// Hand-optimized TASM baseline: std.trinity.inference
//
// Rosetta Stone unification: one lookup table, four readers.
// Real LWE encryption over Goldilocks, lookup-table ReLU activation,
// LUT sponge hash (S-box from LUT), Poseidon2 hash commitment,
// PBS demo (test polynomial from LUT), 2-qubit Bell pair commitment.
//
// Reader 1: lut.apply in __dense_layer โ neural activation
// Reader 2: lut.read in __lut_sponge โ crypto S-box
// Reader 3: lut.read in __pbs_build_test โ FHE test polynomial
// Reader 4: STARK LogUp โ proof authentication (upstream)
//
// Pitch parameters: LWE dim 8, 8 inputs, 16 neurons,
// ring dim 64, domain 1024, Bell commitment.
//
// Stack convention:
// Arguments pushed left-to-right (first arg deepest on stack).
// Return values left on top of stack after return.
//
// Instruction count rules:
// - Comments (// ...) are NOT counted
// - Labels (ending with :) are NOT counted
// - halt is NOT counted
// - Blank lines are NOT counted
// - Everything else IS counted (including return)
//
// Static instruction count summary:
// __decrypt_loop : 24
// __dense_layer : 17
// __sum_loop : 13
// __hash_commit : 15
// __lut_hash_commit : 17
// __quantum_commit : 3
// __trinity : 78
// ----------------------------------------
// Total : 167
// ===========================================================================
// PHASE 1b: DECRYPT OUTPUTS (loop)
// ===========================================================================
// Decrypt loop: counts neurons down to 0.
// Stack: [counter, lwe_n, delta, result_addr, s_addr, ct_out_addr]
__decrypt_loop:
dup 0
push 0
eq
skiz
return
push -1
add
// Stack: [i, lwe_n, delta, result_addr, s_addr, ct_out_addr]
// ct_addr = ct_out_addr + i * (lwe_n + 1)
dup 0
dup 2
push 1
add
mul
dup 6
add
// Stack: [ct_addr, i, lwe_n, delta, result_addr, s_addr, ct_out_addr]
// lwe.decrypt(ct_addr, s_addr, delta, lwe_n) -> m
dup 5
dup 4
dup 4
call __lwe_decrypt
// Stack: [m, i, lwe_n, delta, result_addr, s_addr, ct_out_addr]
// mem.write(result_addr + i, m)
dup 1
dup 5
add
write_mem 1
pop 1
// Stack: [i, lwe_n, delta, result_addr, s_addr, ct_out_addr]
recurse
// ===========================================================================
// PHASE 2: DENSE NEURAL LAYER (with lookup-table activation)
// ===========================================================================
// ---------------------------------------------------------------------------
// __dense_layer: (w_addr, x_addr, b_addr, out_addr, tmp_addr, lut_addr, neurons)
// ---------------------------------------------------------------------------
// Dense layer: out = lut_relu(W * x + b). [Reader 1: lut.apply]
//
// Stack: [w, x, b, out, tmp, lut, neurons]
//
// 17 counted instructions.
__dense_layer:
dup 6
dup 7
dup 7
dup 4
dup 4
call __tensor_matvec
dup 6
dup 4
dup 5
dup 7
call __tensor_bias_add
dup 6
dup 4
dup 5
dup 8
call __lut_apply
return
// ===========================================================================
// PHASE 3a: LUT SPONGE HASH COMMITMENT (Rosetta Stone Reader #2)
// ===========================================================================
// ---------------------------------------------------------------------------
// __sum_loop: (addr, counter, accumulator) -> (addr_end, 0, sum)
// ---------------------------------------------------------------------------
// 13 counted instructions.
__sum_loop:
dup 1
push 0
eq
skiz
return
read_mem 1
swap 3
add
swap 2
push -1
add
swap 1
recurse
// ---------------------------------------------------------------------------
// __lut_hash_commit: (activated, neurons, w_dig, key_dig, class, lut_addr, domain, sponge_rc) -> digest
// ---------------------------------------------------------------------------
// LUT sponge hash: S-box reads from lut_addr (Reader #2).
// Computes output_digest = sum(activated), then hashes via LUT sponge.
//
// Stack: [activated, neurons, w_dig, key_dig, class, lut_addr, domain, sponge_rc]
// st0: activated st4: class
// st1: neurons st5: lut_addr
// st2: w_dig st6: domain
// st3: key_dig st7: sponge_rc
//
// 17 counted instructions.
__lut_hash_commit:
// --- sum(activated, neurons) -> output_digest ---
dup 0
dup 2
push 0
call __sum_loop
pop 2
// Stack: [output_digest, activated, neurons, w_dig, key_dig, class, lut_addr, domain, sponge_rc]
// --- lut_sponge.hash4_to_digest(w_dig, key_dig, output_digest, class, lut_addr, domain, sponge_rc) ---
dup 3
dup 5
dup 3
dup 8
dup 10
dup 12
dup 14
call __lut_sponge_hash4_to_digest
// Stack: [digest, output_digest, activated, ...]
swap 8
pop 5
pop 3
return
// ===========================================================================
// PHASE 3b: POSEIDON2 HASH COMMITMENT (production binding)
// ===========================================================================
// ---------------------------------------------------------------------------
// __hash_commit: (activated_addr, neurons, weights_digest, key_digest, class, rc_addr) -> digest
// ---------------------------------------------------------------------------
// 15 counted instructions.
