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