[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: ds4.c

```c
token_vec_push(&s->checkpoint, drafts[i]);
        logits_on_host = false;
        accepted[n_accept++] = drafts[i];
        verified++;
        if (drafts[i] == eos_token) break;
    }
    if (verified > 0 && !logits_on_host) {
        if (ds4_gpu_tensor_read(s->graph.logits,
                                  0,
                                  s->logits,
                                  (uint64_t)DS4_N_VOCAB * sizeof(s->logits[0])) == 0)
        {
            snprintf(err, errlen, "%s logits readback failed", ds4_backend_name(e->backend));
            s->checkpoint_valid = false;
            return -1;
        }
        logits_on_host = true;
    }
    (void)logits_on_host;
    DS4_MTP_KEEP_ACCEPTED(verified);
#undef DS4_MTP_KEEP_ACCEPTED
    if (mtp_timing) {
        fprintf(stderr,
                "ds4: mtp timing seq drafted=%d verified=%d draft=%.3f ms verify=%.3f ms total=%.3f ms\n",
                draft_n,
                verified,
                (mtp_t_after_draft - mtp_t0) * 1000.0,
                (now_sec() - seq_t0) * 1000.0,
                (now_sec() - mtp_t0) * 1000.0);
    }
    if (getenv("DS4_MTP_SPEC_LOG")) {
        if (verified == draft_n) {
            fprintf(stderr,
                    "ds4: mtp spec seq accept drafted=%d accepted=%d\n",
                    draft_n,
                    n_accept);
        } else {
            fprintf(stderr,
                    "ds4: mtp spec seq partial drafted=%d verified=%d accepted=%d\n",
                    draft_n,
                    verified,
                    n_accept);
        }
    }
    return n_accept;
#endif
}

void ds4_session_invalidate(ds4_session *s) {
    s->checkpoint_valid = false;
    s->checkpoint.len = 0;
    s->mtp_draft_valid = false;
}

void ds4_session_rewind(ds4_session *s, int pos) {
    if (pos < 0) pos = 0;
    if (pos > s->checkpoint.len) pos = s->checkpoint.len;
    s->checkpoint.len = pos;
    s->mtp_draft_valid = false;
}

int ds4_session_pos(ds4_session *s) {
    return s->checkpoint.len;
}

int ds4_session_ctx(ds4_session *s) {
    return s->ctx_size;
}
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: ds4.c

```c
token_vec_push(&s->checkpoint, drafts[i]);
        logits_on_host = false;
        accepted[n_accept++] = drafts[i];
        verified++;
        if (drafts[i] == eos_token) break;
    }
    if (verified > 0 && !logits_on_host) {
        if (ds4_gpu_tensor_read(s->graph.logits,
                                  0,
                                  s->logits,
                                  (uint64_t)DS4_N_VOCAB * sizeof(s->logits[0])) == 0)
        {
            snprintf(err, errlen, "%s logits readback failed", ds4_backend_name(e->backend));
            s->checkpoint_valid = false;
            return -1;
        }
        logits_on_host = true;
    }
    (void)logits_on_host;
    DS4_MTP_KEEP_ACCEPTED(verified);
#undef DS4_MTP_KEEP_ACCEPTED
    if (mtp_timing) {
        fprintf(stderr,
                "ds4: mtp timing seq drafted=%d verified=%d draft=%.3f ms verify=%.3f ms total=%.3f ms\n",
                draft_n,
                verified,
                (mtp_t_after_draft - mtp_t0) * 1000.0,
                (now_sec() - seq_t0) * 1000.0,
                (now_sec() - mtp_t0) * 1000.0);
    }
    if (getenv("DS4_MTP_SPEC_LOG")) {
        if (verified == draft_n) {
            fprintf(stderr,
                    "ds4: mtp spec seq accept drafted=%d accepted=%d\n",
                    draft_n,
                    n_accept);
        } else {
            fprintf(stderr,
                    "ds4: mtp spec seq partial drafted=%d verified=%d accepted=%d\n",
                    draft_n,
                    verified,
                    n_accept);
        }
    }
    return n_accept;
#endif
}

void ds4_session_invalidate(ds4_session *s) {
    s->checkpoint_valid = false;
    s->checkpoint.len = 0;
    s->mtp_draft_valid = false;
}

void ds4_session_rewind(ds4_session *s, int pos) {
    if (pos < 0) pos = 0;
    if (pos > s->checkpoint.len) pos = s->checkpoint.len;
    s->checkpoint.len = pos;
    s->mtp_draft_valid = false;
}

int ds4_session_pos(ds4_session *s) {
    return s->checkpoint.len;
}

int ds4_session_ctx(ds4_session *s) {
    return s->ctx_size;
}
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: ds4.c

```c
, DS4_N_HC, 0, 0);
    tensor_expect_layout(w->output_hc_fn,    DS4_TENSOR_F16,  2, hc_dim, DS4_N_HC, 0);
    tensor_expect_layout(w->output_hc_scale, DS4_TENSOR_F32,  1, 1, 0, 0);
    tensor_expect_layout(w->output_norm,     DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(w->output,          DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_VOCAB, 0);

    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        const ds4_layer_weights *l = &w->layer[il];
        const uint32_t ratio = ds4_layer_compress_ratio(il);

        tensor_expect_layout(l->hc_attn_fn,     DS4_TENSOR_F16,  2, hc_dim, hc_mix_dim, 0);
        tensor_expect_layout(l->hc_attn_scale,  DS4_TENSOR_F32,  1, 3, 0, 0);
        tensor_expect_layout(l->hc_attn_base,   DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
        tensor_expect_layout(l->attn_norm,      DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
        tensor_expect_layout(l->attn_q_a,       DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_LORA_Q, 0);
        tensor_expect_layout(l->attn_q_a_norm,  DS4_TENSOR_F32,  1, DS4_N_LORA_Q, 0, 0);
        tensor_expect_layout(l->attn_q_b,       DS4_TENSOR_Q8_0, 2, DS4_N_LORA_Q, q_dim, 0);
        tensor_expect_layout(l->attn_kv,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_HEAD_DIM, 0);
        tensor_expect_layout(l->attn_kv_a_norm, DS4_TENSOR_F32,  1, DS4_N_HEAD_DIM, 0, 0);
        tensor_expect_layout(l->attn_sinks,     DS4_TENSOR_F32,  1, DS4_N_HEAD, 0, 0);
        tensor_expect_layout(l->attn_output_a,  DS4_TENSOR_Q8_0, 2, DS4_N_HEAD_DIM * (DS4_N_HEAD / DS4_N_OUT_GROUP), out_low_dim, 0);
        tensor_expect_layout(l->attn_output_b,  DS4_TENSOR_Q8_0, 2, out_low_dim, DS4_N_EMBD, 0);

        if (ratio != 0) {
            const uint32_t coff = ratio == 4 ? 2u : 1u;
            const uint64_t comp_width = (uint64_t)coff * DS4_N_HEAD_DIM;
            tensor_expect_layout(l->attn_compressor_ape,  DS4_TENSOR_F16, 2, comp_width, ratio, 0);
            tensor_expect_layout(l->attn_compressor_kv,   DS4_TENSOR_F16, 2, DS4_N_EMBD, comp_width, 0);
            tensor_expect_layout(l->attn_compressor_gate, DS4_TENSOR_F16, 2, DS4_N_EMBD, comp_width, 0);
            tensor_expect_layout(l->attn_compressor_norm, DS4_TENSOR_F32, 1, DS4_N_HEAD_DIM, 0, 0);
        }
        if (ratio == 4) {
            const uint64_t index_q_dim = (uint64_t)DS4_N_INDEXER_HEAD * DS4_N_INDEXER_HEAD_DIM;
            const uint64_t index_width = 2u * DS4_N_INDEXER_HEAD_DIM;
            tensor_expect_layout(l->indexer_attn_q_b,          DS4_TENSOR_F16, 2, DS4_N_LORA_Q, index_q_dim, 0);
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: ds4.c

```c
, DS4_N_HC, 0, 0);
    tensor_expect_layout(w->output_hc_fn,    DS4_TENSOR_F16,  2, hc_dim, DS4_N_HC, 0);
    tensor_expect_layout(w->output_hc_scale, DS4_TENSOR_F32,  1, 1, 0, 0);
    tensor_expect_layout(w->output_norm,     DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(w->output,          DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_VOCAB, 0);

    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        const ds4_layer_weights *l = &w->layer[il];
        const uint32_t ratio = ds4_layer_compress_ratio(il);

        tensor_expect_layout(l->hc_attn_fn,     DS4_TENSOR_F16,  2, hc_dim, hc_mix_dim, 0);
        tensor_expect_layout(l->hc_attn_scale,  DS4_TENSOR_F32,  1, 3, 0, 0);
        tensor_expect_layout(l->hc_attn_base,   DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
        tensor_expect_layout(l->attn_norm,      DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
        tensor_expect_layout(l->attn_q_a,       DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_LORA_Q, 0);
        tensor_expect_layout(l->attn_q_a_norm,  DS4_TENSOR_F32,  1, DS4_N_LORA_Q, 0, 0);
        tensor_expect_layout(l->attn_q_b,       DS4_TENSOR_Q8_0, 2, DS4_N_LORA_Q, q_dim, 0);
        tensor_expect_layout(l->attn_kv,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_HEAD_DIM, 0);
        tensor_expect_layout(l->attn_kv_a_norm, DS4_TENSOR_F32,  1, DS4_N_HEAD_DIM, 0, 0);
        tensor_expect_layout(l->attn_sinks,     DS4_TENSOR_F32,  1, DS4_N_HEAD, 0, 0);
        tensor_expect_layout(l->attn_output_a,  DS4_TENSOR_Q8_0, 2, DS4_N_HEAD_DIM * (DS4_N_HEAD / DS4_N_OUT_GROUP), out_low_dim, 0);
        tensor_expect_layout(l->attn_output_b,  DS4_TENSOR_Q8_0, 2, out_low_dim, DS4_N_EMBD, 0);

        if (ratio != 0) {
            const uint32_t coff = ratio == 4 ? 2u : 1u;
            const uint64_t comp_width = (uint64_t)coff * DS4_N_HEAD_DIM;
            tensor_expect_layout(l->attn_compressor_ape,  DS4_TENSOR_F16, 2, comp_width, ratio, 0);
            tensor_expect_layout(l->attn_compressor_kv,   DS4_TENSOR_F16, 2, DS4_N_EMBD, comp_width, 0);
            tensor_expect_layout(l->attn_compressor_gate, DS4_TENSOR_F16, 2, DS4_N_EMBD, comp_width, 0);
            tensor_expect_layout(l->attn_compressor_norm, DS4_TENSOR_F32, 1, DS4_N_HEAD_DIM, 0, 0);
        }
        if (ratio == 4) {
            const uint64_t index_q_dim = (uint64_t)DS4_N_INDEXER_HEAD * DS4_N_INDEXER_HEAD_DIM;
            const uint64_t index_width = 2u * DS4_N_INDEXER_HEAD_DIM;
            tensor_expect_layout(l->indexer_attn_q_b,          DS4_TENSOR_F16, 2, DS4_N_LORA_Q, index_q_dim, 0);
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: ds4.c

```c
, DS4_N_HC, 0, 0);
    tensor_expect_layout(w->output_hc_fn,    DS4_TENSOR_F16,  2, hc_dim, DS4_N_HC, 0);
    tensor_expect_layout(w->output_hc_scale, DS4_TENSOR_F32,  1, 1, 0, 0);
    tensor_expect_layout(w->output_norm,     DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(w->output,          DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_VOCAB, 0);

    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        const ds4_layer_weights *l = &w->layer[il];
        const uint32_t ratio = ds4_layer_compress_ratio(il);

        tensor_expect_layout(l->hc_attn_fn,     DS4_TENSOR_F16,  2, hc_dim, hc_mix_dim, 0);
        tensor_expect_layout(l->hc_attn_scale,  DS4_TENSOR_F32,  1, 3, 0, 0);
        tensor_expect_layout(l->hc_attn_base,   DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
        tensor_expect_layout(l->attn_norm,      DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
        tensor_expect_layout(l->attn_q_a,       DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_LORA_Q, 0);
        tensor_expect_layout(l->attn_q_a_norm,  DS4_TENSOR_F32,  1, DS4_N_LORA_Q, 0, 0);
        tensor_expect_layout(l->attn_q_b,       DS4_TENSOR_Q8_0, 2, DS4_N_LORA_Q, q_dim, 0);
        tensor_expect_layout(l->attn_kv,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_HEAD_DIM, 0);
        tensor_expect_layout(l->attn_kv_a_norm, DS4_TENSOR_F32,  1, DS4_N_HEAD_DIM, 0, 0);
        tensor_expect_layout(l->attn_sinks,     DS4_TENSOR_F32,  1, DS4_N_HEAD, 0, 0);
        tensor_expect_layout(l->attn_output_a,  DS4_TENSOR_Q8_0, 2, DS4_N_HEAD_DIM * (DS4_N_HEAD / DS4_N_OUT_GROUP), out_low_dim, 0);
        tensor_expect_layout(l->attn_output_b,  DS4_TENSOR_Q8_0, 2, out_low_dim, DS4_N_EMBD, 0);

        if (ratio != 0) {
            const uint32_t coff = ratio == 4 ? 2u : 1u;
            const uint64_t comp_width = (uint64_t)coff * DS4_N_HEAD_DIM;
            tensor_expect_layout(l->attn_compressor_ape,  DS4_TENSOR_F16, 2, comp_width, ratio, 0);
            tensor_expect_layout(l->attn_compressor_kv,   DS4_TENSOR_F16, 2, DS4_N_EMBD, comp_width, 0);
            tensor_expect_layout(l->attn_compressor_gate, DS4_TENSOR_F16, 2, DS4_N_EMBD, comp_width, 0);
            tensor_expect_layout(l->attn_compressor_norm, DS4_TENSOR_F32, 1, DS4_N_HEAD_DIM, 0, 0);
        }
        if (ratio == 4) {
            const uint64_t index_q_dim = (uint64_t)DS4_N_INDEXER_HEAD * DS4_N_INDEXER_HEAD_DIM;
            const uint64_t index_width = 2u * DS4_N_INDEXER_HEAD_DIM;
            tensor_expect_layout(l->indexer_attn_q_b,          DS4_TENSOR_F16, 2, DS4_N_LORA_Q, index_q_dim, 0);
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: ds4.c

