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// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#include "dense_cell_range_function.h"
#include <vespa/eval/eval/value.h>
namespace vespalib::eval {
using namespace tensor_function;
namespace {
template <typename CT>
void my_cell_range_op(InterpretedFunction::State &state, uint64_t param) {
const auto &self = unwrap_param<DenseCellRangeFunction>(param);
auto old_cells = state.peek(0).cells().typify<CT>();
ConstArrayRef<CT> new_cells(&old_cells[self.offset()], self.length());
state.pop_push(state.stash.create<DenseValueView>(self.result_type(), TypedCells(new_cells)));
}
struct MyCellRangeOp {
template <typename CT>
static auto invoke() { return my_cell_range_op<CT>; }
};
} // namespace <unnamed>
DenseCellRangeFunction::DenseCellRangeFunction(const ValueType &result_type,
const TensorFunction &child,
size_t offset, size_t length)
: tensor_function::Op1(result_type, child),
_offset(offset),
_length(length)
{
assert(result_type.cell_type() == child.result_type().cell_type());
}
DenseCellRangeFunction::~DenseCellRangeFunction() = default;
InterpretedFunction::Instruction
DenseCellRangeFunction::compile_self(const ValueBuilderFactory &, Stash &) const
{
assert(result_type().cell_type() == child().result_type().cell_type());
using MyTypify = TypifyCellType;
auto op = typify_invoke<1,MyTypify,MyCellRangeOp>(result_type().cell_type());
return InterpretedFunction::Instruction(op, wrap_param<DenseCellRangeFunction>(*this));
}
} // namespace
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