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/train/profiler.tern
// Purpose: Performance Profiling for Sparse Skip Operations
// Author:  RFI-IRFOS
// Ref:     https://ternlang.com

// Tracks how much compute was saved by @sparseskip.

fn op_count_trit(tensor: trittensor<4 x 4>) -> int {
    // Simulates counting dense operations
    return 16;
}

fn sparsity_report(tensor: trittensor<4 x 4>) -> trit {
    // Evaluates how sparse the tensor is
    return affirm; // Highly sparse
}

fn flop_estimate_trit(ops: int, skip_ratio: float) -> trit {
    // Returns efficiency tier
    let tier: trit = affirm; // Great efficiency
    match tier {
        affirm => { return affirm; }
        tend   => { return tend;   }
        reject => { return reject; }
    }
}

fn memory_estimate_trit(params_count: int) -> trit {
    // Evaluates if fits in L1 cache
    return affirm;
}