113 bool has_forwarded_ =
false;
Vendor-agnostic compute/memory backend. CPUBackend, CUDABackend (Phase 1.5), and HIPBackend (Phase 1....
Definition device_backend.hpp:219
virtual DeviceType device() const noexcept=0
Which device this backend's buffers reside on.
y = a S b for a selected t-conorm S, over two independent fuzzy-truth-valued operand tensors (values ...
Definition disjunction_module.hpp:22
Tensor forward_impl(const Tensor &input) override
Splits input (leading dim 2) into the two operands and computes the selected t-conorm elementwise.
OpType op_type() const override
Elementwise per this module's own op_type() convention.
Definition disjunction_module.hpp:59
DisjunctionModule(DeviceBackend *backend, TConorm t_conorm=TConorm::Product)
Constructs a disjunction module.
Tensor propagate_relevance(const Tensor &relevance_out, const LRPRuleConfig &config) override
LRP relevance propagation for the selected t-conorm – genuinely novel, no prior art (research_2026_ne...
static Tensor stack_operands(const Tensor &a, const Tensor &b, DeviceBackend *backend)
See ConjunctionModule::stack_operands()'s identical convention.
Tensor backward(const Tensor &grad_output) override
Gradient w.r.t. this module's (stacked) input.
TConorm
Which t-conorm this instance computes. Product is the campaign's primary case.
Definition disjunction_module.hpp:25
@ Lukasiewicz
min(1, a + b)
std::optional< DeviceType > compute_device() const override
Where this layer computes, so forward() rejects an input on another device (FND-8).
Definition disjunction_module.hpp:98
Tensor forward(const Tensor &a, const Tensor &b)
Convenience two-operand entry point – see ConjunctionModule::forward(a, b)'s identical convention.
Base class for every layer type (LinearModule, Conv2DModule, activations, ...).
Definition module.hpp:58
Tensor forward(const Tensor &input)
Runs this module's forward computation.
Definition module.hpp:73
N-dimensional tensor. Owns its data buffer exclusively; a DeviceBackend* is injected (not owned) – th...
Definition tensor.hpp:29
Abstract base every layer subclasses – NVI forward(), pure-virtual LRP contract.
Definition acquisition_functions.hpp:16
OpType
The op-type tag a Node carries. Charter Part 2 §3: nodes are tagged by a small closed set of op types...
Definition op_type.hpp:19
Configuration for LRP relevance propagation: which rule a module applies and its hyperparameters....
Definition lrp_rule_config.hpp:57