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// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#include <vespa/searchlib/tensor/tensor_buffer_store.h>
#include <vespa/eval/eval/fast_value.h>
#include <vespa/eval/eval/tensor_spec.h>
#include <vespa/eval/eval/value.h>
#include <vespa/eval/eval/value_codec.h>
#include <vespa/vespalib/gtest/gtest.h>
using search::tensor::TensorBufferStore;
using vespalib::datastore::EntryRef;
using vespalib::eval::FastValueBuilderFactory;
using vespalib::eval::TensorSpec;
using vespalib::eval::Value;
using vespalib::eval::ValueType;
const vespalib::string tensor_type_spec("tensor(x{})");
class TensorBufferStoreTest : public testing::Test
{
protected:
ValueType _tensor_type;
TensorBufferStore _store;
TensorBufferStoreTest();
~TensorBufferStoreTest() override;
EntryRef store_tensor(const Value& tensor);
EntryRef store_tensor(const TensorSpec& spec);
std::unique_ptr<Value> load_tensor(EntryRef ref);
TensorSpec load_tensor_spec(EntryRef ref);
vespalib::nbostream encode_stored_tensor(EntryRef ref);
void assert_store_load(const TensorSpec& tensor_spec);
void assert_store_load_many(const TensorSpec& tensor_spec);
void assert_store_move_on_compact_load(const TensorSpec& tensor_spec);
void assert_store_encode_store_encoded_load(const TensorSpec& tensor_spec);
};
TensorBufferStoreTest::TensorBufferStoreTest()
: testing::Test(),
_tensor_type(ValueType::from_spec(tensor_type_spec)),
_store(_tensor_type, {}, 4)
{
}
TensorBufferStoreTest::~TensorBufferStoreTest() = default;
EntryRef
TensorBufferStoreTest::store_tensor(const Value& tensor)
{
EXPECT_EQ(_tensor_type, tensor.type());
return _store.store_tensor(tensor);
}
EntryRef
TensorBufferStoreTest::store_tensor(const TensorSpec& spec)
{
auto tensor = value_from_spec(spec, FastValueBuilderFactory::get());
return store_tensor(*tensor);
}
std::unique_ptr<Value>
TensorBufferStoreTest::load_tensor(EntryRef ref)
{
return _store.get_tensor(ref);
}
vespalib::nbostream
TensorBufferStoreTest::encode_stored_tensor(EntryRef ref)
{
vespalib::nbostream out;
_store.encode_stored_tensor(ref, out);
return out;
}
TensorSpec
TensorBufferStoreTest::load_tensor_spec(EntryRef ref)
{
auto loaded = load_tensor(ref);
return TensorSpec::from_value(*loaded);
}
void
TensorBufferStoreTest::assert_store_load(const TensorSpec& tensor_spec)
{
auto ref = store_tensor(tensor_spec);
auto loaded_spec = load_tensor_spec(ref);
_store.holdTensor(ref);
EXPECT_EQ(tensor_spec, loaded_spec);
}
void
TensorBufferStoreTest::assert_store_load_many(const TensorSpec& tensor_spec)
{
constexpr uint32_t cnt = 2000;
std::vector<EntryRef> refs;
for (uint32_t i = 0; i < cnt; ++i) {
refs.emplace_back(store_tensor(tensor_spec));
}
for (auto ref : refs) {
auto loaded_spec = load_tensor_spec(ref);
_store.holdTensor(ref);
EXPECT_EQ(tensor_spec, loaded_spec);
}
}
void
TensorBufferStoreTest::assert_store_move_on_compact_load(const TensorSpec& tensor_spec)
{
auto ref = store_tensor(tensor_spec);
auto ref2 = _store.move_on_compact(ref);
EXPECT_NE(ref, ref2);
auto loaded_spec = load_tensor_spec(ref2);
_store.holdTensor(ref2);
EXPECT_EQ(tensor_spec, loaded_spec);
}
void
TensorBufferStoreTest::assert_store_encode_store_encoded_load(const TensorSpec& tensor_spec)
{
auto ref = store_tensor(tensor_spec);
auto encoded = encode_stored_tensor(ref);
_store.holdTensor(ref);
auto ref2 = _store.store_encoded_tensor(encoded);
EXPECT_NE(ref, ref2);
auto loaded_spec = load_tensor_spec(ref2);
_store.holdTensor(ref2);
EXPECT_EQ(tensor_spec, loaded_spec);
}
std::vector<TensorSpec> tensor_specs = {
TensorSpec(tensor_type_spec),
TensorSpec(tensor_type_spec).add({{"x", "a"}}, 4.5),
TensorSpec(tensor_type_spec).add({{"x", "a"}}, 4.5).add({{"x", "b"}}, 5.5),
TensorSpec(tensor_type_spec).add({{"x", "a"}}, 4.5).add({{"x", "b"}}, 5.5).add({{"x", "c"}}, 6.5),
TensorSpec(tensor_type_spec).add({{"x", "a"}}, 4.5).add({{"x", "b"}}, 5.5).add({{"x", "c"}}, 6.5).add({{"x", "d"}}, 7.5)
};
TEST_F(TensorBufferStoreTest, tensor_can_be_stored_and_loaded)
{
for (auto& tensor_spec : tensor_specs) {
assert_store_load(tensor_spec);
}
}
TEST_F(TensorBufferStoreTest, tensor_can_be_stored_and_loaded_many_times)
{
for (auto& tensor_spec : tensor_specs) {
assert_store_load_many(tensor_spec);
}
}
TEST_F(TensorBufferStoreTest, stored_tensor_can_be_moved_on_compact)
{
for (auto& tensor_spec : tensor_specs) {
assert_store_move_on_compact_load(tensor_spec);
}
}
TEST_F(TensorBufferStoreTest, stored_tensor_can_be_encoded_and_stored_as_encoded_and_loaded)
{
for (auto& tensor_spec : tensor_specs) {
assert_store_encode_store_encoded_load(tensor_spec);
}
}
TEST_F(TensorBufferStoreTest, get_vectors)
{
auto ref = store_tensor(tensor_specs.back());
std::vector<double> values;
auto vectors = _store.get_vectors(ref);
EXPECT_EQ(4, vectors.subspaces());
for (uint32_t subspace = 0; subspace < 4; ++subspace) {
auto cells = vectors.cells(subspace).typify<double>();
EXPECT_EQ(1, cells.size());
values.emplace_back(cells[0]);
}
EXPECT_EQ((std::vector<double>{4.5, 5.5, 6.5, 7.5}), values);
EXPECT_EQ(0, _store.get_vectors(EntryRef()).subspaces());
}
GTEST_MAIN_RUN_ALL_TESTS()
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