Merge pull request #13584 from vespa-engine/arnej/stop-using-dispatch-0

use typify_invoke instead of dispatch_0/select_2

4 files changed, 15 insertions, 11 deletions

diff --git a/eval/src/vespa/eval/tensor/default_tensor_engine.cpp b/eval/src/vespa/eval/tensor/default_tensor_engine.cpp
index d9fcbaa3e2a..22073143ac0 100644
--- a/eval/src/vespa/eval/tensor/default_tensor_engine.cpp
+++ b/eval/src/vespa/eval/tensor/default_tensor_engine.cpp
@@ -176,7 +176,7 @@ DefaultTensorEngine::to_spec(const Value &value) const
 struct CallDenseTensorBuilder {
     template <typename CT>
     static Value::UP
-    call(const ValueType &type, const TensorSpec &spec)
+    invoke(const ValueType &type, const TensorSpec &spec)
     {
         TypedDenseTensorBuilder<CT> builder(type);
         for (const auto &cell: spec.cells()) {
@@ -191,6 +191,8 @@ struct CallDenseTensorBuilder {
     }
 };
 
+using MyTypify = eval::TypifyCellType;
+
 Value::UP
 DefaultTensorEngine::from_spec(const TensorSpec &spec) const
 {
@@ -201,7 +203,7 @@ DefaultTensorEngine::from_spec(const TensorSpec &spec) const
         double value = spec.cells().empty() ? 0.0 : spec.cells().begin()->second.value;
         return std::make_unique<DoubleValue>(value);
     } else if (type.is_dense()) {
-        return dispatch_0<CallDenseTensorBuilder>(type.cell_type(), type, spec);
+        return typify_invoke<1,MyTypify,CallDenseTensorBuilder>(type.cell_type(), type, spec);
     } else if (type.is_sparse()) {
         DirectSparseTensorBuilder builder(type);
         SparseTensorAddressBuilder address_builder;
@@ -449,7 +451,7 @@ const Value &concat_vectors(const Value &a, const Value &b, const vespalib::stri
 
 struct CallConcatVectors {
     template <typename OCT>
-    static const Value &call(const Value &a, const Value &b, const vespalib::string &dimension, size_t vector_size, Stash &stash) {
+    static const Value &invoke(const Value &a, const Value &b, const vespalib::string &dimension, size_t vector_size, Stash &stash) {
         return concat_vectors<OCT>(a, b, dimension, vector_size, stash);
     }
 };
@@ -461,7 +463,7 @@ DefaultTensorEngine::concat(const Value &a, const Value &b, const vespalib::stri
     size_t b_size = vector_size(b.type(), dimension);
     if ((a_size > 0) && (b_size > 0)) {
         CellType result_cell_type = ValueType::unify_cell_types(a.type(), b.type());
-        return dispatch_0<CallConcatVectors>(result_cell_type, a, b, dimension, (a_size + b_size), stash);
+        return typify_invoke<1,MyTypify,CallConcatVectors>(result_cell_type, a, b, dimension, (a_size + b_size), stash);
     }
     return to_default(simple_engine().concat(to_simple(a, stash), to_simple(b, stash), dimension, stash), stash);
 }
diff --git a/eval/src/vespa/eval/tensor/serialization/dense_binary_format.cpp b/eval/src/vespa/eval/tensor/serialization/dense_binary_format.cpp
index 493e4af3caf..4d6cfb1c9af 100644
--- a/eval/src/vespa/eval/tensor/serialization/dense_binary_format.cpp
+++ b/eval/src/vespa/eval/tensor/serialization/dense_binary_format.cpp
@@ -92,7 +92,7 @@ DenseBinaryFormat::serialize(nbostream &stream, const DenseTensorView &tensor)
 struct CallDecodeCells {
     template <typename CT>
     static std::unique_ptr<DenseTensorView>
-    call(nbostream &stream, size_t numCells, ValueType &&newType) {
+    invoke(nbostream &stream, size_t numCells, ValueType &&newType) {
         std::vector<CT> newCells;
         newCells.reserve(numCells);
         decodeCells<CT>(stream, numCells, newCells);
@@ -106,7 +106,8 @@ DenseBinaryFormat::deserialize(nbostream &stream, CellType cell_type)
     std::vector<Dimension> dimensions;
     size_t numCells = decodeDimensions(stream, dimensions);
     ValueType newType = ValueType::tensor_type(std::move(dimensions), cell_type);
-    return dispatch_0<CallDecodeCells>(cell_type, stream, numCells, std::move(newType));
+    using MyTypify = eval::TypifyCellType;
+    return typify_invoke<1,MyTypify,CallDecodeCells>(cell_type, stream, numCells, std::move(newType));
 }
 
