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if_test.cc
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// Copyright 2023 Ant Group Co., Ltd.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "engine/operator/if.h"
#include "gtest/gtest.h"
#include "engine/core/tensor_constructor.h"
#include "engine/operator/test_util.h"
namespace scql::engine::op {
struct IfTestCase {
test::NamedTensor cond;
pb::TensorStatus cond_status;
test::NamedTensor value_true;
pb::TensorStatus value_true_status;
test::NamedTensor value_false;
pb::TensorStatus value_false_status;
test::NamedTensor out;
pb::TensorStatus out_status;
};
class IfTest : public ::testing::TestWithParam<
std::tuple<test::SpuRuntimeTestCase, IfTestCase>> {
protected:
static pb::ExecNode MakeIfExecNode(const IfTestCase& tc);
static void FeedInputs(const std::vector<ExecContext*>& ctxs,
const IfTestCase& tc);
static void FeedTensors(const std::vector<ExecContext*>& ctxs,
const std::vector<test::NamedTensor>& ts,
pb::TensorStatus status);
};
INSTANTIATE_TEST_SUITE_P(
IfPrivateTest, IfTest,
testing::Combine(
test::SpuTestValuesMultiPC,
testing::Values(
IfTestCase{
.cond = test::NamedTensor(
"Condition", TensorFrom(arrow::boolean(), "[1,0,1,null]")),
.cond_status = pb::TENSORSTATUS_PRIVATE,
.value_true = test::NamedTensor("ValueIfTrue",
TensorFrom(arrow::int64(),
"[10,11,null,13]")),
.value_true_status = pb::TENSORSTATUS_PRIVATE,
.value_false = test::NamedTensor("ValueIfFalse",
TensorFrom(arrow::int64(),
"[16,17,18,19]")),
.value_false_status = pb::TENSORSTATUS_PRIVATE,
.out = test::NamedTensor(
"Out", TensorFrom(arrow::int64(), "[10,17,null,null]")),
.out_status = pb::TENSORSTATUS_PRIVATE},
IfTestCase{
.cond = test::NamedTensor(
"Condition", TensorFrom(arrow::int64(), "[5,0,6,-1]")),
.cond_status = pb::TENSORSTATUS_PRIVATE,
.value_true = test::NamedTensor(
"ValueIfTrue", TensorFrom(arrow::int64(), "[10,11,12,13]")),
.value_true_status = pb::TENSORSTATUS_PRIVATE,
.value_false = test::NamedTensor("ValueIfFalse",
TensorFrom(arrow::int64(),
"[16,17,18,19]")),
.value_false_status = pb::TENSORSTATUS_PRIVATE,
.out = test::NamedTensor("Out", TensorFrom(arrow::int64(),
"[10,17,12,13]")),
.out_status = pb::TENSORSTATUS_PRIVATE},
IfTestCase{
.cond = test::NamedTensor(
"Condition", TensorFrom(arrow::int64(), "[5,0,6,-1]")),
.cond_status = pb::TENSORSTATUS_PRIVATE,
.value_true = test::NamedTensor(
"ValueIfTrue", TensorFrom(arrow::large_utf8(),
R"json(["A","B","C","D"])json")),
.value_true_status = pb::TENSORSTATUS_PRIVATE,
.value_false = test::NamedTensor(
"ValueIfFalse", TensorFrom(arrow::large_utf8(),
R"json(["E","F","G","H"])json")),
.value_false_status = pb::TENSORSTATUS_PRIVATE,
.out = test::NamedTensor(
"Out", TensorFrom(arrow::large_utf8(),
R"json(["A","F","C","D"])json")),
.out_status = pb::TENSORSTATUS_PRIVATE},
IfTestCase{
.cond = test::NamedTensor(
"Condition", TensorFrom(arrow::int64(), "[5,0,6,-1]")),
.cond_status = pb::TENSORSTATUS_SECRET,
.value_true = test::NamedTensor(
"ValueIfTrue", TensorFrom(arrow::large_utf8(),
R"json(["A","B","C","D"])json")),
.value_true_status = pb::TENSORSTATUS_SECRET,
.value_false = test::NamedTensor(
"ValueIfFalse", TensorFrom(arrow::large_utf8(),
R"json(["E","F","G","H"])json")),
.value_false_status = pb::TENSORSTATUS_SECRET,
.out = test::NamedTensor(
"Out", TensorFrom(arrow::large_utf8(),
R"json(["A","F","C","D"])json")),
.out_status = pb::TENSORSTATUS_SECRET},
IfTestCase{
.cond = test::NamedTensor(
"Condition", TensorFrom(arrow::boolean(), "[1,0,1,1]")),
.cond_status = pb::TENSORSTATUS_SECRET,
.value_true = test::NamedTensor(
