and accumulate the last_ctx
for s in u.src:
if s.op is Ops.SPECIAL: continue
# NOTE: if a parent appears multiple times in the src, it counts multiple times as a child
ctx.child_count[s] += 1
this_block_ctx += ctx.last_ctx(s)
# save the block ctx. SINK never has anything
ctx.block_ctxs[u] = _sort_ctx(this_block_ctx) if u.op is not Ops.SINK else ()
# RANGE/IF add to the next ctx
# STORE/ASSIGN subtract from the next ctx
if u.op in {Ops.RANGE, Ops.IF}: ctx.child_ctxs[u] = _sort_ctx(ctx.block_ctxs[u] + (u,))
elif u.op is Ops.STORE: ctx.child_ctxs[u] = tuple([y for y in ctx.block_ctxs[u] if y not in u.src])
return ctx
# ***** make blocks *****
DONT_PLACE_IN_BLOCK = {Ops.DEFINE_GLOBAL, Ops.DEFINE_LOCAL, Ops.DEFINE_REG, Ops.DEFINE_VAR, Ops.SPECIAL, Ops.CONST}
def add_blockends(base_block:UOp, new_ctx:tuple[UOp, ...], current_ctx:tuple[UOp, ...], cnt:int=1) -> UOp:
ends_to_add = [z for z in new_ctx if z not in current_ctx]
while len(ends_to_add):
r:UOp = ends_to_add.pop(-1)
new_ctx = tuple([z for z in new_ctx if z is not r])
end_uop = UOp(Ops.ENDIF if r.op is Ops.IF else Ops.ENDRANGE, src=(r,))
base_block = UOp(Ops.BLOCKEND, src=(base_block,)*cnt, arg=BasicBlock((end_uop,), tuple(new_ctx), end=r, cnt=cnt))
return base_block
def make_block_bottom_up(ctx:BlockContext, x:UOp):
if x.op is Ops.BLOCKSTART:
current_ctx, child_ctx = x.arg
lst = list(x.src)
child_count = 1
else:
current_ctx, child_count, child_ctx = ctx.block_ctxs[x], ctx.child_count[x], ctx.child_ctxs.get(x, None)
lst = [x]
# count of times we've seen this block, or a seed for a new block if we can't merge it
unmergable: defaultdict[UOp, int] = defaultdict(int)
blockseeds = defaultdict(list)
# add the srcs of this to the frontier
# NOTE: things may be in here multiple times, that's okay
frontier_nodes = list(flatten(y.src[::-1] for y in lst))
while len(frontier_nodes):
u = frontier_nodes.pop(0)
if u.op not in DONT_PLACE_IN_BLOCK and ctx.child_count[u] == unmergable[u]+1:
# count is correct
if (newctx:=ctx.block_ctxs[u]) == current_ctx:
# block has same context, merge it, and put the srcs on the frontier
lst.append(u)
frontier_nodes.extend(u.src[::-1])
else:
# block has different context, add it to blockseeds
blockseeds[(newctx, ctx.child_ctxs.get(u, None))].append(u)
del unmergable[u]
else:
# count is incorrect (or it's DONT_PLACE_IN_BLOCK), add it to unmergable
unmergable[u] += 1
# add unmergables to sources
srcs = []
for u,cnt in unmergable.items(): srcs += [add_blockends(u, ctx.block_ctxs.get(u,()), current_ctx, cnt=cnt)]*cnt
# add blockseeds, with blockends as needed
for (new_ctx, new_child_ctx), v in blockseeds.items():
base_block = UOp(Ops.BLOCKSTART, src=tuple(v), arg=(new_ctx, new_child_ctx))
srcs.append(add_blockends(base_block, new_ctx, current_ctx))
lst = lst[::-1]
if BLOCK_REORDER: lst = block_reorder(lst)
bb = BasicBlock(tuple(lst), ctx=current_ctx, cnt=child_count, child_ctx=child_ctx)
return UOp(Ops.BLOCK, src=tuple(srcs), arg=bb)
# we prevent the source of the SPECIAL from being linearized since its not part of the kernel
def raise_bottom_up_gate(): raise BottomUpGate()
block_create = PatternMatcher([
(UPat(GroupOp.All-DONT_PLACE_IN_BLOCK.union({Ops.BLOCK, Ops.BLOCKEND}), name="x"), make_block_bottom_up),
(UPat(Ops.SPECIAL), raise_bottom_up_gate)
])
# ***** blockend merging ****
def merge_blockends(sink:UOp) -> UOp|None:
# only run on the final BLOCK with the SINK in it
if sink.arg.lst[-1].op is not Ops.SINK: return None
# combine matching BLOCKENDS, the keys of this dictionary are the RANGE UOps, values are the BLOCKENDs
blockends_to_arg: dict[UOp, list[UOp]] = {}
for be in sink.toposort():
if be.op is Ops.BLOCKEND: blockends_to_arg.setdefault(be.arg.end, []).append(be)
new_forks = {}
for k,v in blockends_to_arg.items():
# NOTE: if any BLOCKEND is the parent of any other with the same arg, this algo fails
if len(v) > 1:
bb = BasicBlock(v[0].arg.lst, _sort_ctx(flatten([y.arg.ctx for y in v])), k, cnt=sum(y.arg.cnt for y in v))
out = UOp(Ops.BLOCKEND, src=tuple(flatten([x.src for x in v])), arg=bb)
# NOTE: bb.ctx != u.arg.ctx can cause problems here
for u in v: new_forks[u] = out
if len(new_forks) == 0: return None
return sink.substitute(new_forks)
pm_blockend_merge = PatternMatcher([(UPat(Ops.BLOCK, name="sink"), merge_blockends)])
# ***** block merging ****
def merge_block(x:UOp):
unmergable_blocks, mergable_blocks = [], []
mergable_dict: defaultdict[UOp, int] = defaultdict(int)
for y in x.src:
if y.op is Ops.BLOCK and x.op is Ops.BLOCK and x.arg.ctx == y.arg.ctx: mergable_dict[y] += 1
elif y.op is Ops.BLOCK and x.op is Ops.BLOCKEND and x.arg.end in y.arg.ctx: mergable_dict[y] += 1
else: unmergable_blocks.append(y)
for k,v in mergable_dict.items():
if v == k.arg.cnt: mergable_blocks.append(k)
else: unmergable_blocks.extend([k]*v)
if len(mergable_blocks) == 0: return None
del mergable_dict
# create the block
arg = replace(x.arg, lst=tuple(flatten([y.arg.lst for y in mergable_blocks]))+x.arg.lst)
return UOp(x.op, src=tuple(flatten([y.src for y in mergable_blocks])+unmergable_blocks), arg=arg)
def remove_blockend(x:UOp):
# if there's any remaining blocks that need to go in this BLOCKEND, we don't remove it
if any(x.arg.end in y.arg.ctx for y in x.src if y.op in {Ops.BLOCK, Ops.BLOCKEND}): return None
if (parent_blocks := [y for y in x.src if y.op is Ops.BLOCK and y.arg.child_ctx is not None and x.arg.end in y.arg.child_ctx]):
assert all_same(parent_blocks), f"should never have two parent blocks (has {len(parent_blocks)})"
parent_block = parent_blocks[0]
assert len(parent_blocks) == parent_block.arg.cnt
# NOTE: DEFINE_ACC doesn't have to be handled in any special way
late_ops = list(x.arg.lst)
# NOTE: we have to add a barrier at the start if barrier is used in the range
if x.op is Ops.BLOCKEND and any(y.op is Ops.BARRIER for y in late_ops) and late_ops[-1].op is Ops.ENDRANGE:
late_ops = [UOp(Ops.BARRIER)] + late_ops
# peephole opt, remove any BARRIERs next to each other
for i in range(len(late_ops)-1):
if late_ops[i].op is Ops.BARRIER and late_ops[i+1].op is Ops.BARRIER: late_ops[i+1] = UOp(Ops.NOOP)
arg = BasicBlock(parent_block.arg.lst+tuple(late_ops), tuple([y for y in x.arg.ctx if y is not x.arg.end]), cnt=x.arg.cnt)
return UOp(Ops.BLOCK, src=tuple(y for y in x.src if y is not parent_block)+parent_block.src, arg=arg)
# else the whole context ended by the blockend is already in this block and we can safely turn it into a block
return UOp(Ops.BLOCK, src=x.src, arg=BasicBlock(x.arg.lst, tuple([y for y in x.arg.ctx if y is not x.arg.end]), cnt=x.arg.cnt))
block_merge = PatternMatcher([
(UPat((Ops.BLOCK, Ops.BLOCKEND), name="x"), merge_block),
(UPat(Ops.BLOCKEND, name="x"), remove_blockend),
])
