"""
Step 3: CMD_DECODE -- control lines -> DDR command.

A DDR command is a truth table over the control pins (CS_n, ACT_n, and the
RAS_n/CAS_n/WE_n multiplexed lines). It is a finite function -> N/N verifiable.
(DDR5 uses a multi-cycle CA encoding; the table here is a compact, self-consistent
DDR4-style decode that the same unit shape can be retrained to for DDR5.)
"""
from __future__ import annotations
import torch
from .common import bits_of, int_of, pm

IN, OUT = 5, 4
CMDS = {"DESELECT": 0, "ACTIVATE": 1, "NOP": 2, "READ": 3, "WRITE": 4,
        "PRECHARGE": 5, "REFRESH": 6, "MRS": 7, "ZQ": 8}
NAME = {v: k for k, v in CMDS.items()}


def golden_cmd(v: int) -> int:
    cs, act, ras, cas, we = bits_of(v, 5)          # bit0=CS_n .. bit4=WE_n
    if cs == 1:
        return CMDS["DESELECT"]
    if act == 0:
        return CMDS["ACTIVATE"]
    table = {(1, 1, 1): "NOP", (1, 1, 0): "NOP", (1, 0, 1): "READ", (1, 0, 0): "WRITE",
             (0, 1, 1): "PRECHARGE", (0, 1, 0): "REFRESH", (0, 0, 1): "MRS", (0, 0, 0): "ZQ"}
    return CMDS[table[(ras, cas, we)]]


def domain():
    X = torch.stack([pm(bits_of(v, IN)) for v in range(2 ** IN)])
    Y = torch.tensor([[float(b) for b in bits_of(golden_cmd(v), OUT)] for v in range(2 ** IN)])
    return X, Y


def run(net, v: int) -> int:
    return int_of((net(pm(bits_of(v, IN)).unsqueeze(0))[0] > 0).int().tolist())