1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
|
import timeit
import torch
import torch.nn as nn
from functorch.compile import compiled_module, tvm_compile
def nop(f, _):
return f
fw_compiler = tvm_compile(target="llvm", tuning_logfile="fw_keops")
bw_compiler = tvm_compile(target="llvm", tuning_logfile="bw_keops")
fw_compiler = nop
bw_compiler = nop
def run(mod, input):
out = mod(input)
out.sum().backward()
grads = [p.grad for p in mod.parameters()]
return (out, *grads)
class Foo(nn.Module):
def __init__(self) -> None:
super().__init__()
self.param = nn.Parameter(torch.randn(1))
self.register_buffer("buf", torch.randn(1))
def forward(self, x):
return (self.param * x + self.buf).sum(dim=0)
input = torch.randn(1)
mod = Foo()
compiled_mod = compiled_module(mod, fw_compiler, bw_compiler)
for a, b in zip(run(mod, input), run(compiled_mod, input)):
torch.testing.assert_close(a, b)
out = mod(input)
out.sum().backward()
mod.param.data -= mod.param.grad
compiled_mod.orig_module.param.data -= compiled_mod.orig_module.param.grad
compiled_mod.orig_module.param.grad = None
for a, b in zip(run(mod, input), run(compiled_mod, input)):
torch.testing.assert_close(a, b)
for _ in range(5):
i = 10000
t = timeit.Timer("mod(input)", globals=globals()).timeit(10000)
print(f"eager {t / i * 1e6}")
t = timeit.Timer("compiled_mod(input)", globals=globals()).timeit(10000)
print(f"compiled {t / i * 1e6}")
|
