handle tensor lambda as nested function with bindings

3 files changed, 112 insertions, 7 deletions

diff --git a/eval/src/tests/eval/function/function_test.cpp b/eval/src/tests/eval/function/function_test.cpp
index 5316217d549..11fd8abf549 100644
--- a/eval/src/tests/eval/function/function_test.cpp
+++ b/eval/src/tests/eval/function/function_test.cpp
@@ -813,8 +813,8 @@ TEST("require that tensor rename dimension lists must have equal size") {
 //-----------------------------------------------------------------------------
 
 TEST("require that tensor lambda can be parsed") {
-    EXPECT_EQUAL("tensor(x[3]):{{x:0}:0,{x:1}:1,{x:2}:2}", Function::parse({}, "tensor(x[3])(x)")->dump());
-    EXPECT_EQUAL("tensor(x[2],y[2]):{{x:0,y:0}:(0==0),{x:0,y:1}:(0==1),{x:1,y:0}:(1==0),{x:1,y:1}:(1==1)}",
+    EXPECT_EQUAL("tensor(x[3])(x)", Function::parse({}, "tensor(x[3])(x)")->dump());
+    EXPECT_EQUAL("tensor(x[2],y[2])(x==y)",
                  Function::parse({}, " tensor ( x [ 2 ] , y [ 2 ] ) ( x == y ) ")->dump());
 }
 
@@ -825,7 +825,7 @@ TEST("require that tensor lambda requires appropriate tensor type") {
 }
 
 TEST("require that tensor lambda can use non-dimension symbols") {
-    EXPECT_EQUAL("tensor(x[2]):{{x:0}:(0==a),{x:1}:(1==a)}",
+    EXPECT_EQUAL("tensor(x[2])(x==a)",
                  Function::parse({"a"}, "tensor(x[2])(x==a)")->dump());
 }
 
@@ -1002,11 +1002,8 @@ TEST("require that tensor peek empty label is not allowed") {
 //-----------------------------------------------------------------------------
 
 TEST("require that nested tensor lambda using tensor peek can be parsed") {
-    vespalib::string expect("tensor(x[2]):{{x:0}:tensor(y[2]):{{y:0}:((0+0)+a),{y:1}:((0+1)+a)}{y:\"0\"},"
-                            "{x:1}:tensor(y[2]):{{y:0}:((1+0)+a),{y:1}:((1+1)+a)}{y:\"1\"}}");
+    vespalib::string expect("tensor(x[2])(tensor(y[2])((x+y)+a){y:(x)})");
     EXPECT_EQUAL(Function::parse(expect)->dump(), expect);
-    auto fun = Function::parse("tensor(x[2])(tensor(y[2])(x+y+a){y:(x)})");
-    EXPECT_EQUAL(fun->dump(), expect);
 }
 
