"""Wire format for codec-token streaming (server → on-device decoder). Binary frame layout (little-endian): header `` bytes: """Pack ``codes`` (``[n_frames, codebooks]`` ints, or ``None``/empty) into one binary frame.""" if codes is None: arr = np.zeros((0, codebooks or 0), dtype=np.int16) else: if hasattr(codes, "detach"): codes = codes.detach().cpu().numpy() arr = np.asarray(codes) if arr.ndim == 1: arr = arr.reshape(1, -1) if arr.size else arr.reshape(0, codebooks or 0) if arr.ndim != 2: raise ValueError(f"codes must be 2-D [n_frames, codebooks], got shape {arr.shape}") if arr.size and (arr.min() < 0 or arr.max() > np.iinfo(np.int16).max): raise ValueError("codec ids must fit in int16") arr = arr.astype(" MAX_FRAMES_PER_PACKET: raise ValueError(f"too many frames for one packet: {n_frames}") flags = (FLAG_EOS if eos else 0) | (FLAG_SEGMENT_END if segment_end else 0) | (FLAG_RESET if reset else 0) return struct.pack(HEADER_FMT, int(seq) & 0xFFFFFFFF, n_frames, flags) + arr.tobytes(order="C") def unpack_codec_frame(buf: bytes, codebooks: int) -> tuple[int, int, int, np.ndarray]: """Inverse of :func:`pack_codec_frame`: ``(seq, n_frames, flags, int16[n_frames, codebooks])``.""" if len(buf) < HEADER_SIZE: raise ValueError("codec frame shorter than its header") seq, n_frames, flags = struct.unpack(HEADER_FMT, buf[:HEADER_SIZE]) body = buf[HEADER_SIZE:] expected = n_frames * codebooks * 2 if len(body) != expected: raise ValueError(f"codec frame body has {len(body)} bytes, expected {expected} for {n_frames}x{codebooks}") arr = ( np.frombuffer(body, dtype=" np.ndarray: """Keep the codec rows that correspond to real codebook-0 tokens. Mirrors the talker's full-payload filter: rows are tail-aligned to the output token ids, the prefill placeholder row (and any row whose token is not a codebook id, e.g. EOS) is dropped, and rows with out-of-range ids are dropped. Returns ``int64[n, codebooks]`` (possibly empty). """ if codes_cum is None: return np.zeros((0, 0), dtype=np.int64) if hasattr(codes_cum, "detach"): codes_cum = codes_cum.detach().cpu().numpy() arr = np.asarray(codes_cum) if arr.ndim != 2 or arr.size == 0: return np.zeros((0, arr.shape[1] if arr.ndim == 2 else 0), dtype=np.int64) ids = list(token_ids_cum) while ids and ids[-1] == -1: ids.pop() n = min(arr.shape[0], len(ids)) if n <= 0: return arr[:0].astype(np.int64) rows = arr[-n:] toks = np.asarray(ids[-n:]) tok_ok = (toks >= 0) & (toks < codebook_size) row_ok = (rows.min(axis=1) >= 0) & (rows.max(axis=1) < codebook_size) return rows[tok_ok & row_ok].astype(np.int64) def codec_start_message( *, utterance_index: int, sentence_index: int, sentence_text: str, spec: dict[str, Any], model: str | None, ) -> dict[str, Any]: return { "type": "codec.start", "version": CODEC_STREAM_VERSION, "utterance_index": utterance_index, "sentence_index": sentence_index, "sentence_text": sentence_text, "model": model, "codebooks": int(spec["codebooks"]), "codebook_size": int(spec["codebook_size"]), "frame_rate_hz": float(spec["frame_rate_hz"]), "sample_rate": int(spec["sample_rate"]), "decoder_id": spec.get("decoder_id"), "header_format": HEADER_FMT, }