```c
, DS4_N_HC, 0, 0);
    tensor_expect_layout(w->output_hc_fn,    DS4_TENSOR_F16,  2, hc_dim, DS4_N_HC, 0);
    tensor_expect_layout(w->output_hc_scale, DS4_TENSOR_F32,  1, 1, 0, 0);
    tensor_expect_layout(w->output_norm,     DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(w->output,          DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_VOCAB, 0);

    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        const ds4_layer_weights *l = &w->layer[il];
        const uint32_t ratio = ds4_layer_compress_ratio(il);

        tensor_expect_layout(l->hc_attn_fn,     DS4_TENSOR_F16,  2, hc_dim, hc_mix_dim, 0);
        tensor_expect_layout(l->hc_attn_scale,  DS4_TENSOR_F32,  1, 3, 0, 0);
        tensor_expect_layout(l->hc_attn_base,   DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
        tensor_expect_layout(l->attn_norm,      DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
        tensor_expect_layout(l->attn_q_a,       DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_LORA_Q, 0);
        tensor_expect_layout(l->attn_q_a_norm,  DS4_TENSOR_F32,  1, DS4_N_LORA_Q, 0, 0);
        tensor_expect_layout(l->attn_q_b,       DS4_TENSOR_Q8_0, 2, DS4_N_LORA_Q, q_dim, 0);
        tensor_expect_layout(l->attn_kv,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_HEAD_DIM, 0);
        tensor_expect_layout(l->attn_kv_a_norm, DS4_TENSOR_F32,  1, DS4_N_HEAD_DIM, 0, 0);
        tensor_expect_layout(l->attn_sinks,     DS4_TENSOR_F32,  1, DS4_N_HEAD, 0, 0);
        tensor_expect_layout(l->attn_output_a,  DS4_TENSOR_Q8_0, 2, DS4_N_HEAD_DIM * (DS4_N_HEAD / DS4_N_OUT_GROUP), out_low_dim, 0);
        tensor_expect_layout(l->attn_output_b,  DS4_TENSOR_Q8_0, 2, out_low_dim, DS4_N_EMBD, 0);

        if (ratio != 0) {
            const uint32_t coff = ratio == 4 ? 2u : 1u;
            const uint64_t comp_width = (uint64_t)coff * DS4_N_HEAD_DIM;
            tensor_expect_layout(l->attn_compressor_ape,  DS4_TENSOR_F16, 2, comp_width, ratio, 0);
            tensor_expect_layout(l->attn_compressor_kv,   DS4_TENSOR_F16, 2, DS4_N_EMBD, comp_width, 0);
            tensor_expect_layout(l->attn_compressor_gate, DS4_TENSOR_F16, 2, DS4_N_EMBD, comp_width, 0);
            tensor_expect_layout(l->attn_compressor_norm, DS4_TENSOR_F32, 1, DS4_N_HEAD_DIM, 0, 0);
        }
        if (ratio == 4) {
            const uint64_t index_q_dim = (uint64_t)DS4_N_INDEXER_HEAD * DS4_N_INDEXER_HEAD_DIM;
            const uint64_t index_width = 2u * DS4_N_INDEXER_HEAD_DIM;
            tensor_expect_layout(l->indexer_attn_q_b,          DS4_TENSOR_F16, 2, DS4_N_LORA_Q, index_q_dim, 0);
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: ds4.c

```c
const uint64_t index_width = 2u * DS4_N_INDEXER_HEAD_DIM;
            tensor_expect_layout(l->indexer_attn_q_b,          DS4_TENSOR_F16, 2, DS4_N_LORA_Q, index_q_dim, 0);
            tensor_expect_layout(l->indexer_proj,              DS4_TENSOR_F16, 2, DS4_N_EMBD, DS4_N_INDEXER_HEAD, 0);
            tensor_expect_layout(l->indexer_compressor_ape,    DS4_TENSOR_F16, 2, index_width, ratio, 0);
            tensor_expect_layout(l->indexer_compressor_kv,     DS4_TENSOR_F16, 2, DS4_N_EMBD, index_width, 0);
            tensor_expect_layout(l->indexer_compressor_gate,   DS4_TENSOR_F16, 2, DS4_N_EMBD, index_width, 0);
            tensor_expect_layout(l->indexer_compressor_norm,   DS4_TENSOR_F32, 1, DS4_N_INDEXER_HEAD_DIM, 0, 0);
        }

        tensor_expect_layout(l->hc_ffn_fn,      DS4_TENSOR_F16,  2, hc_dim, hc_mix_dim, 0);
        tensor_expect_layout(l->hc_ffn_scale,   DS4_TENSOR_F32,  1, 3, 0, 0);
        tensor_expect_layout(l->hc_ffn_base,    DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
        tensor_expect_layout(l->ffn_norm,       DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
        tensor_expect_layout(l->ffn_gate_inp,   DS4_TENSOR_F16,  2, DS4_N_EMBD, DS4_N_EXPERT, 0);
        tensor_expect_optional(l->ffn_exp_probs_b, DS4_TENSOR_F32, 1, DS4_N_EXPERT, 0, 0);
        tensor_expect_routed_expert(l->ffn_gate_exps, 3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
        tensor_expect_routed_expert(l->ffn_up_exps,   3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
        tensor_expect_routed_expert(l->ffn_down_exps, 3, DS4_N_FF_EXP, DS4_N_EMBD, DS4_N_EXPERT);
        if (l->ffn_gate_exps->type != l->ffn_up_exps->type) {
            fprintf(stderr, "ds4: routed gate/up experts use different quant types in layer %u\n", il);
            exit(1);
        }
        tensor_expect_layout(l->ffn_gate_shexp, DS4_TENSOR_Q8_0,    2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
        tensor_expect_layout(l->ffn_up_shexp,   DS4_TENSOR_Q8_0,    2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
        tensor_expect_layout(l->ffn_down_shexp, DS4_TENSOR_Q8_0,    2, DS4_N_FF_EXP, DS4_N_EMBD, 0);
        if (il < DS4_N_HASH_LAYER) {
            tensor_expect_layout(l->ffn_gate_tid2eid, DS4_TENSOR_I32, 2, DS4_N_EXPERT_USED, DS4_N_VOCAB, 0);
        }
    }
}

static void mtp_weights_validate_layout(const ds4_mtp_weights *w) {
    const uint64_t hc_dim = (uint64_t)DS4_N_EMBD * DS4_N_HC;
    const uint64_t hc_mix_dim = 2u * DS4_N_HC + (uint64_t)DS4_N_HC * DS4_N_HC;
    const uint64_t q_dim = (uint64_t)DS4_N_HEAD * DS4_N_HEAD_DIM;
    const uint64_t out_low_dim = (uint64_t)DS4_N_OUT_GROUP * DS4_N_LORA_O;
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: ds4.c

```c
const uint64_t index_width = 2u * DS4_N_INDEXER_HEAD_DIM;
            tensor_expect_layout(l->indexer_attn_q_b,          DS4_TENSOR_F16, 2, DS4_N_LORA_Q, index_q_dim, 0);
            tensor_expect_layout(l->indexer_proj,              DS4_TENSOR_F16, 2, DS4_N_EMBD, DS4_N_INDEXER_HEAD, 0);
            tensor_expect_layout(l->indexer_compressor_ape,    DS4_TENSOR_F16, 2, index_width, ratio, 0);
            tensor_expect_layout(l->indexer_compressor_kv,     DS4_TENSOR_F16, 2, DS4_N_EMBD, index_width, 0);
            tensor_expect_layout(l->indexer_compressor_gate,   DS4_TENSOR_F16, 2, DS4_N_EMBD, index_width, 0);
            tensor_expect_layout(l->indexer_compressor_norm,   DS4_TENSOR_F32, 1, DS4_N_INDEXER_HEAD_DIM, 0, 0);
        }

        tensor_expect_layout(l->hc_ffn_fn,      DS4_TENSOR_F16,  2, hc_dim, hc_mix_dim, 0);
        tensor_expect_layout(l->hc_ffn_scale,   DS4_TENSOR_F32,  1, 3, 0, 0);
        tensor_expect_layout(l->hc_ffn_base,    DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
        tensor_expect_layout(l->ffn_norm,       DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
        tensor_expect_layout(l->ffn_gate_inp,   DS4_TENSOR_F16,  2, DS4_N_EMBD, DS4_N_EXPERT, 0);
        tensor_expect_optional(l->ffn_exp_probs_b, DS4_TENSOR_F32, 1, DS4_N_EXPERT, 0, 0);
        tensor_expect_routed_expert(l->ffn_gate_exps, 3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
        tensor_expect_routed_expert(l->ffn_up_exps,   3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
        tensor_expect_routed_expert(l->ffn_down_exps, 3, DS4_N_FF_EXP, DS4_N_EMBD, DS4_N_EXPERT);
        if (l->ffn_gate_exps->type != l->ffn_up_exps->type) {
            fprintf(stderr, "ds4: routed gate/up experts use different quant types in layer %u\n", il);
            exit(1);
        }
        tensor_expect_layout(l->ffn_gate_shexp, DS4_TENSOR_Q8_0,    2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
        tensor_expect_layout(l->ffn_up_shexp,   DS4_TENSOR_Q8_0,    2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
        tensor_expect_layout(l->ffn_down_shexp, DS4_TENSOR_Q8_0,    2, DS4_N_FF_EXP, DS4_N_EMBD, 0);
        if (il < DS4_N_HASH_LAYER) {
            tensor_expect_layout(l->ffn_gate_tid2eid, DS4_TENSOR_I32, 2, DS4_N_EXPERT_USED, DS4_N_VOCAB, 0);
        }
    }
}

