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// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#include <vespa/eval/eval/fast_value.h>
#include <vespa/eval/eval/value_codec.h>
#include <vespa/eval/eval/interpreted_function.h>
#include <vespa/eval/eval/tensor_function.h>
#include <vespa/eval/instruction/universal_dot_product.h>
#include <vespa/eval/eval/test/reference_operations.h>
#include <vespa/eval/eval/test/gen_spec.h>
#include <vespa/vespalib/util/stringfmt.h>
#include <vespa/vespalib/gtest/gtest.h>
using namespace vespalib;
using namespace vespalib::eval;
using namespace vespalib::eval::test;
using vespalib::make_string_short::fmt;
const ValueBuilderFactory &prod_factory = FastValueBuilderFactory::get();
GenSpec::seq_t N_16ths = [] (size_t i) noexcept { return (i + 33.0) / 16.0; };
GenSpec G() { return GenSpec().seq(N_16ths); }
const std::vector<GenSpec> layouts = {
G(), G(),
G().idx("x", 5), G().idx("x", 5),
G().idx("x", 5), G().idx("y", 5),
G().idx("x", 5), G().idx("x", 5).idx("y", 5),
G().idx("y", 3), G().idx("x", 2).idx("z", 3),
G().idx("x", 3).idx("y", 5), G().idx("y", 5).idx("z", 7),
G().map("x", {"a","b","c"}), G().map("x", {"a","b","c"}),
G().map("x", {"a","b","c"}), G().map("x", {"a","b"}),
G().map("x", {"a","b","c"}), G().map("y", {"foo","bar","baz"}),
G().map("x", {"a","b","c"}), G().map("x", {"a","b","c"}).map("y", {"foo","bar","baz"}),
G().map("x", {"a","b"}).map("y", {"foo","bar","baz"}), G().map("x", {"a","b","c"}).map("y", {"foo","bar"}),
G().map("x", {"a","b"}).map("y", {"foo","bar","baz"}), G().map("y", {"foo","bar"}).map("z", {"i","j","k","l"}),
G().idx("x", 3).map("y", {"foo", "bar"}), G().map("y", {"foo", "bar"}).idx("z", 7),
G().map("x", {"a","b","c"}).idx("y", 5), G().idx("y", 5).map("z", {"i","j","k","l"})
};
const std::vector<std::vector<vespalib::string>> reductions = {
{}, {"x"}, {"y"}, {"z"}, {"x", "y"}, {"x", "z"}, {"y", "z"}
};
TensorSpec perform_dot_product(const TensorSpec &a, const TensorSpec &b, const std::vector<vespalib::string> &dims)
{
Stash stash;
auto lhs = value_from_spec(a, prod_factory);
auto rhs = value_from_spec(b, prod_factory);
auto res_type = ValueType::join(lhs->type(), rhs->type()).reduce(dims);
EXPECT_FALSE(res_type.is_error());
UniversalDotProduct dot_product(res_type,
tensor_function::inject(lhs->type(), 0, stash),
tensor_function::inject(rhs->type(), 1, stash));
auto my_op = dot_product.compile_self(prod_factory, stash);
InterpretedFunction::EvalSingle single(prod_factory, my_op);
return spec_from_value(single.eval(std::vector<Value::CREF>({*lhs,*rhs})));
}
TEST(UniversalDotProductTest, generic_dot_product_works_for_various_cases) {
size_t test_cases = 0;
ASSERT_TRUE((layouts.size() % 2) == 0);
for (size_t i = 0; i < layouts.size(); i += 2) {
const auto &l = layouts[i];
const auto &r = layouts[i+1];
for (CellType lct : CellTypeUtils::list_types()) {
auto lhs = l.cpy().cells(lct);
if (lhs.bad_scalar()) continue;
for (CellType rct : CellTypeUtils::list_types()) {
auto rhs = r.cpy().cells(rct);
if (rhs.bad_scalar()) continue;
for (const std::vector<vespalib::string> &dims: reductions) {
if (ValueType::join(lhs.type(), rhs.type()).reduce(dims).is_error()) continue;
++test_cases;
SCOPED_TRACE(fmt("\n===\nLHS: %s\nRHS: %s\n===\n", lhs.gen().to_string().c_str(), rhs.gen().to_string().c_str()));
auto expect = ReferenceOperations::reduce(ReferenceOperations::join(lhs, rhs, operation::Mul::f), Aggr::SUM, dims);
auto actual = perform_dot_product(lhs, rhs, dims);
// fprintf(stderr, "\n===\nLHS: %s\nRHS: %s\n===\nRESULT: %s\n===\n", lhs.gen().to_string().c_str(), rhs.gen().to_string().c_str(), actual.to_string().c_str());
EXPECT_EQ(actual, expect);
}
}
}
}
EXPECT_GT(test_cases, 500);
fprintf(stderr, "total test cases run: %zu\n", test_cases);
}
GTEST_MAIN_RUN_ALL_TESTS()
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