41 lines
1.1 KiB
Python
41 lines
1.1 KiB
Python
from tinygrad.tensor import Tensor
|
|
from tinygrad.ops import LoadOps
|
|
from tinygrad.codegen.linearizer import Linearizer
|
|
from test.external.fuzz_linearizer import run_linearizer
|
|
from tinygrad.codegen.kernel import Opt, OptOps
|
|
|
|
N = 17**3
|
|
|
|
a = Tensor.rand(N, N)
|
|
b = Tensor.rand(N, N)
|
|
c = a @ b
|
|
sched = [si for si in c.lazydata.schedule() if si.ast.op not in LoadOps]
|
|
assert len(sched) == 1
|
|
lin = Linearizer(sched[0].ast)
|
|
|
|
lin.apply_opt(Opt(op=OptOps.PADTO, axis=0, amt=32))
|
|
lin.apply_opt(Opt(op=OptOps.PADTO, axis=1, amt=32))
|
|
lin.apply_opt(Opt(op=OptOps.PADTO, axis=2, amt=32))
|
|
lin.hand_coded_optimizations()
|
|
lin.linearize()
|
|
print(f"{lin.applied_opts=}")
|
|
|
|
run_linearizer(lin)
|
|
quit()
|
|
|
|
###
|
|
|
|
a = Tensor.rand(61, 61).sum(axis=0)
|
|
sched = [si for si in a.lazydata.schedule() if si.ast.op not in LoadOps]
|
|
assert len(sched) == 1
|
|
lin = Linearizer(sched[0].ast)
|
|
|
|
# lin.apply_opt(Opt(op=OptOps.LOCAL, axis=0, amt=32))
|
|
|
|
lin.apply_opt(Opt(op=OptOps.PADTO, axis=0, amt=32))
|
|
lin.apply_opt(Opt(op=OptOps.PADTO, axis=1, amt=32))
|
|
lin.hand_coded_optimizations()
|
|
lin.linearize()
|
|
|
|
run_linearizer(lin)
|