static void mtp_weights_validate_layout(const ds4_mtp_weights *w) {
    const uint64_t hc_dim = (uint64_t)DS4_N_EMBD * DS4_N_HC;
    const uint64_t hc_mix_dim = 2u * DS4_N_HC + (uint64_t)DS4_N_HC * DS4_N_HC;
    const uint64_t q_dim = (uint64_t)DS4_N_HEAD * DS4_N_HEAD_DIM;
    const uint64_t out_low_dim = (uint64_t)DS4_N_OUT_GROUP * DS4_N_LORA_O;
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: ds4.c

```c
const uint64_t index_width = 2u * DS4_N_INDEXER_HEAD_DIM;
            tensor_expect_layout(l->indexer_attn_q_b,          DS4_TENSOR_F16, 2, DS4_N_LORA_Q, index_q_dim, 0);
            tensor_expect_layout(l->indexer_proj,              DS4_TENSOR_F16, 2, DS4_N_EMBD, DS4_N_INDEXER_HEAD, 0);
            tensor_expect_layout(l->indexer_compressor_ape,    DS4_TENSOR_F16, 2, index_width, ratio, 0);
            tensor_expect_layout(l->indexer_compressor_kv,     DS4_TENSOR_F16, 2, DS4_N_EMBD, index_width, 0);
            tensor_expect_layout(l->indexer_compressor_gate,   DS4_TENSOR_F16, 2, DS4_N_EMBD, index_width, 0);
            tensor_expect_layout(l->indexer_compressor_norm,   DS4_TENSOR_F32, 1, DS4_N_INDEXER_HEAD_DIM, 0, 0);
        }

        tensor_expect_layout(l->hc_ffn_fn,      DS4_TENSOR_F16,  2, hc_dim, hc_mix_dim, 0);
        tensor_expect_layout(l->hc_ffn_scale,   DS4_TENSOR_F32,  1, 3, 0, 0);
        tensor_expect_layout(l->hc_ffn_base,    DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
        tensor_expect_layout(l->ffn_norm,       DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
        tensor_expect_layout(l->ffn_gate_inp,   DS4_TENSOR_F16,  2, DS4_N_EMBD, DS4_N_EXPERT, 0);
        tensor_expect_optional(l->ffn_exp_probs_b, DS4_TENSOR_F32, 1, DS4_N_EXPERT, 0, 0);
        tensor_expect_routed_expert(l->ffn_gate_exps, 3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
        tensor_expect_routed_expert(l->ffn_up_exps,   3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
        tensor_expect_routed_expert(l->ffn_down_exps, 3, DS4_N_FF_EXP, DS4_N_EMBD, DS4_N_EXPERT);
        if (l->ffn_gate_exps->type != l->ffn_up_exps->type) {
            fprintf(stderr, "ds4: routed gate/up experts use different quant types in layer %u\n", il);
            exit(1);
        }
        tensor_expect_layout(l->ffn_gate_shexp, DS4_TENSOR_Q8_0,    2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
        tensor_expect_layout(l->ffn_up_shexp,   DS4_TENSOR_Q8_0,    2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
        tensor_expect_layout(l->ffn_down_shexp, DS4_TENSOR_Q8_0,    2, DS4_N_FF_EXP, DS4_N_EMBD, 0);
        if (il < DS4_N_HASH_LAYER) {
            tensor_expect_layout(l->ffn_gate_tid2eid, DS4_TENSOR_I32, 2, DS4_N_EXPERT_USED, DS4_N_VOCAB, 0);
        }
    }
}

static void mtp_weights_validate_layout(const ds4_mtp_weights *w) {
    const uint64_t hc_dim = (uint64_t)DS4_N_EMBD * DS4_N_HC;
    const uint64_t hc_mix_dim = 2u * DS4_N_HC + (uint64_t)DS4_N_HC * DS4_N_HC;
    const uint64_t q_dim = (uint64_t)DS4_N_HEAD * DS4_N_HEAD_DIM;
    const uint64_t out_low_dim = (uint64_t)DS4_N_OUT_GROUP * DS4_N_LORA_O;
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: ds4.c

```c
const uint64_t index_width = 2u * DS4_N_INDEXER_HEAD_DIM;
            tensor_expect_layout(l->indexer_attn_q_b,          DS4_TENSOR_F16, 2, DS4_N_LORA_Q, index_q_dim, 0);
            tensor_expect_layout(l->indexer_proj,              DS4_TENSOR_F16, 2, DS4_N_EMBD, DS4_N_INDEXER_HEAD, 0);
            tensor_expect_layout(l->indexer_compressor_ape,    DS4_TENSOR_F16, 2, index_width, ratio, 0);
            tensor_expect_layout(l->indexer_compressor_kv,     DS4_TENSOR_F16, 2, DS4_N_EMBD, index_width, 0);
            tensor_expect_layout(l->indexer_compressor_gate,   DS4_TENSOR_F16, 2, DS4_N_EMBD, index_width, 0);
            tensor_expect_layout(l->indexer_compressor_norm,   DS4_TENSOR_F32, 1, DS4_N_INDEXER_HEAD_DIM, 0, 0);
        }

        tensor_expect_layout(l->hc_ffn_fn,      DS4_TENSOR_F16,  2, hc_dim, hc_mix_dim, 0);
        tensor_expect_layout(l->hc_ffn_scale,   DS4_TENSOR_F32,  1, 3, 0, 0);
        tensor_expect_layout(l->hc_ffn_base,    DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
        tensor_expect_layout(l->ffn_norm,       DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
        tensor_expect_layout(l->ffn_gate_inp,   DS4_TENSOR_F16,  2, DS4_N_EMBD, DS4_N_EXPERT, 0);
        tensor_expect_optional(l->ffn_exp_probs_b, DS4_TENSOR_F32, 1, DS4_N_EXPERT, 0, 0);
        tensor_expect_routed_expert(l->ffn_gate_exps, 3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
        tensor_expect_routed_expert(l->ffn_up_exps,   3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
        tensor_expect_routed_expert(l->ffn_down_exps, 3, DS4_N_FF_EXP, DS4_N_EMBD, DS4_N_EXPERT);
        if (l->ffn_gate_exps->type != l->ffn_up_exps->type) {
            fprintf(stderr, "ds4: routed gate/up experts use different quant types in layer %u\n", il);
            exit(1);
        }
        tensor_expect_layout(l->ffn_gate_shexp, DS4_TENSOR_Q8_0,    2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
        tensor_expect_layout(l->ffn_up_shexp,   DS4_TENSOR_Q8_0,    2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
        tensor_expect_layout(l->ffn_down_shexp, DS4_TENSOR_Q8_0,    2, DS4_N_FF_EXP, DS4_N_EMBD, 0);
        if (il < DS4_N_HASH_LAYER) {
            tensor_expect_layout(l->ffn_gate_tid2eid, DS4_TENSOR_I32, 2, DS4_N_EXPERT_USED, DS4_N_VOCAB, 0);
        }
    }
}

static void mtp_weights_validate_layout(const ds4_mtp_weights *w) {
    const uint64_t hc_dim = (uint64_t)DS4_N_EMBD * DS4_N_HC;
    const uint64_t hc_mix_dim = 2u * DS4_N_HC + (uint64_t)DS4_N_HC * DS4_N_HC;
    const uint64_t q_dim = (uint64_t)DS4_N_HEAD * DS4_N_HEAD_DIM;
    const uint64_t out_low_dim = (uint64_t)DS4_N_OUT_GROUP * DS4_N_LORA_O;
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
4_N_HC + (uint64_t)DS4_N_HC * DS4_N_HC;
    const uint64_t q_dim = (uint64_t)DS4_N_HEAD * DS4_N_HEAD_DIM;
    const uint64_t out_low_dim = (uint64_t)DS4_N_OUT_GROUP * DS4_N_LORA_O;
    const ds4_layer_weights *l = &w->block;

    tensor_expect_layout(w->hc_head_base,  DS4_TENSOR_F32,  1, DS4_N_HC, 0, 0);
    tensor_expect_plain_layout(w->hc_head_fn, 2, hc_dim, DS4_N_HC, 0);
    tensor_expect_layout(w->hc_head_scale, DS4_TENSOR_F32,  1, 1, 0, 0);
    tensor_expect_layout(w->e_proj,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_EMBD, 0);
    tensor_expect_layout(w->h_proj,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_EMBD, 0);
    tensor_expect_layout(w->enorm,         DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(w->hnorm,         DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(w->norm,          DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);

    tensor_expect_plain_layout(l->hc_attn_fn, 2, hc_dim, hc_mix_dim, 0);
    tensor_expect_layout(l->hc_attn_scale,  DS4_TENSOR_F32,  1, 3, 0, 0);
    tensor_expect_layout(l->hc_attn_base,   DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
    tensor_expect_layout(l->attn_norm,      DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(l->attn_q_a,       DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_LORA_Q, 0);
    tensor_expect_layout(l->attn_q_a_norm,  DS4_TENSOR_F32,  1, DS4_N_LORA_Q, 0, 0);
    tensor_expect_layout(l->attn_q_b,       DS4_TENSOR_Q8_0, 2, DS4_N_LORA_Q, q_dim, 0);
    tensor_expect_layout(l->attn_kv,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_HEAD_DIM, 0);
    tensor_expect_layout(l->attn_kv_a_norm, DS4_TENSOR_F32,  1, DS4_N_HEAD_DIM, 0, 0);
    tensor_expect_layout(l->attn_sinks,     DS4_TENSOR_F32,  1, DS4_N_HEAD, 0, 0);
    tensor_expect_layout(l->attn_output_a,  DS4_TENSOR_Q8_0, 2, DS4_N_HEAD_DIM * (DS4_N_HEAD / DS4_N_OUT_GROUP), out_low_dim, 0);
    tensor_expect_layout(l->attn_output_b,  DS4_TENSOR_Q8_0, 2, out_low_dim, DS4_N_EMBD, 0);

    tensor_expect_plain_layout(l->hc_ffn_fn, 2, hc_dim, hc_mix_dim, 0);
    tensor_expect_layout(l->hc_ffn_scale,   DS4_TENSOR_F32,  1, 3, 0, 0);
    tensor_expect_layout(l->hc_ffn_base,    DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
    tensor_expect_layout(l->ffn_norm,       DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_plain_layout(l->ffn_gate_inp, 2, DS4_N_EMBD, DS4_N_EXPERT, 0);
    tensor_expect_layout(l->ffn_exp_probs_b, DS4_TENSOR_F32, 1, DS4_N_EXPERT, 0, 0);
    tensor_expect_routed_expert(l->ffn_gate_exps, 3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
4_N_HC + (uint64_t)DS4_N_HC * DS4_N_HC;
    const uint64_t q_dim = (uint64_t)DS4_N_HEAD * DS4_N_HEAD_DIM;
    const uint64_t out_low_dim = (uint64_t)DS4_N_OUT_GROUP * DS4_N_LORA_O;
    const ds4_layer_weights *l = &w->block;

    tensor_expect_layout(w->hc_head_base,  DS4_TENSOR_F32,  1, DS4_N_HC, 0, 0);
    tensor_expect_plain_layout(w->hc_head_fn, 2, hc_dim, DS4_N_HC, 0);
    tensor_expect_layout(w->hc_head_scale, DS4_TENSOR_F32,  1, 1, 0, 0);
    tensor_expect_layout(w->e_proj,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_EMBD, 0);
    tensor_expect_layout(w->h_proj,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_EMBD, 0);
    tensor_expect_layout(w->enorm,         DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(w->hnorm,         DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(w->norm,          DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);

    tensor_expect_plain_layout(l->hc_attn_fn, 2, hc_dim, hc_mix_dim, 0);
    tensor_expect_layout(l->hc_attn_scale,  DS4_TENSOR_F32,  1, 3, 0, 0);
    tensor_expect_layout(l->hc_attn_base,   DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
    tensor_expect_layout(l->attn_norm,      DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(l->attn_q_a,       DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_LORA_Q, 0);
    tensor_expect_layout(l->attn_q_a_norm,  DS4_TENSOR_F32,  1, DS4_N_LORA_Q, 0, 0);
    tensor_expect_layout(l->attn_q_b,       DS4_TENSOR_Q8_0, 2, DS4_N_LORA_Q, q_dim, 0);
    tensor_expect_layout(l->attn_kv,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_HEAD_DIM, 0);
    tensor_expect_layout(l->attn_kv_a_norm, DS4_TENSOR_F32,  1, DS4_N_HEAD_DIM, 0, 0);
    tensor_expect_layout(l->attn_sinks,     DS4_TENSOR_F32,  1, DS4_N_HEAD, 0, 0);
    tensor_expect_layout(l->attn_output_a,  DS4_TENSOR_Q8_0, 2, DS4_N_HEAD_DIM * (DS4_N_HEAD / DS4_N_OUT_GROUP), out_low_dim, 0);
    tensor_expect_layout(l->attn_output_b,  DS4_TENSOR_Q8_0, 2, out_low_dim, DS4_N_EMBD, 0);

    tensor_expect_plain_layout(l->hc_ffn_fn, 2, hc_dim, hc_mix_dim, 0);
    tensor_expect_layout(l->hc_ffn_scale,   DS4_TENSOR_F32,  1, 3, 0, 0);
    tensor_expect_layout(l->hc_ffn_base,    DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
    tensor_expect_layout(l->ffn_norm,       DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_plain_layout(l->ffn_gate_inp, 2, DS4_N_EMBD, DS4_N_EXPERT, 0);
    tensor_expect_layout(l->ffn_exp_probs_b, DS4_TENSOR_F32, 1, DS4_N_EXPERT, 0, 0);
    tensor_expect_routed_expert(l->ffn_gate_exps, 3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
4_N_HC + (uint64_t)DS4_N_HC * DS4_N_HC;
    const uint64_t q_dim = (uint64_t)DS4_N_HEAD * DS4_N_HEAD_DIM;
    const uint64_t out_low_dim = (uint64_t)DS4_N_OUT_GROUP * DS4_N_LORA_O;
    const ds4_layer_weights *l = &w->block;

    tensor_expect_layout(w->hc_head_base,  DS4_TENSOR_F32,  1, DS4_N_HC, 0, 0);
    tensor_expect_plain_layout(w->hc_head_fn, 2, hc_dim, DS4_N_HC, 0);
    tensor_expect_layout(w->hc_head_scale, DS4_TENSOR_F32,  1, 1, 0, 0);
    tensor_expect_layout(w->e_proj,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_EMBD, 0);
    tensor_expect_layout(w->h_proj,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_EMBD, 0);
    tensor_expect_layout(w->enorm,         DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(w->hnorm,         DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(w->norm,          DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);

