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case_when_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/case_when.h"
#include "gtest/gtest.h"
#include "libspu/kernel/hal/public_helper.h"
#include "engine/core/tensor_constructor.h"
#include "engine/operator/test_util.h"
#include "engine/util/ndarray_to_arrow.h"
namespace scql::engine::op {
struct CaseWhenTestCase {
std::vector<test::NamedTensor> conds;
std::vector<pb::TensorStatus> cond_status;
std::vector<test::NamedTensor> values;
std::vector<pb::TensorStatus> value_status;
test::NamedTensor value_else;
pb::TensorStatus value_else_status;
test::NamedTensor expect_out;
pb::TensorStatus expect_out_status;
};
class CaseWhenTest
: public ::testing::TestWithParam<
std::tuple<test::SpuRuntimeTestCase, CaseWhenTestCase>> {
protected:
static pb::ExecNode MakeCaseWhenExecNode(const CaseWhenTestCase& tc);
static void FeedInputs(const std::vector<ExecContext*>& ctxs,
const CaseWhenTestCase& tc);
static void FeedTensors(const std::vector<ExecContext*>& ctxs,
const std::vector<test::NamedTensor>& ts,
const std::vector<pb::TensorStatus>& status);
};
INSTANTIATE_TEST_SUITE_P(
CaseWhenPrivateTest, CaseWhenTest,
testing::Combine(
test::SpuTestValuesMultiPC,
testing::Values(
CaseWhenTestCase{
.conds = {test::NamedTensor("cond1", TensorFrom(arrow::int64(),
"[1,0,0,0]")),
test::NamedTensor(
"cond2", TensorFrom(arrow::boolean(),
"[true,true,false,false]")),
test::NamedTensor("cond3",
TensorFrom(arrow::int64(),
"[11,11,11,0]"))},
.cond_status = {pb::TENSORSTATUS_PUBLIC,
pb::TENSORSTATUS_PUBLIC,
pb::TENSORSTATUS_PUBLIC},
.values =
{test::NamedTensor("value1",
TensorFrom(arrow::int64(), "[1,1,1,1]")),
test::NamedTensor("value2",
TensorFrom(arrow::int64(), "[2,2,2,2]")),
test::NamedTensor("value3", TensorFrom(arrow::int64(),
"[3,3,3,3]"))},
.value_status = {pb::TENSORSTATUS_PUBLIC,
pb::TENSORSTATUS_PUBLIC,
pb::TENSORSTATUS_PUBLIC},
.value_else = test::NamedTensor(
"value_else", TensorFrom(arrow::int64(), "[4,4,4,4]")),
.value_else_status = pb::TENSORSTATUS_PUBLIC,
.expect_out = test::NamedTensor(
"out", TensorFrom(arrow::int64(), "[1,2,3,4]")),
.expect_out_status = pb::TENSORSTATUS_PUBLIC},
CaseWhenTestCase{
.conds =
{test::NamedTensor("cond1", TensorFrom(arrow::int64(),
"[1,null,0,0]")),
test::NamedTensor(
"cond2", TensorFrom(arrow::boolean(),
"[true,true,null,false]")),
test::NamedTensor("cond3", TensorFrom(arrow::int64(),
"[11,11,11,null]"))},
.cond_status = {pb::TENSORSTATUS_PRIVATE,
pb::TENSORSTATUS_PRIVATE,
pb::TENSORSTATUS_PRIVATE},
.values =
{test::NamedTensor("value1",
TensorFrom(arrow::int64(), "[1,1,1,1]")),
test::NamedTensor("value2",
TensorFrom(arrow::int64(), "[2,2,2,2]")),
test::NamedTensor("value3", TensorFrom(arrow::int64(),
"[3,3,3,3]"))},
.value_status = {pb::TENSORSTATUS_PRIVATE,
pb::TENSORSTATUS_PRIVATE,
pb::TENSORSTATUS_PRIVATE},
.value_else = test::NamedTensor(
"value_else", TensorFrom(arrow::int64(), "[4,4,4,4]")),
.value_else_status = pb::TENSORSTATUS_PRIVATE,
.expect_out = test::NamedTensor(
"out", TensorFrom(arrow::int64(), "[1,2,3,4]")),
.expect_out_status = pb::TENSORSTATUS_PRIVATE},
CaseWhenTestCase{
.conds = {test::NamedTensor("cond1", TensorFrom(arrow::int64(),
"[1,0,0,0]")),
test::NamedTensor(
"cond2", TensorFrom(arrow::boolean(),
"[true,true,false,false]")),
test::NamedTensor("cond3",
