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8798d120bb
* autopad shapetracker for BEAM * OptOps.PADTO * skip that test for now * correct padding reduce axis * just 32 * avoid more than double the FLOPs * cleanups * test case * no support for triton and llvm yet * typos * symbolic shape would not work * cannot PADTO with MAX kernel * advance db version * no breaking change - don't advance db version * is triton just python? * Revert "is triton just python?" This reverts commit 17e776c25587615e33a3634c2fb0bb8591ce65d4. * Revert "Revert "is triton just python?"" This reverts commit 6c434c01e1c4b0ea0431ec18632cd859fb3cf260. * support llvm * is it really passing in CI only? * update tests * oh triton test passed * simpler * revert that, with a test * check if st are the same * Revert "check if st are the same" This reverts commit d2a5eac110a5da1af82a2728c883779ef69c3cad. * update the db version * rebase artifact
40 lines
1.0 KiB
Python
40 lines
1.0 KiB
Python
from tinygrad.tensor import Tensor
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from tinygrad.ops import LoadOps
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from tinygrad.codegen.linearizer import Linearizer
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from test.external.fuzz_linearizer import run_linearizer
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from tinygrad.codegen.kernel import Opt, OptOps
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N = 17**3
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a = Tensor.rand(N, N)
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b = Tensor.rand(N, N)
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c = a @ b
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sched = [si for si in c.lazydata.schedule() if si.ast.op not in LoadOps]
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assert len(sched) == 1
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lin = Linearizer(sched[0].ast)
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lin.apply_opt(Opt(op=OptOps.PADTO, axis=0, amt=32))
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lin.apply_opt(Opt(op=OptOps.PADTO, axis=1, amt=32))
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lin.apply_opt(Opt(op=OptOps.PADTO, axis=2, amt=32))
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lin.hand_coded_optimizations()
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lin.linearize()
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print(f"{lin.applied_opts=}")
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run_linearizer(lin)
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quit()
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###
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a = Tensor.rand(61, 61).sum(axis=0)
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sched = [si for si in a.lazydata.schedule() if si.ast.op not in LoadOps]
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assert len(sched) == 1
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lin = Linearizer(sched[0].ast)
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# lin.apply_opt(Opt(op=OptOps.LOCAL, axis=0, amt=32))
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lin.apply_opt(Opt(op=OptOps.PADTO, axis=0, amt=32))
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lin.apply_opt(Opt(op=OptOps.PADTO, axis=1, amt=32))
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lin.hand_coded_optimizations()
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lin.linearize()
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run_linearizer(lin) |