1 files changed, 0 insertions, 158 deletions
diff --git a/eval/src/tests/tensor/dense_tensor_function_optimizer/dense_tensor_function_optimizer_test.cpp b/eval/src/tests/tensor/dense_tensor_function_optimizer/dense_tensor_function_optimizer_test.cpp
deleted file mode 100644
index 269a1e265c5..00000000000
--- a/eval/src/tests/tensor/dense_tensor_function_optimizer/dense_tensor_function_optimizer_test.cpp
+++ /dev/null
@@ -1,158 +0,0 @@
-// 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/dense/dense_dot_product_function.h>
-#include <vespa/eval/tensor/dense/dense_xw_product_function.h>
-#include <vespa/eval/eval/operation.h>
-
-using namespace vespalib::eval;
-using namespace vespalib::eval::operation;
-using namespace vespalib::eval::tensor_function;
-using namespace vespalib::tensor;
-using vespalib::Stash;
-
-//-----------------------------------------------------------------------------
-
-const TensorFunction &
-optimizeDotProduct(const vespalib::string &lhsType,
-                  const vespalib::string &rhsType,
-                  Stash &stash)
-{
-    const Node &reduceNode = reduce(join(inject(ValueType::from_spec(lhsType), 1, stash),
-                                         inject(ValueType::from_spec(rhsType), 3, stash),
-                                         Mul::f, stash),
-                                    Aggr::SUM, {}, stash);
-    return DenseDotProductFunction::optimize(reduceNode, stash);
-}
-
-void assertParam(const TensorFunction &node, size_t expect_idx) {
-    auto inject = as<Inject>(node);
-    ASSERT_TRUE(inject);
-    EXPECT_EQUAL(inject->param_idx(), expect_idx);
-}
-
-void
-assertOptimizedDotProduct(const vespalib::string &lhsType,
-                          const vespalib::string &rhsType)
-{
-    Stash stash;
-    const TensorFunction &func = optimizeDotProduct(lhsType, rhsType, stash);
-    const DenseDotProductFunction *dotProduct = as<DenseDotProductFunction>(func);
-    ASSERT_TRUE(dotProduct);
-    TEST_DO(assertParam(dotProduct->lhs(), 1));
-    TEST_DO(assertParam(dotProduct->rhs(), 3));
-}
-
-void
-assertNotOptimizedDotProduct(const vespalib::string &lhsType,
-                            const vespalib::string &rhsType)
-{
-    Stash stash;
-    const TensorFunction &func = optimizeDotProduct(lhsType, rhsType, stash);
-    const Reduce *reduce = as<Reduce>(func);
-    EXPECT_TRUE(reduce);
-}
-
-//-----------------------------------------------------------------------------
-
-const TensorFunction &
-optimizeXWProduct(const vespalib::string &lhsType,
-                 const vespalib::string &rhsType,
-                 const vespalib::string &dim,
-                 Stash &stash)
-{
-    const Node &reduceNode = reduce(join(inject(ValueType::from_spec(lhsType), 1, stash),
-                                         inject(ValueType::from_spec(rhsType), 3, stash),
-                                         Mul::f, stash),
-                                    Aggr::SUM, {dim}, stash);
-    return DenseXWProductFunction::optimize(reduceNode, stash);
-}
-
-void
-assertOptimizedXWProduct(const vespalib::string &vecTypeStr,
-                        const vespalib::string &matTypeStr,
-                        const vespalib::string &dim)
-{
-    Stash stash;
-    const TensorFunction &func = optimizeXWProduct(vecTypeStr, matTypeStr, dim, stash);
-    const TensorFunction &inv_func = optimizeXWProduct(matTypeStr, vecTypeStr, dim, stash);
-    const DenseXWProductFunction *xwProduct = as<DenseXWProductFunction>(func);
-    const DenseXWProductFunction *inv_xwProduct = as<DenseXWProductFunction>(inv_func);
-    ValueType vecType = ValueType::from_spec(vecTypeStr);
-    ValueType matType = ValueType::from_spec(matTypeStr);
-    size_t common_idx = matType.dimension_index(vecType.dimensions()[0].name);
-    ASSERT_TRUE(xwProduct);
-    ASSERT_TRUE(inv_xwProduct);
-    ASSERT_TRUE(common_idx != ValueType::Dimension::npos);
