1 files changed, 108 insertions, 0 deletions
diff --git a/eval/src/tests/instruction/add_trivial_dimension_optimizer/add_trivial_dimension_optimizer_test.cpp b/eval/src/tests/instruction/add_trivial_dimension_optimizer/add_trivial_dimension_optimizer_test.cpp
new file mode 100644
index 00000000000..35195522adc
--- /dev/null
+++ b/eval/src/tests/instruction/add_trivial_dimension_optimizer/add_trivial_dimension_optimizer_test.cpp
@@ -0,0 +1,108 @@
+// Copyright 2018 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/eval/fast_value.h>
+#include <vespa/eval/eval/tensor_function.h>
+#include <vespa/eval/instruction/replace_type_function.h>
+#include <vespa/eval/instruction/fast_rename_optimizer.h>
+#include <vespa/eval/eval/test/tensor_model.hpp>
+#include <vespa/eval/eval/test/eval_fixture.h>
+
+#include <vespa/vespalib/util/stringfmt.h>
+#include <vespa/vespalib/util/stash.h>
+
+using namespace vespalib;
+using namespace vespalib::eval;
+using namespace vespalib::eval::test;
+using namespace vespalib::eval::tensor_function;
+
+const ValueBuilderFactory &prod_factory = FastValueBuilderFactory::get();
+
+EvalFixture::ParamRepo make_params() {
+    return EvalFixture::ParamRepo()
+        .add("x5", spec({x(5)}, N()))
+        .add("x5f", spec(float_cells({x(5)}), N()))
+        .add("x5y1", spec({x(5),y(1)}, N()))
+        .add("y1z1", spec({y(1),z(1)}, N()))
+        .add("x_m", spec({x({"a"})}, N()));
+}
+EvalFixture::ParamRepo param_repo = make_params();
+
+void verify_optimized(const vespalib::string &expr) {
+    EvalFixture fixture(prod_factory, expr, param_repo, true);
+    EXPECT_EQUAL(fixture.result(), EvalFixture::ref(expr, param_repo));
+    auto info = fixture.find_all<ReplaceTypeFunction>();
+    EXPECT_EQUAL(info.size(), 1u);
+}
+
+void verify_not_optimized(const vespalib::string &expr) {
+    EvalFixture fixture(prod_factory, expr, param_repo, true);
+    EXPECT_EQUAL(fixture.result(), EvalFixture::ref(expr, param_repo));
+    auto info = fixture.find_all<ReplaceTypeFunction>();
+    EXPECT_TRUE(info.empty());
+}
+
+TEST("require that dimension addition can be optimized") {
+    TEST_DO(verify_optimized("join(x5,tensor(y[1])(1),f(a,b)(a*b))"));
+    TEST_DO(verify_optimized("join(tensor(y[1])(1),x5,f(a,b)(a*b))"));
+    TEST_DO(verify_optimized("x5*tensor(y[1])(1)"));
+    TEST_DO(verify_optimized("tensor(y[1])(1)*x5"));
+    TEST_DO(verify_optimized("x5y1*tensor(z[1])(1)"));
+    TEST_DO(verify_optimized("tensor(z[1])(1)*x5y1"));
+}
+
+TEST("require that multi-dimension addition can be optimized") {
+    TEST_DO(verify_optimized("x5*tensor(a[1],b[1],c[1])(1)"));
+}
+
+TEST("require that dimension addition can be chained (and compacted)") {
+    TEST_DO(verify_optimized("tensor(z[1])(1)*x5*tensor(y[1])(1)"));
+}
+
+TEST("require that constant dimension addition is optimized") {
+    TEST_DO(verify_optimized("tensor(x[1])(1)*tensor(y[1])(1)"));
+    TEST_DO(verify_optimized("tensor(x[1])(1.1)*tensor(y[1])(1)"));
+    TEST_DO(verify_optimized("tensor(x[1])(1)*tensor(y[1])(1.1)"));
+    TEST_DO(verify_optimized("tensor(x[2])(1)*tensor(y[1])(1)"));
+    TEST_DO(verify_optimized("tensor(x[1])(1)*tensor(y[2])(1)"));
+}
+
+TEST("require that non-canonical dimension addition is not optimized") {
+    TEST_DO(verify_not_optimized("x5+tensor(y[1])(0)"));
+    TEST_DO(verify_not_optimized("tensor(y[1])(0)+x5"));
+    TEST_DO(verify_not_optimized("x5-tensor(y[1])(0)"));
+    TEST_DO(verify_not_optimized("x5/tensor(y[1])(1)"));
+    TEST_DO(verify_not_optimized("tensor(y[1])(1)/x5"));
+}
+
+TEST("require that dimension addition with overlapping dimensions is optimized") {
+    TEST_DO(verify_optimized("x5y1*tensor(y[1],z[1])(1)"));
+    TEST_DO(verify_optimized("tensor(y[1],z[1])(1)*x5y1"));
+}
+
+TEST("require that dimension addition with mixed dimensions is optimized") {
+    TEST_DO(verify_optimized("x_m*tensor(y[1])(1)"));
+    TEST_DO(verify_optimized("tensor(y[1])(1)*x_m"));
+}
+
+TEST("require that dimension addition optimization requires unit constant tensor") {
+    TEST_DO(verify_not_optimized("x5*tensor(y[1])(0.9)"));
+    TEST_DO(verify_not_optimized("tensor(y[1])(1.1)*x5"));
+    TEST_DO(verify_not_optimized("x5*tensor(y[1],z[2])(1)"));
+    TEST_DO(verify_not_optimized("tensor(y[1],z[2])(1)*x5"));
+    TEST_DO(verify_not_optimized("x5*y1z1"));
+    TEST_DO(verify_not_optimized("y1z1*x5"));
+    TEST_DO(verify_not_optimized("tensor(x[1])(1.1)*tensor(y[1])(1.1)"));
+    TEST_DO(verify_not_optimized("tensor(x[2])(1)*tensor(y[2])(1)"));
+}
+
+TEST("require that optimization also works for float cells") {
+    TEST_DO(verify_optimized("x5*tensor<float>(a[1],b[1],c[1])(1)"));
+    TEST_DO(verify_optimized("x5f*tensor<float>(a[1],b[1],c[1])(1)"));
+}
+
+TEST("require that optimization is disabled if unit vector would promote tensor cell types") {
+    TEST_DO(verify_not_optimized("x5f*tensor(a[1],b[1],c[1])(1)"));
+}
+
+TEST_MAIN() { TEST_RUN_ALL(); }