pytorch/test/cpp/jit/test_schema_matching.cpp
Owen Anderson bdf10380d6 Whenever possible, use function pointers rather than std::function to represent Operation's. (#26560)
Summary:
This takes a lot of pressure off of the C++ typechecker as well as generating much more
efficient and smaller code.  In my not-super-rigorous testing, compile time for
register_prim_ops.cpp went from 68s to 35s, and the size of libtorch went from 72MB to 70MB.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/26560

Differential Revision: D17507305

fbshipit-source-id: 8bbd2c08304739432efda96da71f0fa80eb7668b
2019-09-21 20:51:24 -07:00

93 lines
2.3 KiB
C++

#include <torch/csrc/jit/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/custom_operator.h"
#include <sstream>
#include <string>
namespace torch {
namespace jit {
void testSchemaMatching() {
{
RegisterOperators reg({
Operator(
"aten::test_vartype(t[] a, t b) -> (t)",
[](const Node* node) -> Operation {
return [](Stack& stack) {
c10::List<double> list;
double a;
pop(stack, list, a);
push(stack, a);
return 0;
};
}),
});
script::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[])",
[](const Node* node) -> Operation {
return [](Stack& stack) {
double a;
c10::List<double> list;
pop(stack, a, list);
push(stack, a);
return 0;
};
}),
});
script::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