TensorFrom(arrow::int64(),
"[11,11,11,0]"))},
.cond_status = {pb::TENSORSTATUS_SECRET,
pb::TENSORSTATUS_PUBLIC,
pb::TENSORSTATUS_PUBLIC},
.values =
{test::NamedTensor("value1",
TensorFrom(arrow::int64(), "[1,1,1,1]")),
test::NamedTensor("value2",
TensorFrom(arrow::int64(), "[2,2,2,2]")),
test::NamedTensor("value3", TensorFrom(arrow::int64(),
"[3,3,3,3]"))},
.value_status = {pb::TENSORSTATUS_SECRET,
pb::TENSORSTATUS_SECRET,
pb::TENSORSTATUS_PUBLIC},
.value_else = test::NamedTensor(
"value_else", TensorFrom(arrow::int64(), "[4,4,4,4]")),
.value_else_status = pb::TENSORSTATUS_PUBLIC,
.expect_out = test::NamedTensor(
"out", TensorFrom(arrow::int64(), "[1,2,3,4]")),
.expect_out_status = pb::TENSORSTATUS_SECRET},
CaseWhenTestCase{
.conds = {test::NamedTensor("cond1", TensorFrom(arrow::int64(),
"[-1,0,0,0]")),
test::NamedTensor(
"cond2", TensorFrom(arrow::boolean(),
"[true,true,false,false]")),
test::NamedTensor("cond3",
TensorFrom(arrow::int64(),
"[-11,-11,-11,0]"))},
.cond_status = {pb::TENSORSTATUS_PRIVATE,
pb::TENSORSTATUS_PRIVATE,
pb::TENSORSTATUS_PRIVATE},
.values =
{test::NamedTensor(
"value1", TensorFrom(arrow::large_utf8(),
R"json(["A","A","A","A"])json")),
test::NamedTensor(
"value2", TensorFrom(arrow::large_utf8(),
R"json(["B","B","B","B"])json")),
test::NamedTensor(
"value3", TensorFrom(arrow::large_utf8(),
R"json(["C","C","C","C"])json"))},
.value_status = {pb::TENSORSTATUS_PRIVATE,
pb::TENSORSTATUS_PRIVATE,
pb::TENSORSTATUS_PRIVATE},
.value_else = test::NamedTensor(
"value_else", TensorFrom(arrow::large_utf8(),
R"json(["D","D","D","D"])json")),
.value_else_status = pb::TENSORSTATUS_PRIVATE,
.expect_out = test::NamedTensor(
"out", TensorFrom(arrow::large_utf8(),
R"json(["A","B","C","D"])json")),
.expect_out_status = pb::TENSORSTATUS_PRIVATE},
CaseWhenTestCase{
.conds = {test::NamedTensor("cond1", TensorFrom(arrow::int64(),
"[1,0,0,0]")),
test::NamedTensor(
"cond2", TensorFrom(arrow::boolean(),
"[true,true,false,false]")),
test::NamedTensor("cond3",
TensorFrom(arrow::int64(),
"[-11,-11,-11,0]"))},
.cond_status = {pb::TENSORSTATUS_SECRET,
pb::TENSORSTATUS_PUBLIC,
pb::TENSORSTATUS_PUBLIC},
.values =
{test::NamedTensor(
"value1", TensorFrom(arrow::large_utf8(),
R"json(["A","A","A","A"])json")),
test::NamedTensor(
"value2", TensorFrom(arrow::large_utf8(),
R"json(["B","B","B","B"])json")),
test::NamedTensor(
"value3", TensorFrom(arrow::large_utf8(),
R"json(["C","C","C","C"])json"))},
.value_status = {pb::TENSORSTATUS_PUBLIC,
pb::TENSORSTATUS_SECRET,
pb::TENSORSTATUS_SECRET},
.value_else = test::NamedTensor(
"value_else", TensorFrom(arrow::large_utf8(),
R"json(["D","D","D","D"])json")),
.value_else_status = pb::TENSORSTATUS_PUBLIC,
.expect_out = test::NamedTensor(
"out", TensorFrom(arrow::large_utf8(),
R"json(["A","B","C","D"])json")),
.expect_out_status = pb::TENSORSTATUS_SECRET})),
TestParamNameGenerator(CaseWhenTest));
TEST_P(CaseWhenTest, works) {
// Given
auto parm = GetParam();
auto test_case = std::get<1>(parm);
auto node = MakeCaseWhenExecNode(test_case);
auto sessions = test::MakeMultiPCSession(std::get<0>(parm));
std::vector<ExecContext> exec_ctxs;
for (size_t idx = 0; idx < sessions.size(); ++idx) {
exec_ctxs.emplace_back(node, sessions[idx].get());
}
std::vector<ExecContext*> ctx_ptrs;
for (size_t idx = 0; idx < exec_ctxs.size(); ++idx) {
ctx_ptrs.emplace_back(&exec_ctxs[idx]);
