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#include <gtest/gtest.h>
#include <ATen/ATen.h>
#include <torch/nativert/executor/Executor.h>
#include <torch/nativert/graph/Graph.h>
#include <torch/torch.h>
#include <torch/nativert/kernels/KernelHandlerRegistry.h>
namespace torch::nativert {
/*
* This is a lightweight version of ModelRunner that executes a model in
* interpreter mode given a string graph with no weights/attributes
*/
class SimpleTestModelRunner {
public:
SimpleTestModelRunner(
const std::string_view source,
const ExecutorConfig& config) {
register_kernel_handlers();
graph_ = stringToGraph(source);
weights_ = std::make_shared<Weights>(graph_.get());
executor_ = std::make_unique<Executor>(config, graph_, weights_);
}
std::vector<c10::IValue> run(const std::vector<c10::IValue>& inputs) const {
return executor_->execute(inputs);
}
ProfileMetrics benchmarkIndividualNodes(
const std::vector<c10::IValue>& inputs) const {
return executor_->benchmarkIndividualNodes({inputs}, 10, 10);
}
private:
std::shared_ptr<Graph> graph_;
std::unique_ptr<Executor> executor_;
std::shared_ptr<Weights> weights_;
};
inline void compareIValue(
const c10::IValue& expected,
const c10::IValue& actual,
bool native = false) {
if (expected.isTensor()) {
EXPECT_TRUE(actual.isTensor());
EXPECT_TRUE(torch::allclose(
expected.toTensor(),
actual.toTensor(),
1e-5,
1e-8,
/*equal_nan*/ true));
if (!native) {
EXPECT_TRUE(expected.toTensor().strides() == actual.toTensor().strides());
}
} else if (expected.isTuple()) {
EXPECT_TRUE(actual.isTuple());
auto expected_tuple = expected.toTupleRef().elements();
auto actual_tuple = actual.toTupleRef().elements();
ASSERT_TRUE(expected_tuple.size() == actual_tuple.size());
for (size_t i = 0; i < expected_tuple.size(); i++) {
compareIValue(expected_tuple[i], actual_tuple[i], native);
}
} else if (expected.isList()) {
EXPECT_TRUE(actual.isList());
auto expected_list = expected.toList();
auto actual_list = actual.toList();
ASSERT_TRUE(expected_list.size() == actual_list.size());
for (size_t i = 0; i < expected_list.size(); i++) {
compareIValue(expected_list[i], actual_list[i], native);
}
} else if (expected.isGenericDict()) {
EXPECT_TRUE(actual.isGenericDict());
auto expected_dict = expected.toGenericDict();
auto actual_dict = actual.toGenericDict();
EXPECT_TRUE(expected_dict.size() == actual_dict.size());
for (auto& expected_kv : expected_dict) {
auto actual_kv = actual_dict.find(expected_kv.key());
ASSERT_FALSE(actual_kv == actual_dict.end());
compareIValue(expected_kv.value(), actual_kv->value(), native);
}
} else {
// Fall back to default comparison from IValue
EXPECT_TRUE(expected == actual);
}
}
void compareIValues(
std::vector<c10::IValue> expected,
std::vector<c10::IValue> actual,
bool native = false) {
ASSERT_TRUE(expected.size() == actual.size());
for (size_t i = 0; i < expected.size(); i++) {
compareIValue(expected[i], actual[i], native);
}
}
inline void testStaticKernelEqualityInternal(
const SimpleTestModelRunner& modelRunner,
const SimpleTestModelRunner& staticModelRunner,
const std::vector<c10::IValue>& args,
bool native = false) {
auto expected = modelRunner.run(args);
auto output = staticModelRunner.run(args);
compareIValues(expected, output, native);
// Run again to test the static kernel when outputs IValue are cached in the
// execution frame
auto output2 = staticModelRunner.run(args);
compareIValues(expected, output2, native);
}
void testStaticKernelEquality(
const std::string_view source,
const std::vector<c10::IValue>& args,
bool native = false) {
ExecutorConfig config;
config.enableStaticCPUKernels = false;
SimpleTestModelRunner model(source, config);
config.enableStaticCPUKernels = true;
SimpleTestModelRunner staticKernelModel(source, config);
testStaticKernelEqualityInternal(model, staticKernelModel, args, native);
}
inline void testGraphABEquality(
const std::string_view graph_a,
const std::string_view graph_b,
const std::vector<c10::IValue>& args,
const ExecutorConfig& config = {},
bool native = false) {
SimpleTestModelRunner model_a(graph_a, config);
auto expected = model_a.run(args);
SimpleTestModelRunner model_b(graph_b, config);
auto output = model_b.run(args);
compareIValues(expected, output, native);
}
inline void testGraphABPerf(
const std::string_view graph_a,
const std::string_view graph_b,
const std::vector<c10::IValue>& args,
const ExecutorConfig& config = {}) {
SimpleTestModelRunner model_a(graph_a, config);
auto resultA = model_a.benchmarkIndividualNodes(args);
SimpleTestModelRunner model_b(graph_b, config);
auto resultB = model_b.benchmarkIndividualNodes(args);
ASSERT_TRUE(resultA.totalTime > resultB.totalTime);
}
} // namespace torch::nativert
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