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do fusion locally (#10095)

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* do fusion locally

* oops, that's the right way

* explicit delete closure
This commit is contained in:
George Hotz
2025-04-28 20:45:37 -04:00
committed by GitHub
parent 3eba3d6ee9
commit eaceafecae
3 changed files with 19 additions and 4 deletions
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9
test/test_softmax_fusion.py
View File

@@ -30,10 +30,10 @@ def single_kernel_softmax(x_in:Tensor, axis=-1, dtype:DTypeLike|None=None) -> Te
def run_one_schedule_item(out): lower_schedule_item(get_single_element(out.schedule())).run()
class TestFuse(unittest.TestCase):
def _test_fuse(self, fxn, *args, atol=1e-7, **kwargs):
def _test_fuse(self, fxn, *args, atol=1e-7, allow_multiple=False, **kwargs):
GlobalCounters.reset()
out_single = fxn(*args, **kwargs).fuse()
run_one_schedule_item(out_single)
if not allow_multiple: run_one_schedule_item(out_single)
np_single = out_single.numpy()
GlobalCounters.reset()
np_multi = fxn(*args, **kwargs).numpy()
@@ -51,6 +51,11 @@ class TestFuse(unittest.TestCase):
a = Tensor.rand(50,50).realize()
self._test_fuse(lambda a: a.softmax(axis=-1), a)
def test_fuse_gemm_softmax(self):
a = Tensor.rand(50,50).realize()
b = Tensor.rand(50,50).realize()
self._test_fuse(lambda a,b: ((a@b).relu()+a).contiguous().softmax(axis=-1), a,b, allow_multiple=True)
@unittest.skipUnless(is_dtype_supported(dtypes.float16, Device.DEFAULT), f"no float16 on {Device.DEFAULT}")
def test_fuse_softmax_dtype(self):
a = Tensor.rand(50,50).realize()

12
tinygrad/engine/grouper.py
View File

@@ -412,6 +412,16 @@ pm_fuse = PatternMatcher([
(UPat(Ops.FUSE, name="x"), lambda x: x.src[0].replace(src=tuple(y.fuse() for y in x.src[0].src))),
])
def do_fusion(x:UOp):
found_contiguous = {}
def gate_contiguous(x):
if is_contiguous:=(x.op is Ops.CONTIGUOUS): found_contiguous[x] = x.replace(src=(UOp(Ops.VIEW, arg=x.st),))
return not is_contiguous
x.toposort(gate=gate_contiguous)
del gate_contiguous
return graph_rewrite(x.substitute(found_contiguous), pm_fuse, name="local fusion").substitute({v:k for k,v in found_contiguous.items()})
do_fuse = PatternMatcher([(UPat(Ops.FUSE, name="x"), do_fusion),])
PROCESS_REPLAY_CAPTURE:dict[str, bytes] = {}
if CAPTURE_PROCESS_REPLAY:
import atexit
@@ -427,7 +437,7 @@ def get_name(becomes_map:dict[UOp, UOp]) -> str:
@track_rewrites(name_fxn=get_name)
def get_becomes_map(big_sink:UOp) -> dict[UOp, UOp]:
# merge_views + simplify
tensor_map = graph_rewrite_map(big_sink, merge_views+sym+replace_contiguous+pm_fuse, ctx={})
tensor_map = graph_rewrite_map(big_sink, do_fuse+merge_views+sym+replace_contiguous, ctx={})
# display the cleaned up tensor graph
if getenv("VIZ"): graph_rewrite(tensor_map[big_sink], PatternMatcher([]), name="View Tensor Graph")

2
tinygrad/viz/serve.py
View File

@@ -14,7 +14,7 @@ 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.VIEW: "#C8F9D4", Ops.MULTI: "#f6ccff", Ops.KERNEL: "#3e7f55", Ops.IGNORE: "#00C000",
**{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.BLOCK: "#C4A484", Ops.BLOCKEND: "#C4A4A4", Ops.BUFFER: "#B0BDFF", Ops.COPY: "#a040a0", Ops.FUSE: "#FFa500"}
# VIZ API