}
FeedInputs(ctx_ptrs, test_case);
// When
if (test_case.expect_out_status == pb::TENSORSTATUS_PRIVATE) {
EXPECT_NO_THROW(test::RunAsync<CaseWhen>({ctx_ptrs[0]}));
} else {
EXPECT_NO_THROW(test::RunAsync<CaseWhen>(ctx_ptrs));
}
// Then check outputs
auto tensor_table = ctx_ptrs[0]->GetTensorTable();
TensorPtr out;
if (test_case.expect_out_status == pb::TENSORSTATUS_PRIVATE) {
EXPECT_NO_THROW(out = tensor_table->GetTensor(test_case.expect_out.name));
} else {
EXPECT_NO_THROW(
out = test::RevealSecret(ctx_ptrs, test_case.expect_out.name));
// convert hash to string for string tensor in spu
if (test_case.expect_out.tensor->Type() == pb::PrimitiveDataType::STRING) {
out = ctx_ptrs[0]->GetSession()->HashToString(*out);
}
}
EXPECT_TRUE(out != nullptr);
EXPECT_EQ(out->Length(), test_case.expect_out.tensor->Length());
EXPECT_EQ(out->GetNullCount(), test_case.expect_out.tensor->GetNullCount());
EXPECT_EQ(out->Type(), test_case.expect_out.tensor->Type());
// compare tensor content
EXPECT_TRUE(out->ToArrowChunkedArray()->Equals(
test_case.expect_out.tensor->ToArrowChunkedArray()));
}
struct CaseWhenConditionTestCase {
std::vector<test::NamedTensor> conds;
std::vector<test::NamedTensor> expect_out;
};
class CaseWhenConditionTest
: public ::testing::TestWithParam<
std::tuple<test::SpuRuntimeTestCase, CaseWhenConditionTestCase>> {};
INSTANTIATE_TEST_SUITE_P(
CaseWhenConditionShareTest, CaseWhenConditionTest,
testing::Combine(
test::SpuTestValuesMultiPC,
testing::Values(
CaseWhenConditionTestCase{
.conds = {test::NamedTensor("cond1", TensorFrom(arrow::int64(),
"[1,0,0,0]")),
test::NamedTensor(
"cond2", TensorFrom(arrow::boolean(),
"[true,true,false,false]")),
test::NamedTensor("cond3",
TensorFrom(arrow::int64(),
"[11,11,11,0]"))},
.expect_out =
{test::NamedTensor("out1",
TensorFrom(arrow::boolean(),
"[true,false,false,false]")),
test::NamedTensor("out2",
TensorFrom(arrow::boolean(),
"[false,true,false,false]")),
test::NamedTensor(
"out3", TensorFrom(arrow::boolean(),
"[false,false,true,false]")),
test::NamedTensor(
"out4", TensorFrom(arrow::boolean(),
"[false,false,false,true]"))}},
CaseWhenConditionTestCase{
.conds = {test::NamedTensor("cond1", TensorFrom(arrow::int64(),
"[-1,0,1,0]")),
test::NamedTensor(
"cond2", TensorFrom(arrow::boolean(),
"[true,false,false,false]")),
test::NamedTensor("cond3", TensorFrom(arrow::int64(),
"[3,3,3,3]"))},
.expect_out =
{test::NamedTensor(
"out1", TensorFrom(arrow::boolean(),
"[true,false,true,false]")),
test::NamedTensor(
"out2", TensorFrom(arrow::boolean(),
"[false,false,false,false]")),
test::NamedTensor(
"out3", TensorFrom(arrow::boolean(),
"[false,true,false,true]")),
test::NamedTensor(
"out4", TensorFrom(arrow::boolean(),
"[false,false,false,false]"))}},
CaseWhenConditionTestCase{
.conds = {test::NamedTensor("cond1", TensorFrom(arrow::int64(),
"[0,0,0,0]")),
test::NamedTensor(
"cond2", TensorFrom(arrow::boolean(),
"[false,false,false,false]")),
test::NamedTensor("cond3", TensorFrom(arrow::int64(),
"[0,0,0,0]"))},
.expect_out =
{test::NamedTensor(
"out1", TensorFrom(arrow::boolean(),
"[false,false,false,false]")),
test::NamedTensor(
"out2", TensorFrom(arrow::boolean(),
"[false,false,false,false]")),
test::NamedTensor(
"out3", TensorFrom(arrow::boolean(),
"[false,false,false,false]")),
test::NamedTensor(
"out4", TensorFrom(arrow::boolean(),