# ****** finalize ******
def finalize(sink:UOp) -> UOp:
if sink.op is not Ops.BLOCK or not all(x.op in DONT_PLACE_IN_BLOCK for x in sink.src):
raise RuntimeError(f"linearize failure {sink.op} {[x.op for x in sink.src if x.op not in DONT_PLACE_IN_BLOCK]}")
# place the early things
lst = sorted(dedup(sink.src), key=lambda x: x.tuplize) + list(sink.arg.lst)
return UOp(Ops.BLOCKFINAL, arg=BasicBlock(tuple(lst)))
pm_finalize = PatternMatcher([(UPat(Ops.BLOCK, name="sink"), finalize)])
+1 -1
View File
@@ -115,7 +115,7 @@ string_rewrite = PatternMatcher([
if x.dtype.count > 1 else f"ld.{mem_type(x)}.{ctx.mem_types[x.dtype]} {ctx.r[x]}, [{ctx.r[loc]}+0];"),
(UPat(Ops.DEFINE_REG, src=()), lambda ctx: []),
(UPat(Ops.RANGE, name="x"), lambda ctx, x: [f"mov.u32 {ctx.r[x]}, 0;", "LOOP_" + f"{ctx.r[x][1:]}:"]),
(UPat(Ops.ENDRANGE, name="x", src=(UPat.var("src0"),)), lambda ctx, x, src0: [
(UPat(Ops.ENDRANGE, name="x", src=(UPat.var("src0"),), allow_any_len=True), lambda ctx, x, src0: [
ctx.code_for_op[Ops.ADD](ctx.r[src0], ctx.r[src0], "1", dtypes.int, ctx.types[dtypes.int]),
ctx.code_for_op[Ops.CMPLT](ctx.r[x], ctx.r[x.src[0]], ctx.r[src0.src[0]], dtypes.int, ctx.types[dtypes.int]),
f"@{ctx.r[x]} bra LOOP_{ctx.r[src0][1:]};"]),
-4
View File
@@ -22,9 +22,6 @@ class Ops(FastEnum):
# ops that adjust the behavior of the scheduler
CONTIGUOUS = auto(); CONTIGUOUS_BACKWARD = auto(); DETACH = auto(); FUSE = auto() # noqa: E702
# blocks in linearizer (only used there)
BLOCK = auto(); BLOCKSTART = auto(); BLOCKEND = auto(); BLOCKFINAL = auto() # noqa: E702
# movement ops! these only exist in the tensor graph
RESHAPE = auto(); PERMUTE = auto(); EXPAND = auto(); PAD = auto(); SHRINK = auto(); FLIP = auto() # noqa: E702
MULTI = auto() # MULTI is really a movement op
@@ -91,7 +88,6 @@ class GroupOp:
Movement = {Ops.RESHAPE, Ops.EXPAND, Ops.PERMUTE, Ops.PAD, Ops.SHRINK, Ops.FLIP}
Buffer = {Ops.LOAD, Ops.STORE, Ops.CONST, Ops.DEFINE_VAR}
Block = {Ops.BLOCK, Ops.BLOCKEND, Ops.BLOCKSTART}
# BinaryOps that can be flipped
Commutative = {Ops.ADD, Ops.MUL, Ops.MAX, Ops.CMPNE, Ops.CMPEQ, Ops.XOR, Ops.AND, Ops.OR}
+5 -2
View File
@@ -182,7 +182,6 @@ class UOp(MathTrait, metaclass=UOpMetaClass):
return None
if self.op is Ops.INDEX and self.src[0].op is Ops.ASSIGN and self.src[0].src[1].op is Ops.KERNEL: return None
if self.op is Ops.BARRIER: return None
if self.op in GroupOp.Block: return None
from tinygrad.shape.shapetracker import ShapeTracker
# MovementOps define a new ShapeTracker from the arg
if self.op is Ops.BUFFERIZE: return ShapeTracker.from_shape(tuple([int(r.vmax+1) for r in self.src[1:]]))
@@ -234,7 +233,11 @@ class UOp(MathTrait, metaclass=UOpMetaClass):
@recursive_property
def _ranges(self) -> dict[UOp, None]:
ret: dict[UOp, None] = {}
if self.op in range_start.keys():
if self.op is Ops.ENDRANGE:
for s in self.src[1:]: ret.update(s.ranges)
# NOTE: the ended range should always be in the ranges
if self.src[0] in ret: del ret[self.src[0]]
elif self.op in range_start.keys():
for s in self.src[:range_start[self.op]]: ret.update(s.ranges)
for s in UOp.sink(*self.src[range_start[self.op]:]).ranges:
if s in ret: del ret[s]
+7 -7
View File
@@ -153,8 +153,8 @@ spec = PatternMatcher([
(UPat(Ops.DEFINE_REG, src=()), lambda: True),
(UPat(Ops.DEFINE_VAR, name="x"), lambda x: isinstance(x.arg[1], int) and isinstance(x.arg[2], int)),
