@triton.heuristics({'STORE_INITIAL_STATE_GRADIENT': lambda args: args['dh0'
    ] is not None, 'USE_FINAL_STATE_GRADIENT': lambda args: args['dht'] is not
    None, 'USE_OFFSETS': lambda args: args['offsets'] is not None})
@triton.autotune(configs=[triton.Config({'BK': BK, 'BV': BV}, num_warps=
    num_warps, num_stages=num_stages) for BK in [32, 64, 128] for BV in [32,
    64, 128] for num_warps in [2, 4, 8] for num_stages in [2, 3, 4]], key=[
    'BT', 'USE_G', 'USE_GK', 'USE_GV'])
@triton.jit
def chunk_bwd_kernel_dh_parallel(q, g, gk, gv, do, dh, dht, dh0, offsets,
    indices, scale, T: tl.constexpr, HQ: tl.constexpr, H: tl.constexpr, K:
    tl.constexpr, V: tl.constexpr, BT: tl.constexpr, BK: tl.constexpr, BV:
    tl.constexpr, NG: tl.constexpr, USE_G: tl.constexpr, USE_GK: tl.
    constexpr, USE_GV: tl.constexpr, STORE_INITIAL_STATE_GRADIENT: tl.
    constexpr, USE_FINAL_STATE_GRADIENT: tl.constexpr, USE_OFFSETS: tl.
    constexpr, HEAD_FIRST: tl.constexpr):
    i_kv, i_t, i_bh = tl.program_id(0), tl.program_id(1), tl.program_id(2)
    NV = tl.cdiv(V, BV)
    i_k, i_v = i_kv // NV, i_kv % NV
    i_b, i_hq, i_bg = i_bh // HQ, i_bh % HQ, i_bh // NG
    i_h = i_hq // NG
    if USE_OFFSETS:
        i_tg = i_t
        i_n, i_t = tl.load(indices + i_t * 2).to(tl.int32), tl.load(indices +
            i_t * 2 + 1).to(tl.int32)
        bos, eos = tl.load(offsets + i_n).to(tl.int32), tl.load(offsets +
            i_n + 1).to(tl.int32)
        T = eos - bos
        NT = tl.cdiv(T, BT)
    else:
        bos, eos = i_b * T, i_b * T + T
        NT = tl.cdiv(T, BT)
        i_n, i_tg = i_b, i_b * NT + i_t
    i_nh = i_n * HQ + i_hq
    if HEAD_FIRST:
        p_q = tl.make_block_ptr(q + i_bh * T * K, (K, T), (1, K), (i_k * BK,
            i_t * BT), (BK, BT), (0, 1))
        p_do = tl.make_block_ptr(do + i_bh * T * V, (T, V), (V, 1), (i_t *
            BT, i_v * BV), (BT, BV), (1, 0))
        p_dh = tl.make_block_ptr(dh + (i_bh * NT + i_t) * K * V, (K, V), (V,
            1), (i_k * BK, i_v * BV), (BK, BV), (1, 0))
    else:
        p_q = tl.make_block_ptr(q + (bos * HQ + i_hq) * K, (K, T), (1, HQ *
            K), (i_k * BK, i_t * BT), (BK, BT), (0, 1))
        p_do = tl.make_block_ptr(do + (bos * HQ + i_hq) * V, (T, V), (HQ *
            V, 1), (i_t * BT, i_v * BV), (BT, BV), (1, 0))
        p_dh = tl.make_block_ptr(dh + (i_tg * H + i_h) * K * V, (K, V), (V,
            1), (i_k * BK, i_v * BV), (BK, BV), (1, 0))
    if i_t == NT - 1:
        if USE_FINAL_STATE_GRADIENT:
            p_dht = tl.make_block_ptr(dht + i_nh * K * V, (K, V), (V, 1), (
                i_k * BK, i_v * BV), (BK, BV), (1, 0))
            b_dh = tl.load(p_dht, boundary_check=(0, 1)).to(tl.float32)
        else:
            b_dh = tl.zeros([BK, BV], dtype=tl.float32)
        tl.store(p_dh, b_dh.to(p_dh.dtype.element_ty), boundary_check=(0, 1))
    b_q = tl.load(p_q, boundary_check=(0, 1))
    b_q = (b_q * scale).to(b_q.dtype)
    b_do = tl.load(p_do, boundary_check=(0, 1))
    if USE_G:
        if HEAD_FIRST:
            p_g = g + i_bg * T + i_t * BT + tl.arange(0, BT)
            p_g = tl.max_contiguous(tl.multiple_of(p_g, BT), BT)
        else:
            p_g = g + (bos + i_t * BT + tl.arange(0, BT)) * H + i_h
        b_g = tl.load(p_g, mask=i_t * BT + tl.arange(0, BT) < T, other=0.0)
        b_q = (b_q * tl.exp(b_g)[None, :]).to(b_q.dtype)
    if USE_GK:
        if HEAD_FIRST:
            p_gk = tl.make_block_ptr(gk + i_bg * T * K, (K, T), (1, K), (
                i_k * BK, i_t * BT), (BK, BT), (0, 1))
        else:
            p_gk = tl.make_block_ptr(gk + (bos * H + i_h) * K, (K, T), (1, 
                H * K), (i_k * BK, i_t * BT), (BK, BT), (0, 1))
        b_gk = tl.load(p_gk, boundary_check=(0, 1))
        b_q = (b_q * tl.exp(b_gk)).to(b_q.dtype)
    if USE_GV:
        if HEAD_FIRST:
            p_gv = tl.make_block_ptr(gv + i_bg * T * V, (T, V), (V, 1), (
                i_t * BT, i_v * BV), (BT, BV), (1, 0))
        else:
            p_gv = tl.make_block_ptr(gv + (bos * H + i_h) * V, (T, V), (H *
                V, 1), (i_t * BT, i_v * BV), (BT, BV), (1, 0))
        b_gv = tl.load(p_gv, boundary_check=(0, 1))
        b_do = (b_do * tl.exp(b_gv)).to(b_do.dtype)
    b_dh = tl.dot(b_q, b_do)
    if i_t > 0:
        if HEAD_FIRST:
            p_dh = tl.make_block_ptr(dh + (i_bh * NT + i_t - 1) * K * V, (K,
                V), (V, 1), (i_k * BK, i_v * BV), (BK, BV), (1, 0))
        else:
            p_dh = tl.make_block_ptr(dh + ((i_tg - 1) * H + i_h) * K * V, (
                K, V), (V, 1), (i_k * BK, i_v * BV), (BK, BV), (1, 0))
        tl.store(p_dh, b_dh.to(p_dh.dtype.element_ty), boundary_check=(0, 1))
    elif STORE_INITIAL_STATE_GRADIENT:
        p_dh0 = tl.make_block_ptr(dh0 + i_nh * K * V, (K, V), (V, 1), (i_k *
            BK, i_v * BV), (BK, BV), (1, 0))
        tl.store(p_dh0, b_dh.to(p_dh0.dtype.element_ty), boundary_check=(0, 1))