-    TEST_DO(assertParam(xwProduct->lhs(), 1));
-    TEST_DO(assertParam(inv_xwProduct->lhs(), 3));
-    TEST_DO(assertParam(xwProduct->rhs(), 3));
-    TEST_DO(assertParam(inv_xwProduct->rhs(), 1));
-    EXPECT_EQUAL(xwProduct->vectorSize(), vecType.dimensions()[0].size);
-    EXPECT_EQUAL(inv_xwProduct->vectorSize(), vecType.dimensions()[0].size);
-    EXPECT_EQUAL(xwProduct->resultSize(), matType.dimensions()[1 - common_idx].size);
-    EXPECT_EQUAL(inv_xwProduct->resultSize(), matType.dimensions()[1 - common_idx].size);
-    EXPECT_EQUAL(xwProduct->matrixHasCommonDimensionInnermost(), (common_idx == 1));
-    EXPECT_EQUAL(inv_xwProduct->matrixHasCommonDimensionInnermost(), (common_idx == 1));
-}
-
-void
-assertNotOptimizedXWProduct(const vespalib::string &vecType,
-                           const vespalib::string &matType,
-                           const vespalib::string &dim)
-{
-    Stash stash;
-    const TensorFunction &func = optimizeXWProduct(vecType, matType, dim, stash);
-    const TensorFunction &inv_func = optimizeXWProduct(matType, vecType, dim, stash);
-    const Reduce *reduce = as<Reduce>(func);
-    const Reduce *inv_reduce = as<Reduce>(inv_func);
-    EXPECT_TRUE(reduce);
-    EXPECT_TRUE(inv_reduce);
-}
-
-//-----------------------------------------------------------------------------
-
-TEST("require that dot product with compatible dimensions is optimized")
-{
-    TEST_DO(assertOptimizedDotProduct("tensor(x[5])", "tensor(x[5])"));
-    TEST_DO(assertOptimizedDotProduct("tensor(x[3])", "tensor(x[5])"));
-    TEST_DO(assertOptimizedDotProduct("tensor(x[5])", "tensor(x[3])"));
-    TEST_DO(assertOptimizedDotProduct("tensor(x[])",  "tensor(x[5])"));
-    TEST_DO(assertOptimizedDotProduct("tensor(x[5])", "tensor(x[])"));
-    TEST_DO(assertOptimizedDotProduct("tensor(x[])",  "tensor(x[])"));
-}
-
-TEST("require that dot product with incompatible dimensions is NOT optimized")
-{
-    TEST_DO(assertNotOptimizedDotProduct("tensor(x[5])",      "tensor(y[5])"));
-    TEST_DO(assertNotOptimizedDotProduct("tensor(y[5])",      "tensor(x[5])"));
-    TEST_DO(assertNotOptimizedDotProduct("tensor(y[])",       "tensor(x[])"));
-    TEST_DO(assertNotOptimizedDotProduct("tensor(x[5])",      "tensor(x[5],y[7])"));
-    TEST_DO(assertNotOptimizedDotProduct("tensor(x[5],y[7])", "tensor(x[5],y[7])"));
-}
-
-//-----------------------------------------------------------------------------
-
-TEST("require that xw products with compatible dimensions are optimized") {
-    TEST_DO(assertOptimizedXWProduct("tensor(x[3])", "tensor(x[3],y[4])", "x"));
-    TEST_DO(assertOptimizedXWProduct("tensor(y[4])", "tensor(x[3],y[4])", "y"));
-}
-
-TEST("require that xw products with incompatible dimensions are not optimized") {
-    TEST_DO(assertNotOptimizedXWProduct("tensor(x[3])", "tensor(x[3],y[4])", "y"));
-    TEST_DO(assertNotOptimizedXWProduct("tensor(x[])",  "tensor(x[3],y[4])", "x"));
-    TEST_DO(assertNotOptimizedXWProduct("tensor(x[3])", "tensor(x[],y[4])",  "x"));
-    TEST_DO(assertNotOptimizedXWProduct("tensor(x[3])", "tensor(x[3],y[])",  "x"));
-    TEST_DO(assertNotOptimizedXWProduct("tensor(x[2])", "tensor(x[3],y[4])", "x"));
-    TEST_DO(assertNotOptimizedXWProduct("tensor(x[4])", "tensor(x[3],y[4])", "x"));
-    TEST_DO(assertNotOptimizedXWProduct("tensor(x[3])", "tensor(y[3],z[4])", "x"));
-    TEST_DO(assertNotOptimizedXWProduct("tensor(x[3])", "tensor(y[3],z[4])", "y"));
-    TEST_DO(assertNotOptimizedXWProduct("tensor(x[3])", "tensor(y[3],z[4])", "z"));
-    TEST_DO(assertNotOptimizedXWProduct("tensor(y[4])", "tensor(x[3],y[4])", "x"));
-    TEST_DO(assertNotOptimizedXWProduct("tensor(y[3])", "tensor(x[3],y[4])", "y"));
-    TEST_DO(assertNotOptimizedXWProduct("tensor(y[5])", "tensor(x[3],y[4])", "y"));
-}
-
-//-----------------------------------------------------------------------------
-
-TEST_MAIN() { TEST_RUN_ALL(); }