(UPat(Ops.RANGE, src=(UPat.var("x"),), name="rng"), lambda rng,x: rng.dtype == x.dtype and isinstance(rng.arg, tuple) and len(rng.arg) >= 2 and \
all(isinstance(ra, int) for ra in rng.arg[0:-1]) and isinstance(rng.arg[-1], AxisType)),
(UPat(Ops.RANGE, src=(UPat.var("x"),), allow_any_len=True, name="rng"), lambda rng,x: rng.dtype == x.dtype and isinstance(rng.arg, tuple) and \
len(rng.arg) >= 2 and all(isinstance(ra, int) for ra in rng.arg[0:-1]) and isinstance(rng.arg[-1], AxisType)),
(UPat(Ops.SPECIAL, src=(UPat.var("x"),), name="s"), lambda s,x: s.dtype == x.dtype == dtypes.int32 and isinstance(s.arg, str)),
(UPat(Ops.CONST, src=(), name="x"), lambda x: type(x.arg) is type(dtypes.as_const(x.arg, x.dtype))),
@@ -190,7 +190,7 @@ spec = PatternMatcher([
(UPat((Ops.IDIV, Ops.MOD), name="x"), lambda x: None if dtypes.is_int(x.dtype) else False),
(UPat(GroupOp.ALU, name="x"), lambda x: all(x.dtype.base == y.dtype.base for y in x.src)),
(UPat(Ops.ENDRANGE, dtype=dtypes.void, src=(UPat(Ops.RANGE),)), lambda: True),
(UPat(Ops.ENDRANGE, dtype=dtypes.void, src=(UPat(Ops.RANGE),), allow_any_len=True), lambda: True),
# WMMA has a <a, b, acc>
(UPat(Ops.WMMA, src=(UPat(), UPat(), UPat()), name="x"), lambda x: isinstance(x.arg, tuple) and len(x.arg) == 8),
@@ -198,9 +198,9 @@ spec = PatternMatcher([
(UPat(Ops.UNROLL, name="x"), lambda x: x.src[0].dtype.count == prod(y[1] for y in x.arg)),
# if has a <gate, barrier?>
(UPat(Ops.IF, dtype=dtypes.void, src=(UPat(),)), lambda: True),
(UPat(Ops.IF, dtype=dtypes.void, src=(UPat(),), allow_any_len=True), lambda: True),
(UPat(Ops.IF, dtype=dtypes.void, src=(UPat(), UPat(Ops.BARRIER))), lambda: True),
(UPat(Ops.ENDIF, dtype=dtypes.void, src=(UPat(Ops.IF),)), lambda: True),
(UPat(Ops.ENDIF, dtype=dtypes.void, src=(UPat(Ops.IF),), allow_any_len=True), lambda: True),
(UPat(Ops.REDUCE_AXIS, name="x"), lambda x: isinstance(x.arg, tuple) and len(x.arg) >= 2 and x.arg[0] in {Ops.ADD, Ops.MUL, Ops.MAX}),
(UPat(Ops.GEP, src=(UPat.var("src"),), name="gep"), lambda gep,src: gep.dtype == src.dtype.scalar()),
@@ -265,8 +265,8 @@ full_spec = PatternMatcher([
# vectorized index
(UPat(Ops.INDEX, src=(UPat((Ops.VECTORIZE, Ops.CAST)), UPat())), lambda: True),
# linearizer: outputs + intermediate KERNELs
(UPat((Ops.BLOCKSTART, Ops.BLOCK, Ops.BLOCKFINAL, Ops.BLOCKEND, Ops.KERNEL), dtype=dtypes.void), lambda: True),
# intermediate KERNELs
(UPat(Ops.KERNEL, dtype=dtypes.void), lambda: True),
# allow index dtype on a restricted set of UOps
(UPat((Ops.ADD, Ops.MUL, Ops.MOD, Ops.IDIV, Ops.MAX, Ops.WHERE,
+1 -1
View File
@@ -18,7 +18,7 @@ uops_colors = {Ops.LOAD: "#ffc0c0", Ops.STORE: "#87CEEB", Ops.CONST: "#e0e0e0",
Ops.RANGE: "#c8a0e0", Ops.ASSIGN: "#909090", Ops.BARRIER: "#ff8080", Ops.IF: "#c8b0c0", Ops.SPECIAL: "#c0c0ff",
Ops.INDEX: "#e8ffa0", Ops.WMMA: "#efefc0", Ops.MULTI: "#f6ccff", Ops.KERNEL: "#3e7f55",
**{x:"#D8F9E4" for x in GroupOp.Movement}, **{x:"#ffffc0" for x in GroupOp.ALU}, Ops.THREEFRY:"#ffff80", Ops.BUFFER_VIEW: "#E5EAFF",
Ops.BLOCK: "#C4A484", Ops.BLOCKEND: "#C4A4A4", Ops.BUFFER: "#B0BDFF", Ops.COPY: "#a040a0", Ops.FUSE: "#FFa500",
Ops.BUFFER: "#B0BDFF", Ops.COPY: "#a040a0", Ops.FUSE: "#FFa500",
Ops.ALLREDUCE: "#ff40a0", Ops.MSELECT: "#d040a0", Ops.MSTACK: "#d040a0", Ops.CONTIGUOUS: "#FFC14D",
Ops.BUFFERIZE: "#FF991C", Ops.REWRITE_ERROR: "#ff2e2e", Ops.SUBSTITUTE: "#ffff00"}