ternlang-core 0.3.3

Compiler and VM for Ternlang — balanced ternary language with affirm/tend/reject trit semantics, @sparseskip codegen, and BET bytecode execution.
Documentation 
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// Module:  stdlib/nn/optim/rmsprop.tern
// Purpose: RMSProp Optimizer for Trit Gradients
// Author:  RFI-IRFOS
// Ref:     https://ternlang.com

// Adapts learning rates based on moving average of squared gradients.
// When gradient is 'tend', cache doesn't update (sparse update).

struct RMSProp {
    lr: float,
    alpha: float,
    eps: float
}

fn cache_update(grad: trittensor<4 x 4>, cache: trittensor<4 x 4>) -> trittensor<4 x 4> {
    // Only update cache where grad is not 'tend'
    @sparseskip
    let new_cache: trittensor<4 x 4> = cache; // simulated update
    return new_cache;
}

fn param_step_rms(param: trittensor<4 x 4>, grad: trittensor<4 x 4>, cache: trittensor<4 x 4>) -> trittensor<4 x 4> {
    @sparseskip
    let next_param: trittensor<4 x 4> = param; // Simulated param -= lr * grad / sqrt(cache)
    return next_param;
}