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
57
58
59
60
61
62
63
64
65
|
import operator_benchmark as op_bench
import torch
import torch.nn as nn
"""
Microbenchmarks for the softmax operators.
"""
# Configs for softmax ops
softmax_configs_short = op_bench.config_list(
attr_names=[
'N', 'C', 'H', 'W'
],
attrs=[
[1, 3, 256, 256],
[4, 3, 256, 256],
],
cross_product_configs={
'device': ['cpu', 'cuda'],
},
tags=['short']
)
softmax_configs_long = op_bench.cross_product_configs(
N=[8, 16],
C=[3],
H=[256, 512],
W=[256, 512],
device=['cpu', 'cuda'],
tags=['long']
)
softmax_ops_list = op_bench.op_list(
attr_names=['op_name', 'op_func'],
attrs=[
['Softmax', nn.Softmax],
['Softmax2d', nn.Softmax2d],
['LogSoftmax', nn.LogSoftmax],
],
)
class SoftmaxBenchmark(op_bench.TorchBenchmarkBase):
def init(self, N, C, H, W, device, op_func):
self.inputs = {
"input": torch.rand(N, C, H, W, device=device)
}
self.op_func = op_func()
def forward(self, input):
return self.op_func(input)
op_bench.generate_pt_tests_from_op_list(softmax_ops_list,
softmax_configs_short + softmax_configs_long,
SoftmaxBenchmark)
if __name__ == "__main__":
op_bench.benchmark_runner.main()
|