__hash_commit:
dup 0
dup 2
push 0
call __sum_loop
pop 2
dup 3
dup 5
dup 3
dup 8
dup 10
call __poseidon2_hash4_to_digest
swap 7
pop 5
pop 2
return
// ===========================================================================
// PHASE 5: QUANTUM COMMITMENT (2-qubit Bell pair)
// ===========================================================================
// ---------------------------------------------------------------------------
// __quantum_commit: (class: Field) -> Bool
// ---------------------------------------------------------------------------
// 3 counted instructions.
__quantum_commit:
push 0
eq
return
// ===========================================================================
// FULL TRINITY PIPELINE โ ROSETTA STONE UNIFICATION
// ===========================================================================
// ---------------------------------------------------------------------------
// __trinity: (cts_addr, s_addr, w_priv_addr, ct_out_addr, tmp_addr,
// result_addr, delta, lwe_n, input_dim, neurons,
// dense_w_addr, dense_b_addr, activated_addr,
// lut_addr, expected_class,
// rc_addr, weights_digest, key_digest, expected_digest,
// domain, sponge_rc_addr, expected_lut_digest,
// pbs_sample_ct, pbs_out_addr, ring_n,
// pbs_acc_addr, pbs_test_addr, pbs_tmp_addr,
// pbs_expected_m) -> Bool
// ---------------------------------------------------------------------------
// One table (lut_addr), four readers (1-3 demonstrated, 4 upstream):
// Phase 2: lut.apply (Reader 1 โ NN activation)
// Phase 3a: lut.read (Reader 2 โ crypto S-box)
// Phase 4: lut.read (Reader 3 โ FHE test polynomial)
//
// Stack on entry (st0 = top, 29 args):
// st0: pbs_expected_m
// st1: pbs_tmp_addr
// st2: pbs_test_addr
// st3: pbs_acc_addr
// st4: ring_n
// st5: pbs_out_addr
// st6: pbs_sample_ct
// st7: expected_lut_digest
// st8: sponge_rc_addr
// st9: domain
// st10: expected_digest
// st11: key_digest
// st12: weights_digest
// st13: rc_addr
// st14: expected_class
// st15: lut_addr
// st16: activated_addr
// st17: dense_b_addr
// st18: dense_w_addr
// st19: neurons
// st20: input_dim
// st21: lwe_n
// st22: delta
// st23: result_addr
// st24: tmp_addr
// st25: ct_out_addr
// st26: w_priv_addr
// st27: s_addr
// st28: cts_addr
//
// 78 counted instructions.
__trinity:
// --- Phase 1: lwe.private_linear(cts, w_priv, ct_out, tmp, lwe_n, input_dim, neurons) ---
dup 28
dup 27
dup 27
dup 27
dup 25
dup 25
dup 25
call __lwe_private_linear
// --- Phase 1b: decrypt_outputs ---
// __decrypt_loop: [neurons, lwe_n, delta, result_addr, s_addr, ct_out_addr]
dup 19
dup 22
dup 24
dup 26
dup 30
dup 29
call __decrypt_loop
pop 6
// --- Phase 2: dense_layer(dense_w, result, dense_b, activated, tmp, lut, neurons) ---
// [Reader 1: lut.apply]
dup 18
dup 24
dup 19
dup 19
dup 28
dup 19
dup 25
call __dense_layer
pop 7
// --- argmax(activated_addr, neurons) + assert class == expected ---
dup 16
dup 20
call __tensor_argmax
// Stack: [class, pbs_exp_m, pbs_tmp, pbs_test, pbs_acc, ring_n, pbs_out, pbs_ct, exp_lut_dig, sponge_rc, domain, exp_dig, key_dig, w_dig, rc, exp_class, lut, activated, ...]
dup 0
dup 16
eq
assert
// --- Phase 3a: lut_hash_commit(activated, neurons, w_dig, key_dig, class, lut, domain, sponge_rc) ---
// [Reader 2: lut.read in S-box]
dup 17
dup 21
dup 15
dup 15
dup 5
dup 19
dup 14
dup 14
call __lut_hash_commit
// Stack: [lut_digest, class, ...]
// assert lut_digest == expected_lut_digest
dup 9
eq
assert
// --- Phase 3b: hash_commit(activated, neurons, w_dig, key_dig, class, rc_addr) ---
dup 17
dup 21
dup 15
dup 15
dup 5
dup 17
call __hash_commit
// Stack: [digest, class, ...]
// assert digest == expected_digest
dup 12
eq
assert
// --- Phase 4: pbs_demo ---
// [Reader 3: lut.read in build_test_poly]
// pbs.bootstrap(ct, s, lut, out, delta, lwe_n, ring_n, domain, acc, test, tmp) -> m
dup 8
dup 30
dup 19
dup 9
dup 26
dup 25
dup 9
dup 15
dup 9
dup 9
dup 7
call __pbs_bootstrap
// assert m == expected_m
dup 3
eq
assert
// --- Phase 5: quantum_commit(class) ---
// class is still on stack from earlier
call __quantum_commit
// Cleanup: swap result past 29 args, pop all
swap 29
pop 5
pop 5
pop 5
pop 5
pop 5
pop 4
return