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// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
#pragma once
#include <vespa/eval/eval/tensor_function.h>
namespace vespalib::eval {
/**
* Tensor function for a dot product inside a mixed tensor.
*
* Optimized tensor function for dot-product inside a bigger (possibly
* mixed) tensor. To trigger this, the function must be in the form
* reduce((mixed tensor)*(vector),sum,dimension names)
* with "vector" being a dense tensor with the same dimensions that
* are reduced, "mixed tensor" must contain all these dimension, and
* they must also be the innermost (alphabetically last) indexed
* dimensions in the mixed tensor.
* Simple example:
* mixed: tensor(category{},x[32])
* vector: tensor(x[32])
* expression: reduce(mixed*vector,sum,x)
* result: tensor(category{})
* More complex example:
* mixed: tensor<double>(a{},b[31],c{},d[42],e{},f[5],g{})
* vector: tensor<float>(d[42],f[5])
* expression: reduce(mixed*vector,sum,d,f)
* result: tensor<double>(a{},b[31],c{},e{},g{})
* Note:
* if the bigger tensor is dense, other optimizers are likely
* to pick up the operation, even if this function could also
* handle them.
**/
class MixedInnerProductFunction : public tensor_function::Op2
{
public:
MixedInnerProductFunction(const ValueType &res_type_in,
const TensorFunction &mixed_child,
const TensorFunction &vector_child);
InterpretedFunction::Instruction compile_self(const ValueBuilderFactory &factory, Stash &stash) const override;
bool result_is_mutable() const override { return true; }
static bool compatible_types(const ValueType &res, const ValueType &mixed, const ValueType &dense);
static const TensorFunction &optimize(const TensorFunction &expr, Stash &stash);
};
} // namespace
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