    tensor_expect_plain_layout(l->hc_attn_fn, 2, hc_dim, hc_mix_dim, 0);
    tensor_expect_layout(l->hc_attn_scale,  DS4_TENSOR_F32,  1, 3, 0, 0);
    tensor_expect_layout(l->hc_attn_base,   DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
    tensor_expect_layout(l->attn_norm,      DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(l->attn_q_a,       DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_LORA_Q, 0);
    tensor_expect_layout(l->attn_q_a_norm,  DS4_TENSOR_F32,  1, DS4_N_LORA_Q, 0, 0);
    tensor_expect_layout(l->attn_q_b,       DS4_TENSOR_Q8_0, 2, DS4_N_LORA_Q, q_dim, 0);
    tensor_expect_layout(l->attn_kv,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_HEAD_DIM, 0);
    tensor_expect_layout(l->attn_kv_a_norm, DS4_TENSOR_F32,  1, DS4_N_HEAD_DIM, 0, 0);
    tensor_expect_layout(l->attn_sinks,     DS4_TENSOR_F32,  1, DS4_N_HEAD, 0, 0);
    tensor_expect_layout(l->attn_output_a,  DS4_TENSOR_Q8_0, 2, DS4_N_HEAD_DIM * (DS4_N_HEAD / DS4_N_OUT_GROUP), out_low_dim, 0);
    tensor_expect_layout(l->attn_output_b,  DS4_TENSOR_Q8_0, 2, out_low_dim, DS4_N_EMBD, 0);

    tensor_expect_plain_layout(l->hc_ffn_fn, 2, hc_dim, hc_mix_dim, 0);
    tensor_expect_layout(l->hc_ffn_scale,   DS4_TENSOR_F32,  1, 3, 0, 0);
    tensor_expect_layout(l->hc_ffn_base,    DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
    tensor_expect_layout(l->ffn_norm,       DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_plain_layout(l->ffn_gate_inp, 2, DS4_N_EMBD, DS4_N_EXPERT, 0);
    tensor_expect_layout(l->ffn_exp_probs_b, DS4_TENSOR_F32, 1, DS4_N_EXPERT, 0, 0);
    tensor_expect_routed_expert(l->ffn_gate_exps, 3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
4_N_HC + (uint64_t)DS4_N_HC * DS4_N_HC;
    const uint64_t q_dim = (uint64_t)DS4_N_HEAD * DS4_N_HEAD_DIM;
    const uint64_t out_low_dim = (uint64_t)DS4_N_OUT_GROUP * DS4_N_LORA_O;
    const ds4_layer_weights *l = &w->block;

    tensor_expect_layout(w->hc_head_base,  DS4_TENSOR_F32,  1, DS4_N_HC, 0, 0);
    tensor_expect_plain_layout(w->hc_head_fn, 2, hc_dim, DS4_N_HC, 0);
    tensor_expect_layout(w->hc_head_scale, DS4_TENSOR_F32,  1, 1, 0, 0);
    tensor_expect_layout(w->e_proj,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_EMBD, 0);
    tensor_expect_layout(w->h_proj,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_EMBD, 0);
    tensor_expect_layout(w->enorm,         DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(w->hnorm,         DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(w->norm,          DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);

    tensor_expect_plain_layout(l->hc_attn_fn, 2, hc_dim, hc_mix_dim, 0);
    tensor_expect_layout(l->hc_attn_scale,  DS4_TENSOR_F32,  1, 3, 0, 0);
    tensor_expect_layout(l->hc_attn_base,   DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
    tensor_expect_layout(l->attn_norm,      DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_layout(l->attn_q_a,       DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_LORA_Q, 0);
    tensor_expect_layout(l->attn_q_a_norm,  DS4_TENSOR_F32,  1, DS4_N_LORA_Q, 0, 0);
    tensor_expect_layout(l->attn_q_b,       DS4_TENSOR_Q8_0, 2, DS4_N_LORA_Q, q_dim, 0);
    tensor_expect_layout(l->attn_kv,        DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_HEAD_DIM, 0);
    tensor_expect_layout(l->attn_kv_a_norm, DS4_TENSOR_F32,  1, DS4_N_HEAD_DIM, 0, 0);
    tensor_expect_layout(l->attn_sinks,     DS4_TENSOR_F32,  1, DS4_N_HEAD, 0, 0);
    tensor_expect_layout(l->attn_output_a,  DS4_TENSOR_Q8_0, 2, DS4_N_HEAD_DIM * (DS4_N_HEAD / DS4_N_OUT_GROUP), out_low_dim, 0);
    tensor_expect_layout(l->attn_output_b,  DS4_TENSOR_Q8_0, 2, out_low_dim, DS4_N_EMBD, 0);

    tensor_expect_plain_layout(l->hc_ffn_fn, 2, hc_dim, hc_mix_dim, 0);
    tensor_expect_layout(l->hc_ffn_scale,   DS4_TENSOR_F32,  1, 3, 0, 0);
    tensor_expect_layout(l->hc_ffn_base,    DS4_TENSOR_F32,  1, hc_mix_dim, 0, 0);
    tensor_expect_layout(l->ffn_norm,       DS4_TENSOR_F32,  1, DS4_N_EMBD, 0, 0);
    tensor_expect_plain_layout(l->ffn_gate_inp, 2, DS4_N_EMBD, DS4_N_EXPERT, 0);
    tensor_expect_layout(l->ffn_exp_probs_b, DS4_TENSOR_F32, 1, DS4_N_EXPERT, 0, 0);
    tensor_expect_routed_expert(l->ffn_gate_exps, 3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Suggest a minimal correctness-preserving optimization for this excerpt.

File: ds4.c

```c
;
    tensor_expect_layout(l->ffn_exp_probs_b, DS4_TENSOR_F32, 1, DS4_N_EXPERT, 0, 0);
    tensor_expect_routed_expert(l->ffn_gate_exps, 3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
    tensor_expect_routed_expert(l->ffn_up_exps,   3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
    tensor_expect_routed_expert(l->ffn_down_exps, 3, DS4_N_FF_EXP, DS4_N_EMBD, DS4_N_EXPERT);
    if (l->ffn_gate_exps->type != l->ffn_up_exps->type) {
        ds4_die("MTP routed gate/up experts use different quant types");
    }
    tensor_expect_layout(l->ffn_gate_shexp, DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
    tensor_expect_layout(l->ffn_up_shexp,   DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
    tensor_expect_layout(l->ffn_down_shexp, DS4_TENSOR_Q8_0, 2, DS4_N_FF_EXP, DS4_N_EMBD, 0);
}

static void validate_compress_ratio_metadata(const ds4_model *m) {
    const char *key = "deepseek4.attention.compress_ratios";
    ds4_array_ref arr;
    if (!model_get_array(m, key, &arr) ||
        (arr.type != GGUF_VALUE_UINT32 && arr.type != GGUF_VALUE_INT32)) {
        fprintf(stderr, "ds4: required int32/uint32 array metadata key is missing: %s\n", key);
        exit(1);
    }
    if (arr.len < DS4_N_LAYER) {
        ds4_die("deepseek4.attention.compress_ratios is shorter than the layer count");
    }

    ds4_cursor c = cursor_at(m, arr.data_pos);
    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        uint32_t got = 0;
        if (arr.type == GGUF_VALUE_UINT32) {
            if (!cursor_u32(&c, &got)) ds4_die(c.error);
        } else {
            int32_t v = 0;
            if (!cursor_read(&c, &v, sizeof(v))) ds4_die(c.error);
            if (v < 0) ds4_die("metadata array contains a negative value");
            got = (uint32_t)v;
        }

        const uint32_t expected = ds4_layer_compress_ratio(il);
        if (got != expected) {
            fprintf(stderr,
                    "ds4: unexpected DeepSeek4 compression ratio at layer %u: got %u, expected %u\n",
                    il, got, expected);
            exit(1);
        }
    }
}

static void config_expect_f32(const char *name, float got, float expected);

static void validate_swiglu_clamp_metadata(const ds4_model *m) {
    const char *key = "deepseek4.swiglu_clamp_exp";
    ds4_array_ref arr;
    if (!model_get_array(m, key, &arr) ||
        (arr.type != GGUF_VALUE_FLOAT32 && arr.type != GGUF_VALUE_FLOAT64)) {
        fprintf(stderr, "ds4: required float array metadata key is missing: %s\n", key);
        exit(1);
    }
    if (arr.len < DS4_N_LAYER) {
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Suggest a minimal correctness-preserving optimization for this excerpt.

File: ds4.c

```c
;
    tensor_expect_layout(l->ffn_exp_probs_b, DS4_TENSOR_F32, 1, DS4_N_EXPERT, 0, 0);
    tensor_expect_routed_expert(l->ffn_gate_exps, 3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
    tensor_expect_routed_expert(l->ffn_up_exps,   3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
    tensor_expect_routed_expert(l->ffn_down_exps, 3, DS4_N_FF_EXP, DS4_N_EMBD, DS4_N_EXPERT);
    if (l->ffn_gate_exps->type != l->ffn_up_exps->type) {
        ds4_die("MTP routed gate/up experts use different quant types");
    }
    tensor_expect_layout(l->ffn_gate_shexp, DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
    tensor_expect_layout(l->ffn_up_shexp,   DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
    tensor_expect_layout(l->ffn_down_shexp, DS4_TENSOR_Q8_0, 2, DS4_N_FF_EXP, DS4_N_EMBD, 0);
}

static void validate_compress_ratio_metadata(const ds4_model *m) {
    const char *key = "deepseek4.attention.compress_ratios";
    ds4_array_ref arr;
    if (!model_get_array(m, key, &arr) ||
        (arr.type != GGUF_VALUE_UINT32 && arr.type != GGUF_VALUE_INT32)) {
        fprintf(stderr, "ds4: required int32/uint32 array metadata key is missing: %s\n", key);
        exit(1);
    }
    if (arr.len < DS4_N_LAYER) {
        ds4_die("deepseek4.attention.compress_ratios is shorter than the layer count");
    }

    ds4_cursor c = cursor_at(m, arr.data_pos);
    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        uint32_t got = 0;
        if (arr.type == GGUF_VALUE_UINT32) {
            if (!cursor_u32(&c, &got)) ds4_die(c.error);
        } else {
            int32_t v = 0;
            if (!cursor_read(&c, &v, sizeof(v))) ds4_die(c.error);
            if (v < 0) ds4_die("metadata array contains a negative value");
            got = (uint32_t)v;
        }

        const uint32_t expected = ds4_layer_compress_ratio(il);
        if (got != expected) {
            fprintf(stderr,
                    "ds4: unexpected DeepSeek4 compression ratio at layer %u: got %u, expected %u\n",
                    il, got, expected);
            exit(1);
        }
    }
}

static void config_expect_f32(const char *name, float got, float expected);

static void validate_swiglu_clamp_metadata(const ds4_model *m) {
    const char *key = "deepseek4.swiglu_clamp_exp";
    ds4_array_ref arr;
    if (!model_get_array(m, key, &arr) ||
        (arr.type != GGUF_VALUE_FLOAT32 && arr.type != GGUF_VALUE_FLOAT64)) {
        fprintf(stderr, "ds4: required float array metadata key is missing: %s\n", key);
        exit(1);
    }
    if (arr.len < DS4_N_LAYER) {
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Suggest a minimal correctness-preserving optimization for this excerpt.

