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// Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#include <vespa/vespalib/testkit/test_kit.h>
#include <vespa/eval/tensor/sparse/sparse_tensor.h>
#include <vespa/eval/tensor/sparse/sparse_tensor_builder.h>
#include <vespa/eval/tensor/types.h>
#include <vespa/eval/tensor/default_tensor.h>
#include <vespa/eval/tensor/tensor_factory.h>
#include <vespa/eval/tensor/serialization/typed_binary_format.h>
#include <vespa/eval/tensor/serialization/slime_binary_format.h>
#include <vespa/vespalib/data/slime/slime.h>
#include <iostream>
using namespace vespalib::tensor;
template <typename BuilderType>
struct Fixture
{
BuilderType _builder;
Fixture() : _builder() {}
Tensor::UP createTensor(const TensorCells &cells) {
return vespalib::tensor::TensorFactory::create(cells, _builder);
}
Tensor::UP createTensor(const TensorCells &cells, const TensorDimensions &dimensions) {
return TensorFactory::create(cells, dimensions, _builder);
}
static inline uint32_t getTensorTypeId();
void assertSerialized(const vespalib::string &exp, const TensorCells &rhs,
const TensorDimensions &rhsDimensions) {
Tensor::UP rhsTensor(createTensor(rhs, rhsDimensions));
auto slime = SlimeBinaryFormat::serialize(*rhsTensor);
vespalib::Memory memory_exp(exp);
vespalib::Slime expSlime;
size_t used = vespalib::slime::JsonFormat::decode(memory_exp, expSlime);
EXPECT_TRUE(used > 0);
EXPECT_EQUAL(expSlime, *slime);
}
};
template <>
uint32_t
Fixture<SparseTensorBuilder>::getTensorTypeId() { return 2u; }
using SparseFixture = Fixture<SparseTensorBuilder>;
namespace {
vespalib::string twoCellsJson[3] =
{
"{ dimensions: [ 'x', 'y' ],"
" cells: ["
"{ address: { y:'3'}, value: 4.0 },"
"{ address: { x:'1'}, value: 3.0 }"
"] }",
"{ dimensions: [ 'x', 'y' ],"
" cells: ["
"{ address: { x:'1'}, value: 3.0 },"
"{ address: { y:'3'}, value: 4.0 }"
"] }",
"{ dimensions: [ 'x', 'y' ],"
" cells: ["
"{ address: { x:'1'}, value: 3.0 },"
"{ address: { y:'3'}, value: 4.0 }"
"] }",
};
}
template <typename FixtureType>
void
testTensorSlimeSerialization(FixtureType &f)
{
TEST_DO(f.assertSerialized("{ dimensions: [], cells: [] }", {}, {}));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x' ], cells: [] }",
{}, { "x" }));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x', 'y' ], cells: [] }",
{}, { "x", "y" }));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x' ],"
"cells: ["
"{ address: { x: '1' }, value: 3.0 }"
"] }",
{ {{{"x","1"}}, 3} }, { "x" }));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x', 'y' ],"
" cells: ["
"{ address: { }, value: 3.0 }"
"] }",
{ {{}, 3} }, { "x", "y"}));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x', 'y' ],"
" cells: ["
"{ address: { x: '1' }, value: 3.0 }"
"] }",
{ {{{"x","1"}}, 3} }, { "x", "y" }));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x', 'y' ],"
" cells: ["
"{ address: { y: '3' }, value: 3.0 }"
"] }",
{ {{{"y","3"}}, 3} }, { "x", "y" }));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x', 'y' ],"
" cells: ["
"{ address: { x:'2', y:'4'}, value: 3.0 }"
"] }",
{ {{{"x","2"}, {"y", "4"}}, 3} }, { "x", "y" }));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x', 'y' ],"
" cells: ["
"{ address: { x:'1'}, value: 3.0 }"
"] }",
{ {{{"x","1"}}, 3} }, {"x", "y"}));
TEST_DO(f.assertSerialized(twoCellsJson[FixtureType::getTensorTypeId()],
{ {{{"x","1"}}, 3}, {{{"y","3"}}, 4} },
{"x", "y"}));
}
TEST_F("test tensor slime serialization for SparseTensor", SparseFixture)
{
testTensorSlimeSerialization(f);
}
struct DenseFixture
{
DenseFixture() {}
Tensor::UP createTensor(const DenseTensorCells &cells) {
return vespalib::tensor::TensorFactory::createDense(cells);
}
void assertSerialized(const vespalib::string &exp,
const DenseTensorCells &rhs) {
Tensor::UP rhsTensor(createTensor(rhs));
auto slime = SlimeBinaryFormat::serialize(*rhsTensor);
vespalib::Memory memory_exp(exp);
vespalib::Slime expSlime;
size_t used = vespalib::slime::JsonFormat::decode(memory_exp, expSlime);
EXPECT_TRUE(used > 0);
EXPECT_EQUAL(expSlime, *slime);
}
};
TEST_F("test tensor slime serialization for DenseTensor", DenseFixture)
{
TEST_DO(f.assertSerialized("{ dimensions: [], cells: ["
"{ address: { }, value: 0.0 }"
"] }", {}));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x' ], cells: ["
"{ address: { x: '0' }, value: 0.0 }"
"] }",
{ {{{"x",0}}, 0} }));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x', 'y' ], cells: ["
"{ address: { x: '0', y: '0' }, value: 0.0 }"
"] }",
{ {{{"x",0},{"y",0}}, 0} }));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x' ],"
"cells: ["
"{ address: { x: '0' }, value: 0.0 },"
"{ address: { x: '1' }, value: 3.0 }"
"] }",
{ {{{"x",1}}, 3} }));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x', 'y' ],"
" cells: ["
"{ address: { x: '0', y: '0' }, value: 3.0 }"
"] }",
{ {{{"x",0},{"y",0}}, 3} }));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x', 'y' ],"
" cells: ["
"{ address: { x: '0', y: '0' }, value: 0.0 },"
"{ address: { x: '1', y: '0' }, value: 3.0 }"
"] }",
{ {{{"x",1},{"y", 0}}, 3} }));
TEST_DO(f.assertSerialized("{ dimensions: [ 'x', 'y' ],"
" cells: ["
"{ address: { x: '0', y: '0' }, value: 0.0 },"
"{ address: { x: '0', y: '1' }, value: 0.0 },"
"{ address: { x: '0', y: '2' }, value: 0.0 },"
"{ address: { x: '0', y: '3' }, value: 3.0 }"
"] }",
{ {{{"x",0},{"y",3}}, 3} }));
}
TEST_MAIN() { TEST_RUN_ALL(); }
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