forked from pytorch/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
test_dce.cpp
52 lines (49 loc) · 1.56 KB
/
test_dce.cpp
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
#include <test/cpp/jit/test_base.h>
#include <test/cpp/jit/test_utils.h>
#include <torch/csrc/jit/passes/dead_code_elimination.h>
#include <torch/csrc/jit/testing/file_check.h>
namespace torch {
namespace jit {
void testDCE() {
auto graph = std::make_shared<Graph>();
// Consider the following loop:
// for i in range(3):
// tot += a[0][0]
// b = a[0]
// b[0] += 1
// print(tot)
// We want to check that b[0] and b are properly marked as live and thus not
// DCE'd.
const std::string input =
R"IR(
graph():
%48 : None = prim::Constant()
%50 : bool = prim::Constant[value=1]()
%0 : int = prim::Constant[value=2]()
%12 : int = prim::Constant[value=1]()
%24 : int = prim::Constant[value=3]()
%31 : int = prim::Constant[value=0]()
%2 : int[] = prim::ListConstruct(%0, %0)
%a.1 : Tensor = prim::MakeTestTensor()
%14 : int[] = prim::ListConstruct(%12)
%tot.1 : Tensor = prim::MakeTestTensor()
%tot : Tensor = prim::Loop(%24, %50, %tot.1)
block0(%i : int, %tot.6 : Tensor):
%33 : Tensor = aten::select(%a.1, %31, %31)
%35 : Tensor = aten::select(%33, %31, %31)
# CHECK: add_
%tot.3 : Tensor = aten::add_(%tot.6, %35, %12)
%b.1 : Tensor = aten::select(%a.1, %31, %31)
%44 : Tensor = aten::select(%b.1, %31, %31)
# CHECK: add_
%46 : Tensor = aten::add_(%44, %12, %12)
-> (%50, %tot.3)
return (%tot)
)IR";
parseIR(input, graph.get());
EliminateDeadCode(graph);
// Check that dead code elimin
testing::FileCheck().run(input, *graph);
}
} // namespace jit
} // namespace torch