File: ds4.c

```c
;
    tensor_expect_layout(l->ffn_exp_probs_b, DS4_TENSOR_F32, 1, DS4_N_EXPERT, 0, 0);
    tensor_expect_routed_expert(l->ffn_gate_exps, 3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
    tensor_expect_routed_expert(l->ffn_up_exps,   3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
    tensor_expect_routed_expert(l->ffn_down_exps, 3, DS4_N_FF_EXP, DS4_N_EMBD, DS4_N_EXPERT);
    if (l->ffn_gate_exps->type != l->ffn_up_exps->type) {
        ds4_die("MTP routed gate/up experts use different quant types");
    }
    tensor_expect_layout(l->ffn_gate_shexp, DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
    tensor_expect_layout(l->ffn_up_shexp,   DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
    tensor_expect_layout(l->ffn_down_shexp, DS4_TENSOR_Q8_0, 2, DS4_N_FF_EXP, DS4_N_EMBD, 0);
}

static void validate_compress_ratio_metadata(const ds4_model *m) {
    const char *key = "deepseek4.attention.compress_ratios";
    ds4_array_ref arr;
    if (!model_get_array(m, key, &arr) ||
        (arr.type != GGUF_VALUE_UINT32 && arr.type != GGUF_VALUE_INT32)) {
        fprintf(stderr, "ds4: required int32/uint32 array metadata key is missing: %s\n", key);
        exit(1);
    }
    if (arr.len < DS4_N_LAYER) {
        ds4_die("deepseek4.attention.compress_ratios is shorter than the layer count");
    }

    ds4_cursor c = cursor_at(m, arr.data_pos);
    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        uint32_t got = 0;
        if (arr.type == GGUF_VALUE_UINT32) {
            if (!cursor_u32(&c, &got)) ds4_die(c.error);
        } else {
            int32_t v = 0;
            if (!cursor_read(&c, &v, sizeof(v))) ds4_die(c.error);
            if (v < 0) ds4_die("metadata array contains a negative value");
            got = (uint32_t)v;
        }

        const uint32_t expected = ds4_layer_compress_ratio(il);
        if (got != expected) {
            fprintf(stderr,
                    "ds4: unexpected DeepSeek4 compression ratio at layer %u: got %u, expected %u\n",
                    il, got, expected);
            exit(1);
        }
    }
}

static void config_expect_f32(const char *name, float got, float expected);

static void validate_swiglu_clamp_metadata(const ds4_model *m) {
    const char *key = "deepseek4.swiglu_clamp_exp";
    ds4_array_ref arr;
    if (!model_get_array(m, key, &arr) ||
        (arr.type != GGUF_VALUE_FLOAT32 && arr.type != GGUF_VALUE_FLOAT64)) {
        fprintf(stderr, "ds4: required float array metadata key is missing: %s\n", key);
        exit(1);
    }
    if (arr.len < DS4_N_LAYER) {
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Suggest a minimal correctness-preserving optimization for this excerpt.

File: ds4.c

```c
;
    tensor_expect_layout(l->ffn_exp_probs_b, DS4_TENSOR_F32, 1, DS4_N_EXPERT, 0, 0);
    tensor_expect_routed_expert(l->ffn_gate_exps, 3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
    tensor_expect_routed_expert(l->ffn_up_exps,   3, DS4_N_EMBD, DS4_N_FF_EXP, DS4_N_EXPERT);
    tensor_expect_routed_expert(l->ffn_down_exps, 3, DS4_N_FF_EXP, DS4_N_EMBD, DS4_N_EXPERT);
    if (l->ffn_gate_exps->type != l->ffn_up_exps->type) {
        ds4_die("MTP routed gate/up experts use different quant types");
    }
    tensor_expect_layout(l->ffn_gate_shexp, DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
    tensor_expect_layout(l->ffn_up_shexp,   DS4_TENSOR_Q8_0, 2, DS4_N_EMBD, DS4_N_FF_EXP, 0);
    tensor_expect_layout(l->ffn_down_shexp, DS4_TENSOR_Q8_0, 2, DS4_N_FF_EXP, DS4_N_EMBD, 0);
}

static void validate_compress_ratio_metadata(const ds4_model *m) {
    const char *key = "deepseek4.attention.compress_ratios";
    ds4_array_ref arr;
    if (!model_get_array(m, key, &arr) ||
        (arr.type != GGUF_VALUE_UINT32 && arr.type != GGUF_VALUE_INT32)) {
        fprintf(stderr, "ds4: required int32/uint32 array metadata key is missing: %s\n", key);
        exit(1);
    }
    if (arr.len < DS4_N_LAYER) {
        ds4_die("deepseek4.attention.compress_ratios is shorter than the layer count");
    }

    ds4_cursor c = cursor_at(m, arr.data_pos);
    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        uint32_t got = 0;
        if (arr.type == GGUF_VALUE_UINT32) {
            if (!cursor_u32(&c, &got)) ds4_die(c.error);
        } else {
            int32_t v = 0;
            if (!cursor_read(&c, &v, sizeof(v))) ds4_die(c.error);
            if (v < 0) ds4_die("metadata array contains a negative value");
            got = (uint32_t)v;
        }

        const uint32_t expected = ds4_layer_compress_ratio(il);
        if (got != expected) {
            fprintf(stderr,
                    "ds4: unexpected DeepSeek4 compression ratio at layer %u: got %u, expected %u\n",
                    il, got, expected);
            exit(1);
        }
    }
}

static void config_expect_f32(const char *name, float got, float expected);

static void validate_swiglu_clamp_metadata(const ds4_model *m) {
    const char *key = "deepseek4.swiglu_clamp_exp";
    ds4_array_ref arr;
    if (!model_get_array(m, key, &arr) ||
        (arr.type != GGUF_VALUE_FLOAT32 && arr.type != GGUF_VALUE_FLOAT64)) {
        fprintf(stderr, "ds4: required float array metadata key is missing: %s\n", key);
        exit(1);
    }
    if (arr.len < DS4_N_LAYER) {
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: ds4.c

```c
arr.type != GGUF_VALUE_FLOAT64)) {
        fprintf(stderr, "ds4: required float array metadata key is missing: %s\n", key);
        exit(1);
    }
    if (arr.len < DS4_N_LAYER) {
        ds4_die("deepseek4.swiglu_clamp_exp is shorter than the layer count");
    }

    ds4_cursor c = cursor_at(m, arr.data_pos);
    for (uint32_t i = 0; i < DS4_N_LAYER; i++) {
        float got = 0.0f;
        if (arr.type == GGUF_VALUE_FLOAT32) {
            if (!cursor_read(&c, &got, sizeof(got))) ds4_die(c.error);
        } else {
            double v = 0.0;
            if (!cursor_read(&c, &v, sizeof(v))) ds4_die(c.error);
            got = (float)v;
        }
        config_expect_f32("swiglu_clamp_exp", got, DS4_SWIGLU_CLAMP_EXP);
    }
}

static void config_expect_u32(const char *name, uint32_t got, uint32_t expected) {
    if (got == expected) return;
    fprintf(stderr, "ds4: expected %s=%u for DeepSeek4 Flash, got %u\n",
            name, expected, got);
    exit(1);
}

static void config_expect_f32(const char *name, float got, float expected) {
    const float scale = fabsf(expected) > 1.0f ? fabsf(expected) : 1.0f;
    if (fabsf(got - expected) <= scale * 1.0e-6f) return;
    fprintf(stderr, "ds4: expected %s=%.9g for DeepSeek4 Flash, got %.9g\n",
            name, (double)expected, (double)got);
    exit(1);
}

static void config_expect_bool(const char *name, bool got, bool expected) {
    if (got == expected) return;
    fprintf(stderr, "ds4: expected %s=%s for DeepSeek4 Flash, got %s\n",
            name, expected ? "true" : "false", got ? "true" : "false");
    exit(1);
}

static void config_validate_fixed_shape(uint32_t n_layer) {
    config_expect_u32("block_count",                  n_layer,                 DS4_N_LAYER);
}

/* Validate metadata values that affect semantics: attention shape, HC count,
 * expert routing, RoPE scaling, compression ratios, and SwiGLU clamp. */
static void config_validate_model(const ds4_model *m) {
    const uint32_t n_layer = required_u32(m, "deepseek4.block_count");
    const uint32_t n_embd = required_u32(m, "deepseek4.embedding_length");
    const uint32_t n_vocab = required_u32(m, "deepseek4.vocab_size");
    const uint32_t n_head = required_u32(m, "deepseek4.attention.head_count");
    const uint32_t n_head_kv = required_u32(m, "deepseek4.attention.head_count_kv");
    const uint32_t n_head_dim = required_u32(m, "deepseek4.attention.key_length");
    const uint32_t n_value_dim = required_u32(m, "deepseek4.attention.value_length");
    const uint32_t n_rot = required_u32(m, "deepseek4.rope.dimension_count");
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: ds4.c

```c
arr.type != GGUF_VALUE_FLOAT64)) {
        fprintf(stderr, "ds4: required float array metadata key is missing: %s\n", key);
        exit(1);
    }
    if (arr.len < DS4_N_LAYER) {
        ds4_die("deepseek4.swiglu_clamp_exp is shorter than the layer count");
    }

    ds4_cursor c = cursor_at(m, arr.data_pos);
    for (uint32_t i = 0; i < DS4_N_LAYER; i++) {
        float got = 0.0f;
        if (arr.type == GGUF_VALUE_FLOAT32) {
            if (!cursor_read(&c, &got, sizeof(got))) ds4_die(c.error);
        } else {
            double v = 0.0;
            if (!cursor_read(&c, &v, sizeof(v))) ds4_die(c.error);
            got = (float)v;
        }
        config_expect_f32("swiglu_clamp_exp", got, DS4_SWIGLU_CLAMP_EXP);
    }
}

static void config_expect_u32(const char *name, uint32_t got, uint32_t expected) {
    if (got == expected) return;
    fprintf(stderr, "ds4: expected %s=%u for DeepSeek4 Flash, got %u\n",
            name, expected, got);
    exit(1);
}

static void config_expect_f32(const char *name, float got, float expected) {
    const float scale = fabsf(expected) > 1.0f ? fabsf(expected) : 1.0f;
    if (fabsf(got - expected) <= scale * 1.0e-6f) return;
    fprintf(stderr, "ds4: expected %s=%.9g for DeepSeek4 Flash, got %.9g\n",
            name, (double)expected, (double)got);
    exit(1);
}

static void config_expect_bool(const char *name, bool got, bool expected) {
    if (got == expected) return;
    fprintf(stderr, "ds4: expected %s=%s for DeepSeek4 Flash, got %s\n",
            name, expected ? "true" : "false", got ? "true" : "false");
    exit(1);
}

static void config_validate_fixed_shape(uint32_t n_layer) {
    config_expect_u32("block_count",                  n_layer,                 DS4_N_LAYER);
}

/* Validate metadata values that affect semantics: attention shape, HC count,
 * expert routing, RoPE scaling, compression ratios, and SwiGLU clamp. */
static void config_validate_model(const ds4_model *m) {
    const uint32_t n_layer = required_u32(m, "deepseek4.block_count");
    const uint32_t n_embd = required_u32(m, "deepseek4.embedding_length");
    const uint32_t n_vocab = required_u32(m, "deepseek4.vocab_size");
    const uint32_t n_head = required_u32(m, "deepseek4.attention.head_count");
    const uint32_t n_head_kv = required_u32(m, "deepseek4.attention.head_count_kv");
    const uint32_t n_head_dim = required_u32(m, "deepseek4.attention.key_length");
    const uint32_t n_value_dim = required_u32(m, "deepseek4.attention.value_length");
    const uint32_t n_rot = required_u32(m, "deepseek4.rope.dimension_count");
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: ds4.c

```c
arr.type != GGUF_VALUE_FLOAT64)) {
        fprintf(stderr, "ds4: required float array metadata key is missing: %s\n", key);
        exit(1);
    }
    if (arr.len < DS4_N_LAYER) {
        ds4_die("deepseek4.swiglu_clamp_exp is shorter than the layer count");
    }

    ds4_cursor c = cursor_at(m, arr.data_pos);
    for (uint32_t i = 0; i < DS4_N_LAYER; i++) {
        float got = 0.0f;
        if (arr.type == GGUF_VALUE_FLOAT32) {
            if (!cursor_read(&c, &got, sizeof(got))) ds4_die(c.error);
        } else {
            double v = 0.0;
            if (!cursor_read(&c, &v, sizeof(v))) ds4_die(c.error);
            got = (float)v;
        }
        config_expect_f32("swiglu_clamp_exp", got, DS4_SWIGLU_CLAMP_EXP);
    }
}

static void config_expect_u32(const char *name, uint32_t got, uint32_t expected) {
    if (got == expected) return;
    fprintf(stderr, "ds4: expected %s=%u for DeepSeek4 Flash, got %u\n",
            name, expected, got);
    exit(1);
}

static void config_expect_f32(const char *name, float got, float expected) {
    const float scale = fabsf(expected) > 1.0f ? fabsf(expected) : 1.0f;
    if (fabsf(got - expected) <= scale * 1.0e-6f) return;
    fprintf(stderr, "ds4: expected %s=%.9g for DeepSeek4 Flash, got %.9g\n",
            name, (double)expected, (double)got);
    exit(1);
}

static void config_expect_bool(const char *name, bool got, bool expected) {
    if (got == expected) return;
    fprintf(stderr, "ds4: expected %s=%s for DeepSeek4 Flash, got %s\n",
            name, expected ? "true" : "false", got ? "true" : "false");
    exit(1);
}

static void config_validate_fixed_shape(uint32_t n_layer) {
    config_expect_u32("block_count",                  n_layer,                 DS4_N_LAYER);
}

/* Validate metadata values that affect semantics: attention shape, HC count,
 * expert routing, RoPE scaling, compression ratios, and SwiGLU clamp. */
static void config_validate_model(const ds4_model *m) {
    const uint32_t n_layer = required_u32(m, "deepseek4.block_count");
    const uint32_t n_embd = required_u32(m, "deepseek4.embedding_length");
    const uint32_t n_vocab = required_u32(m, "deepseek4.vocab_size");
    const uint32_t n_head = required_u32(m, "deepseek4.attention.head_count");
    const uint32_t n_head_kv = required_u32(m, "deepseek4.attention.head_count_kv");
    const uint32_t n_head_dim = required_u32(m, "deepseek4.attention.key_length");
    const uint32_t n_value_dim = required_u32(m, "deepseek4.attention.value_length");
    const uint32_t n_rot = required_u32(m, "deepseek4.rope.dimension_count");
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: ds4.c

