Files
pytorch/test/custom_operator/test_custom_ops.cpp
Peter Goldsborough a0d4106c07 Integrate custom op tests with CI (#10611)
Summary:
This PR is stacked on https://github.com/pytorch/pytorch/pull/10610, and only adds changes in one file `.jenkins/pytorch/test.sh`, where we now build the custom op tests and run them.

I'd also like to take this PR to discuss whether the [`TorchConfig.cmake`](https://github.com/pytorch/pytorch/blob/master/cmake/TorchConfig.cmake.in) I made is robust enough (we will also see in the CI) orionr Yangqing dzhulgakov what do you think?

Also ezyang for CI changes
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10611

Differential Revision: D9597627

Pulled By: goldsborough

fbshipit-source-id: f5af8164c076894f448cef7e5b356a6b3159f8b3
2018-09-10 15:40:21 -07:00

93 lines
2.6 KiB
C++

#include <torch/op.h>
#include "op.h"
#include <cassert>
#include <memory>
#include <vector>
#include <iostream>
void get_operator_from_registry_and_execute() {
auto& ops = torch::jit::getAllOperatorsFor(
torch::jit::Symbol::fromQualString("custom::op"));
assert(ops.size() == 1);
auto& op = ops.front();
assert(op->schema().name == "custom::op");
torch::jit::Stack stack;
torch::jit::push(stack, torch::ones(5), 2.0, 3);
op->getOperation()(stack);
std::vector<at::Tensor> output;
torch::jit::pop(stack, output);
const auto manual = custom_op(torch::ones(5), 2.0, 3);
assert(output.size() == 3);
for (size_t i = 0; i < output.size(); ++i) {
assert(output[i].allclose(torch::ones(5) * 2));
assert(output[i].allclose(manual[i]));
}
}
void load_serialized_module_with_custom_op_and_execute(
const char* path_to_exported_script_module) {
std::shared_ptr<torch::jit::script::Module> module =
torch::jit::load(path_to_exported_script_module);
assert(module != nullptr);
std::vector<torch::jit::IValue> inputs;
inputs.push_back(torch::ones(5));
auto output = module->forward(inputs).toTensor();
assert(output.allclose(torch::ones(5) + 1));
}
void test_argument_checking_for_serialized_modules(
const char* path_to_exported_script_module) {
std::shared_ptr<torch::jit::script::Module> module =
torch::jit::load(path_to_exported_script_module);
assert(module != nullptr);
try {
module->forward({torch::jit::IValue(1), torch::jit::IValue(2)});
assert(false);
} catch (const at::Error& error) {
assert(
std::string(error.what_without_backtrace())
.find("Expected at most 1 argument(s) for operator 'forward', "
"but received 2 argument(s)") == 0);
}
try {
module->forward({torch::jit::IValue(5)});
assert(false);
} catch (const at::Error& error) {
assert(
std::string(error.what_without_backtrace())
.find("Expected value of type Dynamic for argument 'input' in "
"position 0, but instead got value of type int") == 0);
}
try {
module->forward({});
assert(false);
} catch (const at::Error& error) {
assert(
std::string(error.what_without_backtrace())
.find("forward() is missing value for argument 'input'") == 0);
}
}
int main(int argc, const char* argv[]) {
if (argc != 2) {
std::cerr << "usage: test_custom_ops <path-to-exported-script-module>\n";
return -1;
}
get_operator_from_registry_and_execute();
load_serialized_module_with_custom_op_and_execute(argv[1]);
test_argument_checking_for_serialized_modules(argv[1]);
std::cout << "ok\n";
}