"[true,true,true,true]"))}})),
TestParamNameGenerator(CaseWhenConditionTest));
TEST_P(CaseWhenConditionTest, condition) {
// Given
auto parm = GetParam();
auto test_case = std::get<1>(parm);
test::ExecNodeBuilder builder(CaseWhen::kOpType);
builder.SetNodeName("case_when_condition-test");
// Build node
std::vector<pb::Tensor> conds;
for (size_t i = 0; i < test_case.conds.size(); i++) {
auto t = test::MakeTensorReference(test_case.conds[i].name,
test_case.conds[i].tensor->Type(),
pb::TENSORSTATUS_PUBLIC);
conds.push_back(std::move(t));
}
builder.AddInput(CaseWhen::kCond, conds);
auto node = builder.Build();
auto sessions = test::MakeMultiPCSession(std::get<0>(parm));
std::vector<ExecContext> exec_ctxs;
for (size_t idx = 0; idx < sessions.size(); ++idx) {
exec_ctxs.emplace_back(node, sessions[idx].get());
}
std::vector<ExecContext*> ctx_ptrs;
for (size_t idx = 0; idx < exec_ctxs.size(); ++idx) {
ctx_ptrs.emplace_back(&exec_ctxs[idx]);
}
test::FeedInputsAsPublic(ctx_ptrs, test_case.conds);
auto CaseWhenOp = std::make_unique<CaseWhen>();
auto result = CaseWhenOp->TransformConditionData(ctx_ptrs[0]);
for (size_t i = 0; i < result.size(); i++) {
spu::NdArrayRef arr = spu::kernel::hal::dump_public(
ctx_ptrs[0]->GetSession()->GetSpuContext(), result[i]);
auto arrow = util::NdArrayToArrow(arr);
EXPECT_TRUE(arrow->Equals(
test_case.expect_out.at(i).tensor->ToArrowChunkedArray()));
}
}
/// ===========================
/// CaseWhenTest impl
/// ===========================
pb::ExecNode CaseWhenTest::MakeCaseWhenExecNode(const CaseWhenTestCase& tc) {
test::ExecNodeBuilder builder(CaseWhen::kOpType);
builder.SetNodeName("case_when-test");
// Add inputs
std::vector<pb::Tensor> conds;
for (size_t i = 0; i < tc.conds.size(); i++) {
auto t = test::MakeTensorReference(
tc.conds[i].name, tc.conds[i].tensor->Type(), tc.cond_status[i]);
conds.push_back(std::move(t));
}
builder.AddInput(CaseWhen::kCond, conds);
std::vector<pb::Tensor> values;
for (size_t i = 0; i < tc.values.size(); i++) {
auto t = test::MakeTensorReference(
tc.values[i].name, tc.values[i].tensor->Type(), tc.value_status[i]);
values.push_back(std::move(t));
}
builder.AddInput(CaseWhen::kValue, values);
auto value_else = test::MakeTensorReference(
tc.value_else.name, tc.value_else.tensor->Type(), tc.value_else_status);
builder.AddInput(CaseWhen::kValueElse, std::vector<pb::Tensor>{value_else});
// Add outputs
auto out = test::MakeTensorReference(
tc.expect_out.name, tc.expect_out.tensor->Type(), tc.expect_out_status);
builder.AddOutput(CaseWhen::kOut, std::vector<pb::Tensor>{out});
return builder.Build();
}
void CaseWhenTest::FeedTensors(const std::vector<ExecContext*>& ctxs,
const std::vector<test::NamedTensor>& ts,
const std::vector<pb::TensorStatus>& status) {
for (size_t i = 0; i < ts.size(); i++) {
if (status[i] == pb::TENSORSTATUS_PRIVATE) {
test::FeedInputsAsPrivate(ctxs[0], {ts[i]});
} else if (status[i] == pb::TENSORSTATUS_SECRET) {
test::FeedInputsAsSecret(ctxs, {ts[i]});
} else {
test::FeedInputsAsPublic(ctxs, {ts[i]});
}
}
}
void CaseWhenTest::FeedInputs(const std::vector<ExecContext*>& ctxs,
const CaseWhenTestCase& tc) {
FeedTensors(ctxs, tc.conds, tc.cond_status);
FeedTensors(ctxs, tc.values, tc.value_status);
FeedTensors(ctxs, {tc.value_else}, {tc.value_else_status});
}
} // namespace scql::engine::op