```c
arr.type != GGUF_VALUE_FLOAT64)) {
        fprintf(stderr, "ds4: required float array metadata key is missing: %s\n", key);
        exit(1);
    }
    if (arr.len < DS4_N_LAYER) {
        ds4_die("deepseek4.swiglu_clamp_exp is shorter than the layer count");
    }

    ds4_cursor c = cursor_at(m, arr.data_pos);
    for (uint32_t i = 0; i < DS4_N_LAYER; i++) {
        float got = 0.0f;
        if (arr.type == GGUF_VALUE_FLOAT32) {
            if (!cursor_read(&c, &got, sizeof(got))) ds4_die(c.error);
        } else {
            double v = 0.0;
            if (!cursor_read(&c, &v, sizeof(v))) ds4_die(c.error);
            got = (float)v;
        }
        config_expect_f32("swiglu_clamp_exp", got, DS4_SWIGLU_CLAMP_EXP);
    }
}

static void config_expect_u32(const char *name, uint32_t got, uint32_t expected) {
    if (got == expected) return;
    fprintf(stderr, "ds4: expected %s=%u for DeepSeek4 Flash, got %u\n",
            name, expected, got);
    exit(1);
}

static void config_expect_f32(const char *name, float got, float expected) {
    const float scale = fabsf(expected) > 1.0f ? fabsf(expected) : 1.0f;
    if (fabsf(got - expected) <= scale * 1.0e-6f) return;
    fprintf(stderr, "ds4: expected %s=%.9g for DeepSeek4 Flash, got %.9g\n",
            name, (double)expected, (double)got);
    exit(1);
}

static void config_expect_bool(const char *name, bool got, bool expected) {
    if (got == expected) return;
    fprintf(stderr, "ds4: expected %s=%s for DeepSeek4 Flash, got %s\n",
            name, expected ? "true" : "false", got ? "true" : "false");
    exit(1);
}

static void config_validate_fixed_shape(uint32_t n_layer) {
    config_expect_u32("block_count",                  n_layer,                 DS4_N_LAYER);
}

/* Validate metadata values that affect semantics: attention shape, HC count,
 * expert routing, RoPE scaling, compression ratios, and SwiGLU clamp. */
static void config_validate_model(const ds4_model *m) {
    const uint32_t n_layer = required_u32(m, "deepseek4.block_count");
    const uint32_t n_embd = required_u32(m, "deepseek4.embedding_length");
    const uint32_t n_vocab = required_u32(m, "deepseek4.vocab_size");
    const uint32_t n_head = required_u32(m, "deepseek4.attention.head_count");
    const uint32_t n_head_kv = required_u32(m, "deepseek4.attention.head_count_kv");
    const uint32_t n_head_dim = required_u32(m, "deepseek4.attention.key_length");
    const uint32_t n_value_dim = required_u32(m, "deepseek4.attention.value_length");
    const uint32_t n_rot = required_u32(m, "deepseek4.rope.dimension_count");
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: ds4.c

```c
on.key_length");
    const uint32_t n_value_dim = required_u32(m, "deepseek4.attention.value_length");
    const uint32_t n_rot = required_u32(m, "deepseek4.rope.dimension_count");
    const uint32_t n_lora_q = required_u32(m, "deepseek4.attention.q_lora_rank");
    const uint32_t n_lora_o = required_u32(m, "deepseek4.attention.output_lora_rank");
    const uint32_t n_out_group = required_u32(m, "deepseek4.attention.output_group_count");
    const uint32_t n_expert = required_u32(m, "deepseek4.expert_count");
    const uint32_t n_expert_used = required_u32(m, "deepseek4.expert_used_count");
    const uint32_t n_ff_exp = required_u32(m, "deepseek4.expert_feed_forward_length");
    const uint32_t n_expert_shared = required_u32(m, "deepseek4.expert_shared_count");
    const uint32_t n_hash_layer = required_u32(m, "deepseek4.hash_layer_count");
    uint32_t n_expert_groups = 0;
    uint32_t n_group_used = 0;
    model_get_u32(m, "deepseek4.expert_group_count", &n_expert_groups);
    model_get_u32(m, "deepseek4.expert_group_used_count", &n_group_used);
    config_expect_u32("embedding_length",            n_embd,         DS4_N_EMBD);
    config_expect_u32("vocab_size",                  n_vocab,        DS4_N_VOCAB);
    config_expect_u32("attention.head_count",        n_head,         DS4_N_HEAD);
    config_expect_u32("attention.key_length",        n_head_dim,     DS4_N_HEAD_DIM);
    config_expect_u32("attention.head_count_kv",     n_head_kv,      DS4_N_HEAD_KV);
    config_expect_u32("attention.value_length",      n_value_dim,    DS4_N_VALUE_DIM);
    config_expect_u32("rope.dimension_count",        n_rot,          DS4_N_ROT);
    config_expect_u32("attention.output_group_count", n_out_group,    DS4_N_OUT_GROUP);
    config_expect_u32("attention.q_lora_rank",       n_lora_q,        DS4_N_LORA_Q);
    config_expect_u32("attention.output_lora_rank",  n_lora_o,        DS4_N_LORA_O);
    config_expect_u32("expert_count",               n_expert,        DS4_N_EXPERT);
    config_expect_u32("expert_used_count",          n_expert_used,   DS4_N_EXPERT_USED);
    config_expect_u32("expert_feed_forward_length", n_ff_exp,        DS4_N_FF_EXP);
    config_expect_u32("expert_shared_count",         n_expert_shared, DS4_N_EXPERT_SHARED);
    config_expect_u32("hash_layer_count",            n_hash_layer,    DS4_N_HASH_LAYER);
    config_expect_u32("expert_group_count",         n_expert_groups, 0);
    config_expect_u32("expert_group_used_count",    n_group_used,    0);

    const uint32_t n_swa = required_u32(m, "deepseek4.attention.sliding_window");
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: ds4.c

```c
on.key_length");
    const uint32_t n_value_dim = required_u32(m, "deepseek4.attention.value_length");
    const uint32_t n_rot = required_u32(m, "deepseek4.rope.dimension_count");
    const uint32_t n_lora_q = required_u32(m, "deepseek4.attention.q_lora_rank");
    const uint32_t n_lora_o = required_u32(m, "deepseek4.attention.output_lora_rank");
    const uint32_t n_out_group = required_u32(m, "deepseek4.attention.output_group_count");
    const uint32_t n_expert = required_u32(m, "deepseek4.expert_count");
    const uint32_t n_expert_used = required_u32(m, "deepseek4.expert_used_count");
    const uint32_t n_ff_exp = required_u32(m, "deepseek4.expert_feed_forward_length");
    const uint32_t n_expert_shared = required_u32(m, "deepseek4.expert_shared_count");
    const uint32_t n_hash_layer = required_u32(m, "deepseek4.hash_layer_count");
    uint32_t n_expert_groups = 0;
    uint32_t n_group_used = 0;
    model_get_u32(m, "deepseek4.expert_group_count", &n_expert_groups);
    model_get_u32(m, "deepseek4.expert_group_used_count", &n_group_used);
    config_expect_u32("embedding_length",            n_embd,         DS4_N_EMBD);
    config_expect_u32("vocab_size",                  n_vocab,        DS4_N_VOCAB);
    config_expect_u32("attention.head_count",        n_head,         DS4_N_HEAD);
    config_expect_u32("attention.key_length",        n_head_dim,     DS4_N_HEAD_DIM);
    config_expect_u32("attention.head_count_kv",     n_head_kv,      DS4_N_HEAD_KV);
    config_expect_u32("attention.value_length",      n_value_dim,    DS4_N_VALUE_DIM);
    config_expect_u32("rope.dimension_count",        n_rot,          DS4_N_ROT);
    config_expect_u32("attention.output_group_count", n_out_group,    DS4_N_OUT_GROUP);
    config_expect_u32("attention.q_lora_rank",       n_lora_q,        DS4_N_LORA_Q);
    config_expect_u32("attention.output_lora_rank",  n_lora_o,        DS4_N_LORA_O);
    config_expect_u32("expert_count",               n_expert,        DS4_N_EXPERT);
    config_expect_u32("expert_used_count",          n_expert_used,   DS4_N_EXPERT_USED);
    config_expect_u32("expert_feed_forward_length", n_ff_exp,        DS4_N_FF_EXP);
    config_expect_u32("expert_shared_count",         n_expert_shared, DS4_N_EXPERT_SHARED);
    config_expect_u32("hash_layer_count",            n_hash_layer,    DS4_N_HASH_LAYER);
    config_expect_u32("expert_group_count",         n_expert_groups, 0);
    config_expect_u32("expert_group_used_count",    n_group_used,    0);

    const uint32_t n_swa = required_u32(m, "deepseek4.attention.sliding_window");
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: ds4.c

```c
on.key_length");
    const uint32_t n_value_dim = required_u32(m, "deepseek4.attention.value_length");
    const uint32_t n_rot = required_u32(m, "deepseek4.rope.dimension_count");
    const uint32_t n_lora_q = required_u32(m, "deepseek4.attention.q_lora_rank");
    const uint32_t n_lora_o = required_u32(m, "deepseek4.attention.output_lora_rank");
    const uint32_t n_out_group = required_u32(m, "deepseek4.attention.output_group_count");
    const uint32_t n_expert = required_u32(m, "deepseek4.expert_count");
    const uint32_t n_expert_used = required_u32(m, "deepseek4.expert_used_count");
    const uint32_t n_ff_exp = required_u32(m, "deepseek4.expert_feed_forward_length");
    const uint32_t n_expert_shared = required_u32(m, "deepseek4.expert_shared_count");
    const uint32_t n_hash_layer = required_u32(m, "deepseek4.hash_layer_count");
    uint32_t n_expert_groups = 0;
    uint32_t n_group_used = 0;
    model_get_u32(m, "deepseek4.expert_group_count", &n_expert_groups);
    model_get_u32(m, "deepseek4.expert_group_used_count", &n_group_used);
    config_expect_u32("embedding_length",            n_embd,         DS4_N_EMBD);
    config_expect_u32("vocab_size",                  n_vocab,        DS4_N_VOCAB);
    config_expect_u32("attention.head_count",        n_head,         DS4_N_HEAD);
    config_expect_u32("attention.key_length",        n_head_dim,     DS4_N_HEAD_DIM);
    config_expect_u32("attention.head_count_kv",     n_head_kv,      DS4_N_HEAD_KV);
    config_expect_u32("attention.value_length",      n_value_dim,    DS4_N_VALUE_DIM);
    config_expect_u32("rope.dimension_count",        n_rot,          DS4_N_ROT);
    config_expect_u32("attention.output_group_count", n_out_group,    DS4_N_OUT_GROUP);
    config_expect_u32("attention.q_lora_rank",       n_lora_q,        DS4_N_LORA_Q);
    config_expect_u32("attention.output_lora_rank",  n_lora_o,        DS4_N_LORA_O);
    config_expect_u32("expert_count",               n_expert,        DS4_N_EXPERT);
    config_expect_u32("expert_used_count",          n_expert_used,   DS4_N_EXPERT_USED);
    config_expect_u32("expert_feed_forward_length", n_ff_exp,        DS4_N_FF_EXP);
    config_expect_u32("expert_shared_count",         n_expert_shared, DS4_N_EXPERT_SHARED);
    config_expect_u32("hash_layer_count",            n_hash_layer,    DS4_N_HASH_LAYER);
    config_expect_u32("expert_group_count",         n_expert_groups, 0);
    config_expect_u32("expert_group_used_count",    n_group_used,    0);

    const uint32_t n_swa = required_u32(m, "deepseek4.attention.sliding_window");
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: ds4.c

