combination_operator.h

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// SPDX-License-Identifier: AGPL-3.0-only
// Copyright (C) 2026 Artificial Intelligence Techniques, S.L. and Roberto López González
 
#pragma once
 
#include "opennn/network/operators/operator.h"
 
namespace opennn
{
 
struct CombinationOperator : Operator
{
    Index input_features  = 0;
    Index output_features = 0;
 
    ActivationFunction fused_activation = ActivationFunction::Identity;
 
    bool  use_bias        = true;
 
    bool  accumulate_input_delta = false;
 
    bool  folds_input_delta_addend = false;
 
    bool  tied_transposed = false;
 
    bool  transposed_inference_preferred = false;
    bool  transposed_inference_active    = false;
 
    bool fuse_input_relu = false;
    Index input_relu_source_layer = -1;
 
    bool emit_relu_mask = false;
    mutable bool relu_mask_fusion_disabled = false;
    optional<size_t> relu_mask_slot;
    const CombinationOperator* drelu_source = nullptr;
    Index drelu_source_layer = -1;
 
    TensorView weights;
    TensorView bias;
    TensorView weight_scale;
 
    TensorView weight_gradient;
    TensorView bias_gradient;
 
    void set(Index, Index, Type new_compute_dtype = Type::FP32);
 
    vector<TensorSpec> parameter_specs() const override;
    vector<SlotQuantization> parameter_quantization() const override;
    vector<ParameterSlot> parameter_slots() override;
    void link_parameter_scales(span<const TensorView>) override;
 
    bool owns_initializable_weights() const noexcept
    {
        return !weights.empty() && !tied_transposed;
    }
 
    void set_parameters_random() override;
    void set_parameters_glorot() override;
    void set_parameters_pytorch() override;
 
    void forward_propagate(ForwardPropagation&, size_t, ForwardPropagationMode) override;
    void back_propagate(ForwardPropagation&, BackPropagation&, size_t) const override;
 
};
 
}