"ValueIfTrue", TensorFrom(arrow::int64(), "[10,11,12,13]")),
.value_true_status = pb::TENSORSTATUS_SECRET,
.value_false = test::NamedTensor("ValueIfFalse",
TensorFrom(arrow::int64(),
"[16,17,18,19]")),
.value_false_status = pb::TENSORSTATUS_SECRET,
.out = test::NamedTensor("Out", TensorFrom(arrow::int64(),
"[10,17,12,13]")),
.out_status = pb::TENSORSTATUS_SECRET},
IfTestCase{
.cond = test::NamedTensor(
"Condition", TensorFrom(arrow::int64(), "[5,0,6,-1]")),
.cond_status = pb::TENSORSTATUS_SECRET,
.value_true = test::NamedTensor(
"ValueIfTrue", TensorFrom(arrow::int64(), "[10,11,12,13]")),
.value_true_status = pb::TENSORSTATUS_SECRET,
.value_false = test::NamedTensor("ValueIfFalse",
TensorFrom(arrow::int64(),
"[16,17,18,19]")),
.value_false_status = pb::TENSORSTATUS_SECRET,
.out = test::NamedTensor("Out", TensorFrom(arrow::int64(),
"[10,17,12,13]")),
.out_status = pb::TENSORSTATUS_SECRET},
IfTestCase{
.cond = test::NamedTensor(
"Condition", TensorFrom(arrow::boolean(), "[1,0,1,1]")),
.cond_status = pb::TENSORSTATUS_PUBLIC,
.value_true = test::NamedTensor(
"ValueIfTrue", TensorFrom(arrow::int64(), "[10,11,12,13]")),
.value_true_status = pb::TENSORSTATUS_PUBLIC,
.value_false = test::NamedTensor("ValueIfFalse",
TensorFrom(arrow::int64(),
"[16,17,18,19]")),
.value_false_status = pb::TENSORSTATUS_SECRET,
.out = test::NamedTensor("Out", TensorFrom(arrow::int64(),
"[10,17,12,13]")),
.out_status = pb::TENSORSTATUS_SECRET},
IfTestCase{
.cond = test::NamedTensor(
"Condition", TensorFrom(arrow::boolean(), "[1,0,1,1]")),
.cond_status = pb::TENSORSTATUS_PUBLIC,
.value_true = test::NamedTensor(
"ValueIfTrue", TensorFrom(arrow::int64(), "[10,11,12,13]")),
.value_true_status = pb::TENSORSTATUS_PUBLIC,
.value_false = test::NamedTensor("ValueIfFalse",
TensorFrom(arrow::int64(),
"[16,17,18,19]")),
.value_false_status = pb::TENSORSTATUS_PUBLIC,
.out = test::NamedTensor("Out", TensorFrom(arrow::int64(),
"[10,17,12,13]")),
.out_status = pb::TENSORSTATUS_PUBLIC},
IfTestCase{
.cond = test::NamedTensor(
"Condition", TensorFrom(arrow::boolean(), "[1,0,1,1]")),
.cond_status = pb::TENSORSTATUS_SECRET,
.value_true = test::NamedTensor(
"ValueIfTrue", TensorFrom(arrow::int64(), "[10,11,12,13]")),
.value_true_status = pb::TENSORSTATUS_SECRET,
.value_false = test::NamedTensor(
"ValueIfFalse",
TensorFrom(arrow::float32(), "[16,17.5,18,19.5]")),
.value_false_status = pb::TENSORSTATUS_SECRET,
.out = test::NamedTensor("Out", TensorFrom(arrow::float32(),
"[10,17.5,12,13]")),
.out_status = pb::TENSORSTATUS_SECRET},
IfTestCase{
.cond = test::NamedTensor("Condition",
TensorFrom(arrow::float32(),
"[1.5,0,-1.5,1]")),
.cond_status = pb::TENSORSTATUS_SECRET,
.value_true = test::NamedTensor(
"ValueIfTrue", TensorFrom(arrow::int64(), "[10,11,12,13]")),
.value_true_status = pb::TENSORSTATUS_SECRET,
.value_false = test::NamedTensor(
"ValueIfFalse",
TensorFrom(arrow::float32(), "[16,17.5,18,19.5]")),
.value_false_status = pb::TENSORSTATUS_SECRET,
.out = test::NamedTensor("Out", TensorFrom(arrow::float32(),
"[10,17.5,12,13]")),
.out_status = pb::TENSORSTATUS_SECRET},
IfTestCase{
.cond = test::NamedTensor("Condition",
TensorFrom(arrow::float32(),
"[1.5,0,-1.5,1]")),
.cond_status = pb::TENSORSTATUS_PRIVATE,
.value_true = test::NamedTensor(
"ValueIfTrue", TensorFrom(arrow::int64(), "[10,11,12,13]")),
.value_true_status = pb::TENSORSTATUS_PRIVATE,
.value_false = test::NamedTensor(
"ValueIfFalse",
TensorFrom(arrow::float32(), "[16,17.5,18,19.5]")),
.value_false_status = pb::TENSORSTATUS_PRIVATE,
.out = test::NamedTensor("Out", TensorFrom(arrow::float32(),
"[10,17.5,12,13]")),
.out_status = pb::TENSORSTATUS_PRIVATE},
IfTestCase{