```c
on.key_length");
    const uint32_t n_value_dim = required_u32(m, "deepseek4.attention.value_length");
    const uint32_t n_rot = required_u32(m, "deepseek4.rope.dimension_count");
    const uint32_t n_lora_q = required_u32(m, "deepseek4.attention.q_lora_rank");
    const uint32_t n_lora_o = required_u32(m, "deepseek4.attention.output_lora_rank");
    const uint32_t n_out_group = required_u32(m, "deepseek4.attention.output_group_count");
    const uint32_t n_expert = required_u32(m, "deepseek4.expert_count");
    const uint32_t n_expert_used = required_u32(m, "deepseek4.expert_used_count");
    const uint32_t n_ff_exp = required_u32(m, "deepseek4.expert_feed_forward_length");
    const uint32_t n_expert_shared = required_u32(m, "deepseek4.expert_shared_count");
    const uint32_t n_hash_layer = required_u32(m, "deepseek4.hash_layer_count");
    uint32_t n_expert_groups = 0;
    uint32_t n_group_used = 0;
    model_get_u32(m, "deepseek4.expert_group_count", &n_expert_groups);
    model_get_u32(m, "deepseek4.expert_group_used_count", &n_group_used);
    config_expect_u32("embedding_length",            n_embd,         DS4_N_EMBD);
    config_expect_u32("vocab_size",                  n_vocab,        DS4_N_VOCAB);
    config_expect_u32("attention.head_count",        n_head,         DS4_N_HEAD);
    config_expect_u32("attention.key_length",        n_head_dim,     DS4_N_HEAD_DIM);
    config_expect_u32("attention.head_count_kv",     n_head_kv,      DS4_N_HEAD_KV);
    config_expect_u32("attention.value_length",      n_value_dim,    DS4_N_VALUE_DIM);
    config_expect_u32("rope.dimension_count",        n_rot,          DS4_N_ROT);
    config_expect_u32("attention.output_group_count", n_out_group,    DS4_N_OUT_GROUP);
    config_expect_u32("attention.q_lora_rank",       n_lora_q,        DS4_N_LORA_Q);
    config_expect_u32("attention.output_lora_rank",  n_lora_o,        DS4_N_LORA_O);
    config_expect_u32("expert_count",               n_expert,        DS4_N_EXPERT);
    config_expect_u32("expert_used_count",          n_expert_used,   DS4_N_EXPERT_USED);
    config_expect_u32("expert_feed_forward_length", n_ff_exp,        DS4_N_FF_EXP);
    config_expect_u32("expert_shared_count",         n_expert_shared, DS4_N_EXPERT_SHARED);
    config_expect_u32("hash_layer_count",            n_hash_layer,    DS4_N_HASH_LAYER);
    config_expect_u32("expert_group_count",         n_expert_groups, 0);
    config_expect_u32("expert_group_used_count",    n_group_used,    0);

    const uint32_t n_swa = required_u32(m, "deepseek4.attention.sliding_window");
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
b082b080819,
    0x08192b1908080808, 0x08192b1908081919, 0x08192b192b2b0808, 0x08192b2b19190819,
    0x082b080808080808, 0x082b08080808082b, 0x082b080808082b2b, 0x082b080819081908,
    0x082b0808192b0819, 0x082b08082b080808, 0x082b08082b08082b, 0x082b0819082b2b19,
    0x082b081919082b08, 0x082b082b08080808, 0x082b082b0808082b, 0x082b190808080819,
    0x082b190808081908, 0x082b190808190808, 0x082b190819080808, 0x082b19081919192b,
    0x082b191908080808, 0x082b191919080819, 0x082b1919192b1908, 0x082b192b2b190808,
    0x082b2b0808082b08, 0x082b2b08082b0808, 0x082b2b082b191908, 0x082b2b2b19081908,
    0x1908080808080819, 0x1908080808081908, 0x1908080808190808, 0x1908080808192b08,
    0x19080808082b0819, 0x19080808082b1908, 0x1908080819080808, 0x1908080819082b08,
    0x190808081919192b, 0x19080808192b0808, 0x190808082b080819, 0x190808082b081908,
    0x190808082b190808, 0x1908081908080808, 0x19080819082b0808, 0x19080819192b0819,
    0x190808192b080808, 0x190808192b081919, 0x1908082b08080819, 0x1908082b08190808,
    0x1908082b19082b08, 0x1908082b1919192b, 0x1908082b192b2b08, 0x1908190808080808,
    0x1908190808082b08, 0x19081908082b0808, 0x190819082b080808, 0x190819082b192b19,
    0x190819190819082b, 0x19081919082b1908, 0x1908192b08080808, 0x19082b0808080819,
    0x19082b0808081908, 0x19082b0808190808, 0x19082b0819080808, 0x19082b0819081919,
    0x19082b1908080808, 0x19082b1919192b08, 0x19082b19192b0819, 0x19082b192b08082b,
    0x19082b2b19081919, 0x19082b2b2b190808, 0x1919080808080808, 0x1919080808082b08,
    0x1919080808190819, 0x1919080808192b19, 0x19190808082b0808, 0x191908082b080808,
    0x191908082b082b08, 0x1919081908081908, 0x191908191908082b, 0x191908192b2b1908,
    0x1919082b2b190819, 0x191919082b190808, 0x191919082b19082b, 0x1919191908082b2b,
    0x1919192b08080819, 0x1919192b19191908, 0x19192b0808080808, 0x19192b0808190819,
    0x19192b0808192b19, 0x19192b08192b1908, 0x19192b1919080808, 0x19192b2b08082b08,
    0x192b080808081908, 0x192b080808190808, 0x192b080819080808, 0x192b0808192b2b08,
    0x192b081908080808, 0x192b081919191919, 0x192b082b08192b08, 0x192b082b192b0808,
    0x192b190808080808, 0x192b190808081919, 0x192b191908190808, 0x192b19190819082b,
    0x192b19192b081908, 0x192b2b081908082b, 0x2b08080808080808, 0x2b0808080808082b,
    0x2b08080808082b2b, 0x2b08080819080819, 0x2b0808082b08082b, 0x2b08081908081908,
    0x2b08081908192b08, 0x2b08081919080808, 0x2b08082b08190819, 0x2b08190808080819,
    0x2b08190808081908, 0x2b08190808190808, 0x2b08190808191919, 0x2b08190819080808,
```


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
b082b080819,
    0x08192b1908080808, 0x08192b1908081919, 0x08192b192b2b0808, 0x08192b2b19190819,
    0x082b080808080808, 0x082b08080808082b, 0x082b080808082b2b, 0x082b080819081908,
    0x082b0808192b0819, 0x082b08082b080808, 0x082b08082b08082b, 0x082b0819082b2b19,
    0x082b081919082b08, 0x082b082b08080808, 0x082b082b0808082b, 0x082b190808080819,
    0x082b190808081908, 0x082b190808190808, 0x082b190819080808, 0x082b19081919192b,
    0x082b191908080808, 0x082b191919080819, 0x082b1919192b1908, 0x082b192b2b190808,
    0x082b2b0808082b08, 0x082b2b08082b0808, 0x082b2b082b191908, 0x082b2b2b19081908,
    0x1908080808080819, 0x1908080808081908, 0x1908080808190808, 0x1908080808192b08,
    0x19080808082b0819, 0x19080808082b1908, 0x1908080819080808, 0x1908080819082b08,
    0x190808081919192b, 0x19080808192b0808, 0x190808082b080819, 0x190808082b081908,
    0x190808082b190808, 0x1908081908080808, 0x19080819082b0808, 0x19080819192b0819,
    0x190808192b080808, 0x190808192b081919, 0x1908082b08080819, 0x1908082b08190808,
    0x1908082b19082b08, 0x1908082b1919192b, 0x1908082b192b2b08, 0x1908190808080808,
    0x1908190808082b08, 0x19081908082b0808, 0x190819082b080808, 0x190819082b192b19,
    0x190819190819082b, 0x19081919082b1908, 0x1908192b08080808, 0x19082b0808080819,
    0x19082b0808081908, 0x19082b0808190808, 0x19082b0819080808, 0x19082b0819081919,
    0x19082b1908080808, 0x19082b1919192b08, 0x19082b19192b0819, 0x19082b192b08082b,
    0x19082b2b19081919, 0x19082b2b2b190808, 0x1919080808080808, 0x1919080808082b08,
    0x1919080808190819, 0x1919080808192b19, 0x19190808082b0808, 0x191908082b080808,
    0x191908082b082b08, 0x1919081908081908, 0x191908191908082b, 0x191908192b2b1908,
    0x1919082b2b190819, 0x191919082b190808, 0x191919082b19082b, 0x1919191908082b2b,
    0x1919192b08080819, 0x1919192b19191908, 0x19192b0808080808, 0x19192b0808190819,
    0x19192b0808192b19, 0x19192b08192b1908, 0x19192b1919080808, 0x19192b2b08082b08,
    0x192b080808081908, 0x192b080808190808, 0x192b080819080808, 0x192b0808192b2b08,
    0x192b081908080808, 0x192b081919191919, 0x192b082b08192b08, 0x192b082b192b0808,
    0x192b190808080808, 0x192b190808081919, 0x192b191908190808, 0x192b19190819082b,
    0x192b19192b081908, 0x192b2b081908082b, 0x2b08080808080808, 0x2b0808080808082b,
    0x2b08080808082b2b, 0x2b08080819080819, 0x2b0808082b08082b, 0x2b08081908081908,
    0x2b08081908192b08, 0x2b08081919080808, 0x2b08082b08190819, 0x2b08190808080819,
    0x2b08190808081908, 0x2b08190808190808, 0x2b08190808191919, 0x2b08190819080808,
```


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
n_expert_groups, 0);
    config_expect_u32("expert_group_used_count",    n_group_used,    0);

    const uint32_t n_swa = required_u32(m, "deepseek4.attention.sliding_window");
    config_expect_u32("attention.sliding_window",     n_swa,                   DS4_N_SWA);
    const uint32_t n_indexer_head = required_u32(m, "deepseek4.attention.indexer.head_count");
    const uint32_t n_indexer_head_dim = required_u32(m, "deepseek4.attention.indexer.key_length");
    const uint32_t n_indexer_top_k = required_u32(m, "deepseek4.attention.indexer.top_k");
    config_expect_u32("attention.indexer.head_count", n_indexer_head,     DS4_N_INDEXER_HEAD);
    config_expect_u32("attention.indexer.key_length", n_indexer_head_dim, DS4_N_INDEXER_HEAD_DIM);
    config_expect_u32("attention.indexer.top_k",      n_indexer_top_k,    DS4_N_INDEXER_TOP_K);
    const uint32_t n_hc = required_u32(m, "deepseek4.hyper_connection.count");
    config_expect_u32("hyper_connection.count", n_hc, DS4_N_HC);
    const uint32_t n_hc_sinkhorn_iter = required_u32(m, "deepseek4.hyper_connection.sinkhorn_iterations");
    config_expect_u32("hyper_connection.sinkhorn_iterations", n_hc_sinkhorn_iter, DS4_N_HC_SINKHORN_ITER);

    config_validate_fixed_shape(n_layer);
    validate_compress_ratio_metadata(m);

    validate_swiglu_clamp_metadata(m);

    const uint64_t rope_orig_ctx = required_u64(m, "deepseek4.rope.scaling.original_context_length");
    if (rope_orig_ctx != DS4_ROPE_ORIG_CTX) {
        fprintf(stderr, "ds4: expected rope.scaling.original_context_length=%" PRIu64
                " for DeepSeek4 Flash, got %" PRIu64 "\n",
                (uint64_t)DS4_ROPE_ORIG_CTX, rope_orig_ctx);
        exit(1);
    }
    const float rope_freq_base = required_f32(m, "deepseek4.rope.freq_base");
    config_expect_f32("rope.freq_base", rope_freq_base, DS4_ROPE_FREQ_BASE);
    const float rope_scale_factor = required_f32(m, "deepseek4.rope.scaling.factor");
    config_expect_f32("rope.scaling.factor", rope_scale_factor, DS4_ROPE_SCALE_FACTOR);
    const float rope_yarn_beta_fast = required_f32(m, "deepseek4.rope.scaling.yarn_beta_fast");
    config_expect_f32("rope.scaling.yarn_beta_fast", rope_yarn_beta_fast, DS4_ROPE_YARN_BETA_FAST);
    const float rope_yarn_beta_slow = required_f32(m, "deepseek4.rope.scaling.yarn_beta_slow");
    config_expect_f32("rope.scaling.yarn_beta_slow", rope_yarn_beta_slow, DS4_ROPE_YARN_BETA_SLOW);
    const float compress_rope_freq_base = required_f32(m, "deepseek4.attention.compress_rope_freq_base");
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
n_expert_groups, 0);
    config_expect_u32("expert_group_used_count",    n_group_used,    0);

    const uint32_t n_swa = required_u32(m, "deepseek4.attention.sliding_window");
    config_expect_u32("attention.sliding_window",     n_swa,                   DS4_N_SWA);
    const uint32_t n_indexer_head = required_u32(m, "deepseek4.attention.indexer.head_count");
    const uint32_t n_indexer_head_dim = required_u32(m, "deepseek4.attention.indexer.key_length");
    const uint32_t n_indexer_top_k = required_u32(m, "deepseek4.attention.indexer.top_k");
    config_expect_u32("attention.indexer.head_count", n_indexer_head,     DS4_N_INDEXER_HEAD);
    config_expect_u32("attention.indexer.key_length", n_indexer_head_dim, DS4_N_INDEXER_HEAD_DIM);
    config_expect_u32("attention.indexer.top_k",      n_indexer_top_k,    DS4_N_INDEXER_TOP_K);
    const uint32_t n_hc = required_u32(m, "deepseek4.hyper_connection.count");
    config_expect_u32("hyper_connection.count", n_hc, DS4_N_HC);
    const uint32_t n_hc_sinkhorn_iter = required_u32(m, "deepseek4.hyper_connection.sinkhorn_iterations");
    config_expect_u32("hyper_connection.sinkhorn_iterations", n_hc_sinkhorn_iter, DS4_N_HC_SINKHORN_ITER);

    config_validate_fixed_shape(n_layer);
    validate_compress_ratio_metadata(m);

    validate_swiglu_clamp_metadata(m);

