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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_operations.h>
#include <vespa/eval/eval/simple_value.h>
#include <vespa/eval/eval/tensor_spec.h>
#include <vespa/eval/eval/value.h>
#include <vespa/eval/eval/value_codec.h>
#include <vespa/eval/streamed/streamed_value_builder_factory.h>
#include <vespa/vespalib/gtest/gtest.h>
using search::tensor::TensorBufferOperations;
using vespalib::eval::SimpleValue;
using vespalib::eval::StreamedValueBuilderFactory;
using vespalib::eval::TensorSpec;
using vespalib::eval::Value;
using vespalib::eval::ValueType;
using vespalib::eval::TypedCells;
const vespalib::string tensor_type_spec("tensor(x{})");
const vespalib::string tensor_type_2d_spec("tensor(x{},y{})");
const vespalib::string tensor_type_2d_mixed_spec("tensor(x{},y[2])");
const vespalib::string float_tensor_type_spec("tensor<float>(y{})");
struct TestParam
{
vespalib::string _name;
std::vector<size_t> _array_sizes;
TensorSpec _tensor_spec;
TestParam(vespalib::string name, std::vector<size_t> array_sizes, TensorSpec tensor_spec)
: _name(std::move(name)),
_array_sizes(std::move(array_sizes)),
_tensor_spec(std::move(tensor_spec))
{
}
TestParam(const TestParam&);
~TestParam();
};
TestParam::TestParam(const TestParam&) = default;
TestParam::~TestParam() = default;
std::ostream& operator<<(std::ostream& os, const TestParam& param)
{
os << param._name;
return os;
}
class TensorBufferOperationsTest : public testing::TestWithParam<TestParam>
{
protected:
ValueType _tensor_type;
TensorBufferOperations _ops;
TensorBufferOperationsTest();
~TensorBufferOperationsTest() override;
std::vector<size_t> get_array_sizes(uint32_t max_subspaces);
std::vector<char> store_tensor(const Value& tensor);
std::vector<char> store_tensor(const TensorSpec& spec);
std::unique_ptr<Value> load_tensor(vespalib::ConstArrayRef<char> buf);
TensorSpec load_tensor_spec(vespalib::ConstArrayRef<char> buf);
vespalib::nbostream encode_stored_tensor(vespalib::ConstArrayRef<char> buf);
void assert_store_load(const TensorSpec& tensor_spec);
void assert_store_copy_load(const TensorSpec& tensor_spec);
void assert_store_encode_decode(const TensorSpec& tensor_spec);
};
TensorBufferOperationsTest::TensorBufferOperationsTest()
: testing::TestWithParam<TestParam>(),
_tensor_type(ValueType::from_spec(GetParam()._tensor_spec.type())),
_ops(_tensor_type)
{
}
TensorBufferOperationsTest::~TensorBufferOperationsTest() = default;
std::vector<size_t>
TensorBufferOperationsTest::get_array_sizes(uint32_t max_subspaces)
{
std::vector<size_t> array_sizes;
for (uint32_t num_subspaces = 0; num_subspaces < max_subspaces; ++num_subspaces) {
array_sizes.emplace_back(_ops.get_array_size(num_subspaces));
}
return array_sizes;
}
std::vector<char>
TensorBufferOperationsTest::store_tensor(const Value& tensor)
{
EXPECT_EQ(_tensor_type, tensor.type());
uint32_t num_subspaces = tensor.index().size();
auto array_size = _ops.get_array_size(num_subspaces);
std::vector<char> buf;
buf.resize(array_size);
_ops.store_tensor(buf, tensor);
return buf;
}
std::vector<char>
TensorBufferOperationsTest::store_tensor(const TensorSpec& spec)
{
auto tensor = SimpleValue::from_spec(spec);
return store_tensor(*tensor);
}
std::unique_ptr<Value>
TensorBufferOperationsTest::load_tensor(vespalib::ConstArrayRef<char> buf)
{
return _ops.make_fast_view(buf, _tensor_type);
}
vespalib::nbostream
TensorBufferOperationsTest::encode_stored_tensor(vespalib::ConstArrayRef<char> buf)
{
vespalib::nbostream out;
_ops.encode_stored_tensor(buf, _tensor_type, out);
return out;
}
TensorSpec
TensorBufferOperationsTest::load_tensor_spec(vespalib::ConstArrayRef<char> buf)
{
auto loaded = load_tensor(buf);
return TensorSpec::from_value(*loaded);
}
void
TensorBufferOperationsTest::assert_store_load(const TensorSpec& tensor_spec)
{
auto buf = store_tensor(tensor_spec);
auto loaded_spec = load_tensor_spec(buf);
_ops.reclaim_labels(buf);
EXPECT_EQ(tensor_spec, loaded_spec);
}
void
TensorBufferOperationsTest::assert_store_copy_load(const TensorSpec& tensor_spec)
{
auto buf = store_tensor(tensor_spec);
auto buf2 = buf;
_ops.copied_labels(buf);
EXPECT_NE(buf, buf2);
_ops.reclaim_labels(buf);
buf.clear();
auto loaded_spec = load_tensor_spec(buf2);
_ops.reclaim_labels(buf2);
EXPECT_EQ(tensor_spec, loaded_spec);
}
void
TensorBufferOperationsTest::assert_store_encode_decode(const TensorSpec& tensor_spec)
{
auto buf = store_tensor(tensor_spec);
auto encoded = encode_stored_tensor(buf);
_ops.reclaim_labels(buf);
const auto& factory = StreamedValueBuilderFactory::get();
auto decoded = vespalib::eval::decode_value(encoded, factory);
auto decoded_spec = TensorSpec::from_value(*decoded);
EXPECT_EQ(tensor_spec, decoded_spec);
}
INSTANTIATE_TEST_SUITE_P(TensorBufferOperationsMultiTest,
TensorBufferOperationsTest,
testing::Values(TestParam("1d", {8, 16, 32, 40, 64}, TensorSpec(tensor_type_spec).add({{"x", "a"}}, 4.5)),
TestParam("1dmulti", {8, 16, 32, 40, 64}, TensorSpec(tensor_type_spec).add({{"x", "a"}}, 4.5).add({{"x", "c"}}, 4.25)),
TestParam("1dfloat", {4, 12, 20, 28, 36}, TensorSpec(float_tensor_type_spec).add({{"y", "aa"}}, 4.25)),
TestParam("2d", {8, 24, 40, 56, 80}, TensorSpec(tensor_type_2d_spec).add({{"x", "a"},{"y", "aa"}}, 4.75)),
TestParam("2dmixed", {8, 24, 48, 64, 96}, TensorSpec(tensor_type_2d_mixed_spec).add({{"x", "a"},{"y", 0}}, 4.5).add({{"x", "a"},{"y", 1}}, 4.25))),
testing::PrintToStringParamName());
TEST_P(TensorBufferOperationsTest, array_sizes_are_calculated)
{
EXPECT_EQ(GetParam()._array_sizes, get_array_sizes(5));
}
TEST_P(TensorBufferOperationsTest, tensor_can_be_stored_and_loaded)
{
assert_store_load(GetParam()._tensor_spec);
}
TEST_P(TensorBufferOperationsTest, tensor_buffer_can_be_copied)
{
assert_store_copy_load(GetParam()._tensor_spec);
}
TEST_P(TensorBufferOperationsTest, tensor_buffer_can_be_encoded)
{
assert_store_encode_decode(GetParam()._tensor_spec);
}
GTEST_MAIN_RUN_ALL_TESTS()
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