.cond = test::NamedTensor(
"Condition", TensorFrom(arrow::boolean(), "[1,0,1,1]")),
.cond_status = pb::TENSORSTATUS_PRIVATE,
.value_true = test::NamedTensor(
"ValueIfTrue", TensorFrom(arrow::int64(), "[10,11,12,13]")),
.value_true_status = pb::TENSORSTATUS_PRIVATE,
.value_false = test::NamedTensor(
"ValueIfFalse",
TensorFrom(arrow::float32(), "[16,17.5,18,19.5]")),
.value_false_status = pb::TENSORSTATUS_PRIVATE,
.out = test::NamedTensor("Out", TensorFrom(arrow::float32(),
"[10,17.5,12,13]")),
.out_status = pb::TENSORSTATUS_PRIVATE})),
TestParamNameGenerator(IfTest));
TEST_P(IfTest, works) {
// Given
auto parm = GetParam();
auto tc = std::get<1>(parm);
auto node = MakeIfExecNode(tc);
auto sessions = test::MakeMultiPCSession(std::get<0>(parm));
std::vector<ExecContext> exec_ctxs;
exec_ctxs.reserve(sessions.size());
for (auto& session : sessions) {
exec_ctxs.emplace_back(node, session.get());
}
// feed inputs
std::vector<ExecContext*> ctx_ptrs;
ctx_ptrs.reserve(exec_ctxs.size());
for (auto& exec_ctx : exec_ctxs) {
ctx_ptrs.emplace_back(&exec_ctx);
}
FeedInputs(ctx_ptrs, tc);
// When
if (tc.value_false_status == pb::TENSORSTATUS_PRIVATE) {
EXPECT_NO_THROW(test::RunAsync<If>({ctx_ptrs[0]}));
} else {
EXPECT_NO_THROW(test::RunAsync<If>(ctx_ptrs));
}
// Then check alice's outputs
auto* tensor_table = ctx_ptrs[0]->GetTensorTable();
TensorPtr out;
if (tc.value_false_status == pb::TENSORSTATUS_PRIVATE) {
EXPECT_NO_THROW(out = tensor_table->GetTensor(tc.out.name));
} else {
EXPECT_NO_THROW(out = test::RevealSecret(ctx_ptrs, tc.out.name));
// convert hash to string for string tensor in spu
if (tc.out.tensor->Type() == pb::PrimitiveDataType::STRING) {
out = ctx_ptrs[0]->GetSession()->HashToString(*out);
}
}
EXPECT_TRUE(out != nullptr);
EXPECT_EQ(out->Length(), tc.out.tensor->Length());
EXPECT_EQ(out->GetNullCount(), tc.out.tensor->GetNullCount());
EXPECT_EQ(out->Type(), tc.out.tensor->Type());
// compare tensor content
EXPECT_TRUE(
out->ToArrowChunkedArray()->Equals(tc.out.tensor->ToArrowChunkedArray()));
}
/// ===========================
/// IfTest impl
/// ===========================
pb::ExecNode IfTest::MakeIfExecNode(const IfTestCase& tc) {
test::ExecNodeBuilder builder(If::kOpType);
builder.SetNodeName("if-test");
// Add inputs
auto cond = test::MakeTensorReference(tc.cond.name, tc.cond.tensor->Type(),
tc.cond_status);
builder.AddInput(If::kCond, std::vector<pb::Tensor>{cond});
auto value_true = test::MakeTensorReference(
tc.value_true.name, tc.value_true.tensor->Type(), tc.value_true_status);
builder.AddInput(If::kValueTrue, std::vector<pb::Tensor>{value_true});
auto value_false = test::MakeTensorReference(tc.value_false.name,
tc.value_false.tensor->Type(),
tc.value_false_status);
builder.AddInput(If::kValueFalse, std::vector<pb::Tensor>{value_false});
// Add outputs
auto out = test::MakeTensorReference(tc.out.name, tc.out.tensor->Type(),
tc.out_status);
builder.AddOutput(If::kOut, std::vector<pb::Tensor>{out});
return builder.Build();
}
void IfTest::FeedTensors(const std::vector<ExecContext*>& ctxs,
const std::vector<test::NamedTensor>& ts,
pb::TensorStatus status) {
if (status == pb::TENSORSTATUS_PRIVATE) {
test::FeedInputsAsPrivate(ctxs[0], ts);
} else if (status == pb::TENSORSTATUS_SECRET) {
test::FeedInputsAsSecret(ctxs, ts);
} else {
test::FeedInputsAsPublic(ctxs, ts);
}
}
void IfTest::FeedInputs(const std::vector<ExecContext*>& ctxs,
const IfTestCase& tc) {
FeedTensors(ctxs, {tc.cond}, tc.cond_status);
FeedTensors(ctxs, {tc.value_true}, tc.value_true_status);
FeedTensors(ctxs, {tc.value_false}, tc.value_false_status);
}
} // namespace scql::engine::op