mirror of
https://github.com/zebrajr/pytorch.git
synced 2026-01-15 12:15:51 +00:00
6384c2d81b
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/35115 This commit runs the newly added tools/clang_format.py on the JIT codebase and includes all of the formatting changes thus produced. Testing: Ran the script, CI. Test Plan: Imported from OSS Reviewed By: eellison Differential Revision: D20568523 Pulled By: SplitInfinity fbshipit-source-id: e09bdb982ccf090eecfb7c7b461b8d0681eef82b
92 lines
2.3 KiB
C++
92 lines
2.3 KiB
C++
#include <torch/csrc/jit/ir/ir.h>
|
|
#include <torch/csrc/jit/testing/file_check.h>
|
|
#include <torch/jit.h>
|
|
#include "test/cpp/jit/test_base.h"
|
|
#include "torch/csrc/jit/runtime/custom_operator.h"
|
|
|
|
#include <sstream>
|
|
#include <string>
|
|
|
|
namespace torch {
|
|
namespace jit {
|
|
|
|
void testSchemaMatching() {
|
|
{
|
|
RegisterOperators reg({
|
|
Operator(
|
|
"aten::test_vartype(t[] a, t b) -> (t)",
|
|
[](Stack& stack) {
|
|
c10::List<double> list;
|
|
double a;
|
|
pop(stack, list, a);
|
|
push(stack, a);
|
|
return 0;
|
|
},
|
|
c10::AliasAnalysisKind::FROM_SCHEMA),
|
|
});
|
|
Module m("m");
|
|
m.define(R"(
|
|
def test(self):
|
|
a = (1.0, 2.0)
|
|
return torch.test_vartype(a, 2.0)
|
|
)");
|
|
auto result = m.run_method("test");
|
|
TORCH_INTERNAL_ASSERT(result.toDouble() == 2.0);
|
|
|
|
const std::string error_example = R"JIT(
|
|
def test_2(self):
|
|
a = (1.0, 2.0)
|
|
non_float = (1, 1)
|
|
return torch.test_vartype(a, non_float)
|
|
)JIT";
|
|
|
|
std::string err = "";
|
|
try {
|
|
m.define(error_example);
|
|
} catch (const std::exception& e) {
|
|
err = e.what();
|
|
}
|
|
TORCH_INTERNAL_ASSERT(
|
|
err.find("previously matched to type") != std::string::npos);
|
|
}
|
|
{
|
|
RegisterOperators reg({
|
|
Operator(
|
|
"aten::test_vartype2(t a, t[] b) -> (t[])",
|
|
[](Stack& stack) {
|
|
double a;
|
|
c10::List<double> list;
|
|
pop(stack, a, list);
|
|
push(stack, a);
|
|
return 0;
|
|
},
|
|
AliasAnalysisKind::FROM_SCHEMA),
|
|
});
|
|
Module m("m");
|
|
m.define(R"JIT(
|
|
def test(self):
|
|
a = (1.0, 2.0)
|
|
return torch.test_vartype2(3.0, a)
|
|
)JIT");
|
|
auto result = m.run_method("test");
|
|
TORCH_INTERNAL_ASSERT(result.toDouble() == 3.0);
|
|
|
|
static const auto error_exam2 = R"JIT(
|
|
def test_2(self):
|
|
a = (1, 2)
|
|
return torch.test_vartype2(3.0, a)
|
|
)JIT";
|
|
|
|
std::string err = "";
|
|
try {
|
|
m.define(error_exam2);
|
|
} catch (const std::exception& e) {
|
|
err = e.what();
|
|
}
|
|
TORCH_INTERNAL_ASSERT(
|
|
err.find("previously matched to type") != std::string::npos);
|
|
}
|
|
}
|
|
} // namespace jit
|
|
} // namespace torch
|