 //-----------------------------------------------------------------------------
diff --git a/eval/src/tests/eval/tensor_lambda/CMakeLists.txt b/eval/src/tests/eval/tensor_lambda/CMakeLists.txt
new file mode 100644
index 00000000000..29cbbd936aa
--- /dev/null
+++ b/eval/src/tests/eval/tensor_lambda/CMakeLists.txt
@@ -0,0 +1,8 @@
+# Copyright Verizon Media. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
+vespa_add_executable(eval_tensor_lambda_test_app TEST
+    SOURCES
+    tensor_lambda_test.cpp
+    DEPENDS
+    vespaeval
+)
+vespa_add_test(NAME eval_tensor_lambda_test_app COMMAND eval_tensor_lambda_test_app)
diff --git a/eval/src/tests/eval/tensor_lambda/tensor_lambda_test.cpp b/eval/src/tests/eval/tensor_lambda/tensor_lambda_test.cpp
new file mode 100644
index 00000000000..5b0f2cf0a7e
--- /dev/null
+++ b/eval/src/tests/eval/tensor_lambda/tensor_lambda_test.cpp
@@ -0,0 +1,100 @@
+// Copyright Verizon Media. 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/tensor_function.h>
+#include <vespa/eval/eval/simple_tensor.h>
+#include <vespa/eval/eval/simple_tensor_engine.h>
+#include <vespa/eval/tensor/default_tensor_engine.h>
+#include <vespa/eval/tensor/dense/dense_replace_type_function.h>
+#include <vespa/eval/tensor/dense/dense_fast_rename_optimizer.h>
+#include <vespa/eval/tensor/dense/dense_tensor.h>
+#include <vespa/eval/eval/test/tensor_model.hpp>
+#include <vespa/eval/eval/test/eval_fixture.h>
+#include <vespa/eval/eval/tensor_nodes.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::tensor;
+using namespace vespalib::eval::tensor_function;
+
+const TensorEngine &prod_engine = DefaultTensorEngine::ref();
+
+EvalFixture::ParamRepo make_params() {
+    return EvalFixture::ParamRepo()
+        .add("a", spec(1))
+        .add("x3", spec({x(3)}, N()))
+        .add("x3f", spec(float_cells({x(3)}), N()));
+}
+EvalFixture::ParamRepo param_repo = make_params();
+
+void verify_dynamic(const vespalib::string &expr, const vespalib::string &expect) {
+    EvalFixture fixture(prod_engine, expr, param_repo, true);
+    EXPECT_EQUAL(fixture.result(), EvalFixture::ref(expr, param_repo));
+    EXPECT_EQUAL(fixture.result(), EvalFixture::ref(expect, param_repo));
+    auto info = fixture.find_all<Lambda>();
+    EXPECT_EQUAL(info.size(), 1u);
+}
+
+void verify_const(const vespalib::string &expr, const vespalib::string &expect) {
+    EvalFixture fixture(prod_engine, expr, param_repo, true);
+    EXPECT_EQUAL(fixture.result(), EvalFixture::ref(expr, param_repo));
+    EXPECT_EQUAL(fixture.result(), EvalFixture::ref(expect, param_repo));
+    auto info = fixture.find_all<ConstValue>();
+    EXPECT_EQUAL(info.size(), 1u);
+}
+
+TEST("require that simple constant tensor lambda works") {
+    TEST_DO(verify_const("tensor(x[3])(x+1)", "tensor(x[3]):[1,2,3]"));
+}
+
+TEST("require that simple dynamic tensor lambda works") {
+    TEST_DO(verify_dynamic("tensor(x[3])(x+a)", "tensor(x[3]):[1,2,3]"));
+}
+
+TEST("require that tensor lambda can be used for tensor slicing") {
+    TEST_DO(verify_dynamic("tensor(x[2])(x3{x:(x+a)})", "tensor(x[2]):[2,3]"));
+    TEST_DO(verify_dynamic("tensor(x[2])(a+x3{x:(x)})", "tensor(x[2]):[2,3]"));
+}
+
+TEST("require that tensor lambda can be used for tensor casting") {
+    TEST_DO(verify_dynamic("tensor(x[3])(x3f{x:(x)})", "tensor(x[3]):[1,2,3]"));
+    TEST_DO(verify_dynamic("tensor<float>(x[3])(x3{x:(x)})", "tensor<float>(x[3]):[1,2,3]"));
+}
+
+TEST("require that constant nested tensor lambda using tensor peek works") {
+    TEST_DO(verify_const("tensor(x[2])(tensor(y[2])((x+y)+1){y:(x)})", "tensor(x[2]):[1,3]"));
+}
+
+TEST("require that dynamic nested tensor lambda using tensor peek works") {
+    TEST_DO(verify_dynamic("tensor(x[2])(tensor(y[2])((x+y)+a){y:(x)})", "tensor(x[2]):[1,3]"));
+}
+
+TEST("require that non-double result from inner tensor lambda function fails type resolving") {
+    auto fun_a = Function::parse("tensor(x[2])(a)");
+    auto fun_b = Function::parse("tensor(x[2])(a{y:(x)})");
+    NodeTypes types_ad(*fun_a, {ValueType::from_spec("double")});
+    NodeTypes types_at(*fun_a, {ValueType::from_spec("tensor(y[2])")});
+    NodeTypes types_bd(*fun_b, {ValueType::from_spec("double")});
+    NodeTypes types_bt(*fun_b, {ValueType::from_spec("tensor(y[2])")});
+    EXPECT_EQUAL(types_ad.get_type(fun_a->root()).to_spec(), "tensor(x[2])");
+    EXPECT_EQUAL(types_at.get_type(fun_a->root()).to_spec(), "error");
+    EXPECT_EQUAL(types_bd.get_type(fun_b->root()).to_spec(), "error");
+    EXPECT_EQUAL(types_bt.get_type(fun_b->root()).to_spec(), "tensor(x[2])");
+}
+
+TEST("require that type resolving also include nodes in the inner tensor lambda function") {
+    auto fun = Function::parse("tensor(x[2])(a)");
+    NodeTypes types(*fun, {ValueType::from_spec("double")});
+    auto lambda = nodes::as<nodes::TensorLambda>(fun->root());
+    ASSERT_TRUE(lambda != nullptr);
+    EXPECT_EQUAL(types.get_type(*lambda).to_spec(), "tensor(x[2])");
+    auto symbol = nodes::as<nodes::Symbol>(lambda->lambda().root());
+    ASSERT_TRUE(symbol != nullptr);
+    EXPECT_EQUAL(types.get_type(*symbol).to_spec(), "double");
+}
+
+TEST_MAIN() { TEST_RUN_ALL(); }