carrot/tinygrad_repo/test/test_winograd.py
Vehicle Researcher 4fca6dec8e openpilot v0.9.8 release
date: 2025-01-29T09:09:56
master commit: 227bb68e1891619b360b89809e6822d50d34228f
2025-01-29 09:09:58 +00:00

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Python

import unittest
from tinygrad import Tensor, GlobalCounters, dtypes
from tinygrad.ops import Ops
from tinygrad.helpers import Timing, CI, Profiling, WINO, DEBUG, getenv
from tinygrad.codegen.kernel import Kernel
class TestWinograd(unittest.TestCase):
def setUp(self):
self.old = WINO.value
WINO.value = 1
def tearDown(self):
WINO.value = self.old
def test_speed(self):
x = Tensor.empty(1,4,9,9)
w = Tensor.empty(4,4,3,3)
with Timing("running conv: "):
out = Tensor.conv2d(x, w)
with Timing("scheduling: "):
sched = out.schedule()
for i,s in enumerate(sched):
if s.ast.op is not Ops.SINK: continue
ops = s.ast.toposort
with Timing(f"linearize {i} with {len(ops):4d} ops: "):
l = Kernel(s.ast)
l.hand_coded_optimizations()
l.linearize()
assert len(l.sts) <= 256 # just the current value to prevent regression
if DEBUG >= 2: print(f"{len(l.sts):4d} shapetrackers with max {max(len(x.views) for x in l.sts)} views")
for st in l.sts:
assert len(st.views) <= 2, "too many views in winograd"
if DEBUG >= 3:
print(f"{len(st.views):3d} views")
for v in st.views: print(v)
def test_profile(self):
x,w = Tensor.rand(1,4,9,9).realize(), Tensor.rand(4,4,3,3).realize()
with Profiling(enabled=not CI, sort='time'):
out = Tensor.conv2d(x,w).realize()
out.numpy()
def test_four_kernels(self):
x,w = Tensor.rand(1,4,9,9).realize(), Tensor.rand(4,4,3,3).realize()
GlobalCounters.reset()
out = Tensor.conv2d(x,w).realize()
assert GlobalCounters.kernel_count == 4
out.numpy()
@unittest.skipIf(getenv("PTX"), "winograd uses too much in PTX")
def test_counters(self):
IC, OC, X, Y = 4,4,9,9
#OC, IC, X, Y = 512, 256, 8, 8
x,w = Tensor.rand(1,IC,Y,X).realize(), Tensor.rand(OC,IC,3,3).realize()
GlobalCounters.reset()
Tensor.conv2d(x,w).realize()
ops_wino, mem_wino = GlobalCounters.global_ops, GlobalCounters.global_mem
WINO.value = 0
GlobalCounters.reset()
Tensor.conv2d(x,w).realize()
ops_normal, mem_normal = GlobalCounters.global_ops, GlobalCounters.global_mem
ops_ratio, mem_ratio = ops_wino/ops_normal, mem_wino/mem_normal
print(f"ops: normal {ops_normal:9d} wino {ops_wino:9d} ratio {ops_ratio:.2f}")
print(f"mem: normal {mem_normal:9d} wino {mem_wino:9d} ratio {mem_ratio:.2f}")
self.assertLess(ops_ratio, 2.6) # TODO: there's issues with factorization now
self.assertLess(mem_ratio, 10)
def test_dtype(self):
IC, OC, X, Y = 4,4,9,9
x,w = Tensor.empty(1,IC,Y,X), Tensor.empty(OC,IC,3,3)
self.assertEqual(Tensor.conv2d(x,w).dtype, dtypes.default_float)
x,w = Tensor.empty(1,IC,Y,X,dtype=dtypes.half), Tensor.empty(OC,IC,3,3,dtype=dtypes.half)
self.assertEqual(Tensor.conv2d(x,w).dtype, dtypes.half)
if __name__ == '__main__':
unittest.main(verbosity=2)