 template <typename T>
diff --git a/searchlib/src/vespa/searchlib/queryeval/nearest_neighbor_blueprint.cpp b/searchlib/src/vespa/searchlib/queryeval/nearest_neighbor_blueprint.cpp
index 55342f91e93..d8b63909142 100644
--- a/searchlib/src/vespa/searchlib/queryeval/nearest_neighbor_blueprint.cpp
+++ b/searchlib/src/vespa/searchlib/queryeval/nearest_neighbor_blueprint.cpp
@@ -45,7 +45,7 @@ convert_cells<double,double>(std::unique_ptr<DenseTensorView> &, vespalib::eval:
 struct ConvertCellsSelector
 {
     template <typename LCT, typename RCT>
-    static auto get_fun() { return convert_cells<LCT, RCT>; }
+    static auto invoke() { return convert_cells<LCT, RCT>; }
 };
 
 } // namespace <unnamed>
@@ -67,7 +67,8 @@ NearestNeighborBlueprint::NearestNeighborBlueprint(const queryeval::FieldSpec& f
 {
     auto lct = _query_tensor->cellsRef().type;
     auto rct = _attr_tensor.getTensorType().cell_type();
-    auto fixup_fun = vespalib::tensor::select_2<ConvertCellsSelector>(lct, rct);
+    using MyTypify = vespalib::eval::TypifyCellType;
+    auto fixup_fun = vespalib::typify_invoke<2,MyTypify,ConvertCellsSelector>(lct, rct);
     fixup_fun(_query_tensor, _attr_tensor.getTensorType());
     _fallback_dist_fun = search::tensor::make_distance_function(_attr_tensor.getConfig().distance_metric(), rct);
     _dist_fun = _fallback_dist_fun.get();
diff --git a/searchlib/src/vespa/searchlib/tensor/tensor_attribute.cpp b/searchlib/src/vespa/searchlib/tensor/tensor_attribute.cpp
index 979eedec58a..f8db11ae9d8 100644
--- a/searchlib/src/vespa/searchlib/tensor/tensor_attribute.cpp
+++ b/searchlib/src/vespa/searchlib/tensor/tensor_attribute.cpp
@@ -20,7 +20,6 @@ using vespalib::tensor::SparseTensor;
 using vespalib::tensor::Tensor;
 using vespalib::tensor::TypedDenseTensorBuilder;
 using vespalib::tensor::WrappedSimpleTensor;
-using vespalib::tensor::dispatch_0;
 using search::StateExplorerUtils;
 
 namespace search::tensor {
@@ -34,7 +33,7 @@ constexpr size_t DEAD_SLACK = 0x10000u;
 
 struct CallMakeEmptyTensor {
     template <typename CT>
-    static Tensor::UP call(const ValueType &type) {
+    static Tensor::UP invoke(const ValueType &type) {
         TypedDenseTensorBuilder<CT> builder(type);
         return builder.build();
     }
@@ -46,7 +45,8 @@ createEmptyTensor(const ValueType &type)
     if (type.is_sparse()) {
         return std::make_unique<SparseTensor>(type, SparseTensor::Cells());
     } else if (type.is_dense()) {
-        return dispatch_0<CallMakeEmptyTensor>(type.cell_type(), type);
+        using MyTypify = vespalib::eval::TypifyCellType;
+        return vespalib::typify_invoke<1,MyTypify,CallMakeEmptyTensor>(type.cell_type(), type);
     } else {
         return std::make_unique<WrappedSimpleTensor>(std::make_unique<SimpleTensor>(type, SimpleTensor::Cells()));
     }