    const uint64_t rope_orig_ctx = required_u64(m, "deepseek4.rope.scaling.original_context_length");
    if (rope_orig_ctx != DS4_ROPE_ORIG_CTX) {
        fprintf(stderr, "ds4: expected rope.scaling.original_context_length=%" PRIu64
                " for DeepSeek4 Flash, got %" PRIu64 "\n",
                (uint64_t)DS4_ROPE_ORIG_CTX, rope_orig_ctx);
        exit(1);
    }
    const float rope_freq_base = required_f32(m, "deepseek4.rope.freq_base");
    config_expect_f32("rope.freq_base", rope_freq_base, DS4_ROPE_FREQ_BASE);
    const float rope_scale_factor = required_f32(m, "deepseek4.rope.scaling.factor");
    config_expect_f32("rope.scaling.factor", rope_scale_factor, DS4_ROPE_SCALE_FACTOR);
    const float rope_yarn_beta_fast = required_f32(m, "deepseek4.rope.scaling.yarn_beta_fast");
    config_expect_f32("rope.scaling.yarn_beta_fast", rope_yarn_beta_fast, DS4_ROPE_YARN_BETA_FAST);
    const float rope_yarn_beta_slow = required_f32(m, "deepseek4.rope.scaling.yarn_beta_slow");
    config_expect_f32("rope.scaling.yarn_beta_slow", rope_yarn_beta_slow, DS4_ROPE_YARN_BETA_SLOW);
    const float compress_rope_freq_base = required_f32(m, "deepseek4.attention.compress_rope_freq_base");
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
n_expert_groups, 0);
    config_expect_u32("expert_group_used_count",    n_group_used,    0);

    const uint32_t n_swa = required_u32(m, "deepseek4.attention.sliding_window");
    config_expect_u32("attention.sliding_window",     n_swa,                   DS4_N_SWA);
    const uint32_t n_indexer_head = required_u32(m, "deepseek4.attention.indexer.head_count");
    const uint32_t n_indexer_head_dim = required_u32(m, "deepseek4.attention.indexer.key_length");
    const uint32_t n_indexer_top_k = required_u32(m, "deepseek4.attention.indexer.top_k");
    config_expect_u32("attention.indexer.head_count", n_indexer_head,     DS4_N_INDEXER_HEAD);
    config_expect_u32("attention.indexer.key_length", n_indexer_head_dim, DS4_N_INDEXER_HEAD_DIM);
    config_expect_u32("attention.indexer.top_k",      n_indexer_top_k,    DS4_N_INDEXER_TOP_K);
    const uint32_t n_hc = required_u32(m, "deepseek4.hyper_connection.count");
    config_expect_u32("hyper_connection.count", n_hc, DS4_N_HC);
    const uint32_t n_hc_sinkhorn_iter = required_u32(m, "deepseek4.hyper_connection.sinkhorn_iterations");
    config_expect_u32("hyper_connection.sinkhorn_iterations", n_hc_sinkhorn_iter, DS4_N_HC_SINKHORN_ITER);

    config_validate_fixed_shape(n_layer);
    validate_compress_ratio_metadata(m);

    validate_swiglu_clamp_metadata(m);

    const uint64_t rope_orig_ctx = required_u64(m, "deepseek4.rope.scaling.original_context_length");
    if (rope_orig_ctx != DS4_ROPE_ORIG_CTX) {
        fprintf(stderr, "ds4: expected rope.scaling.original_context_length=%" PRIu64
                " for DeepSeek4 Flash, got %" PRIu64 "\n",
                (uint64_t)DS4_ROPE_ORIG_CTX, rope_orig_ctx);
        exit(1);
    }
    const float rope_freq_base = required_f32(m, "deepseek4.rope.freq_base");
    config_expect_f32("rope.freq_base", rope_freq_base, DS4_ROPE_FREQ_BASE);
    const float rope_scale_factor = required_f32(m, "deepseek4.rope.scaling.factor");
    config_expect_f32("rope.scaling.factor", rope_scale_factor, DS4_ROPE_SCALE_FACTOR);
    const float rope_yarn_beta_fast = required_f32(m, "deepseek4.rope.scaling.yarn_beta_fast");
    config_expect_f32("rope.scaling.yarn_beta_fast", rope_yarn_beta_fast, DS4_ROPE_YARN_BETA_FAST);
    const float rope_yarn_beta_slow = required_f32(m, "deepseek4.rope.scaling.yarn_beta_slow");
    config_expect_f32("rope.scaling.yarn_beta_slow", rope_yarn_beta_slow, DS4_ROPE_YARN_BETA_SLOW);
    const float compress_rope_freq_base = required_f32(m, "deepseek4.attention.compress_rope_freq_base");
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
n_expert_groups, 0);
    config_expect_u32("expert_group_used_count",    n_group_used,    0);

    const uint32_t n_swa = required_u32(m, "deepseek4.attention.sliding_window");
    config_expect_u32("attention.sliding_window",     n_swa,                   DS4_N_SWA);
    const uint32_t n_indexer_head = required_u32(m, "deepseek4.attention.indexer.head_count");
    const uint32_t n_indexer_head_dim = required_u32(m, "deepseek4.attention.indexer.key_length");
    const uint32_t n_indexer_top_k = required_u32(m, "deepseek4.attention.indexer.top_k");
    config_expect_u32("attention.indexer.head_count", n_indexer_head,     DS4_N_INDEXER_HEAD);
    config_expect_u32("attention.indexer.key_length", n_indexer_head_dim, DS4_N_INDEXER_HEAD_DIM);
    config_expect_u32("attention.indexer.top_k",      n_indexer_top_k,    DS4_N_INDEXER_TOP_K);
    const uint32_t n_hc = required_u32(m, "deepseek4.hyper_connection.count");
    config_expect_u32("hyper_connection.count", n_hc, DS4_N_HC);
    const uint32_t n_hc_sinkhorn_iter = required_u32(m, "deepseek4.hyper_connection.sinkhorn_iterations");
    config_expect_u32("hyper_connection.sinkhorn_iterations", n_hc_sinkhorn_iter, DS4_N_HC_SINKHORN_ITER);

    config_validate_fixed_shape(n_layer);
    validate_compress_ratio_metadata(m);

    validate_swiglu_clamp_metadata(m);

    const uint64_t rope_orig_ctx = required_u64(m, "deepseek4.rope.scaling.original_context_length");
    if (rope_orig_ctx != DS4_ROPE_ORIG_CTX) {
        fprintf(stderr, "ds4: expected rope.scaling.original_context_length=%" PRIu64
                " for DeepSeek4 Flash, got %" PRIu64 "\n",
                (uint64_t)DS4_ROPE_ORIG_CTX, rope_orig_ctx);
        exit(1);
    }
    const float rope_freq_base = required_f32(m, "deepseek4.rope.freq_base");
    config_expect_f32("rope.freq_base", rope_freq_base, DS4_ROPE_FREQ_BASE);
    const float rope_scale_factor = required_f32(m, "deepseek4.rope.scaling.factor");
    config_expect_f32("rope.scaling.factor", rope_scale_factor, DS4_ROPE_SCALE_FACTOR);
    const float rope_yarn_beta_fast = required_f32(m, "deepseek4.rope.scaling.yarn_beta_fast");
    config_expect_f32("rope.scaling.yarn_beta_fast", rope_yarn_beta_fast, DS4_ROPE_YARN_BETA_FAST);
    const float rope_yarn_beta_slow = required_f32(m, "deepseek4.rope.scaling.yarn_beta_slow");
    config_expect_f32("rope.scaling.yarn_beta_slow", rope_yarn_beta_slow, DS4_ROPE_YARN_BETA_SLOW);
    const float compress_rope_freq_base = required_f32(m, "deepseek4.attention.compress_rope_freq_base");
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Suggest a minimal correctness-preserving optimization for this excerpt.

File: ds4.c

```c
pe.scaling.yarn_beta_slow", rope_yarn_beta_slow, DS4_ROPE_YARN_BETA_SLOW);
    const float compress_rope_freq_base = required_f32(m, "deepseek4.attention.compress_rope_freq_base");
    config_expect_f32("attention.compress_rope_freq_base", compress_rope_freq_base, DS4_COMPRESS_ROPE_FREQ_BASE);
    const float expert_weight_scale = required_f32(m, "deepseek4.expert_weights_scale");
    config_expect_f32("expert_weights_scale", expert_weight_scale, DS4_EXPERT_WEIGHT_SCALE);
    const float rms_eps = required_f32(m, "deepseek4.attention.layer_norm_rms_epsilon");
    config_expect_f32("attention.layer_norm_rms_epsilon", rms_eps, DS4_RMS_EPS);
    const float hc_eps = required_f32(m, "deepseek4.hyper_connection.epsilon");
    config_expect_f32("hyper_connection.epsilon", hc_eps, DS4_HC_EPS);
    const bool expert_weight_norm = required_bool(m, "deepseek4.expert_weights_norm");
    config_expect_bool("expert_weights_norm", expert_weight_norm, true);
}

/* Bind tensor names once into the fixed DS4 layer layout.  This is the point
 * where stringly GGUF metadata becomes direct model-specific pointers. */
static void weights_bind(ds4_weights *w, const ds4_model *m) {
    memset(w, 0, sizeof(*w));
    w->token_embd       = required_tensor(m, "token_embd.weight");
    w->output_hc_base   = required_tensor(m, "output_hc_base.weight");
    w->output_hc_fn     = required_tensor(m, "output_hc_fn.weight");
    w->output_hc_scale  = required_tensor(m, "output_hc_scale.weight");
    w->output_norm      = required_tensor(m, "output_norm.weight");
    w->output           = required_tensor(m, "output.weight");

    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        ds4_layer_weights *l = &w->layer[il];
        const uint32_t compress_ratio = ds4_layer_compress_ratio(il);

        l->hc_attn_fn      = required_tensorf(m, "blk.%u.hc_attn_fn.weight", il);
        l->hc_attn_scale   = required_tensorf(m, "blk.%u.hc_attn_scale.weight", il);
        l->hc_attn_base    = required_tensorf(m, "blk.%u.hc_attn_base.weight", il);
        l->attn_norm       = required_tensorf(m, "blk.%u.attn_norm.weight", il);
        l->attn_q_a        = required_tensorf(m, "blk.%u.attn_q_a.weight", il);
        l->attn_q_a_norm   = required_tensorf(m, "blk.%u.attn_q_a_norm.weight", il);
        l->attn_q_b        = required_tensorf(m, "blk.%u.attn_q_b.weight", il);
        l->attn_kv         = required_tensorf(m, "blk.%u.attn_kv.weight", il);
        l->attn_kv_a_norm  = required_tensorf(m, "blk.%u.attn_kv_a_norm.weight", il);
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Suggest a minimal correctness-preserving optimization for this excerpt.

File: ds4.c

```c
pe.scaling.yarn_beta_slow", rope_yarn_beta_slow, DS4_ROPE_YARN_BETA_SLOW);
    const float compress_rope_freq_base = required_f32(m, "deepseek4.attention.compress_rope_freq_base");
    config_expect_f32("attention.compress_rope_freq_base", compress_rope_freq_base, DS4_COMPRESS_ROPE_FREQ_BASE);
    const float expert_weight_scale = required_f32(m, "deepseek4.expert_weights_scale");
    config_expect_f32("expert_weights_scale", expert_weight_scale, DS4_EXPERT_WEIGHT_SCALE);
    const float rms_eps = required_f32(m, "deepseek4.attention.layer_norm_rms_epsilon");
    config_expect_f32("attention.layer_norm_rms_epsilon", rms_eps, DS4_RMS_EPS);
    const float hc_eps = required_f32(m, "deepseek4.hyper_connection.epsilon");
    config_expect_f32("hyper_connection.epsilon", hc_eps, DS4_HC_EPS);
    const bool expert_weight_norm = required_bool(m, "deepseek4.expert_weights_norm");
    config_expect_bool("expert_weights_norm", expert_weight_norm, true);
}

/* Bind tensor names once into the fixed DS4 layer layout.  This is the point
 * where stringly GGUF metadata becomes direct model-specific pointers. */
static void weights_bind(ds4_weights *w, const ds4_model *m) {
    memset(w, 0, sizeof(*w));
    w->token_embd       = required_tensor(m, "token_embd.weight");
    w->output_hc_base   = required_tensor(m, "output_hc_base.weight");
    w->output_hc_fn     = required_tensor(m, "output_hc_fn.weight");
    w->output_hc_scale  = required_tensor(m, "output_hc_scale.weight");
    w->output_norm      = required_tensor(m, "output_norm.weight");
    w->output           = required_tensor(m, "output.weight");

    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        ds4_layer_weights *l = &w->layer[il];
        const uint32_t compress_ratio = ds4_layer_compress_ratio(il);

        l->hc_attn_fn      = required_tensorf(m, "blk.%u.hc_attn_fn.weight", il);
        l->hc_attn_scale   = required_tensorf(m, "blk.%u.hc_attn_scale.weight", il);
        l->hc_attn_base    = required_tensorf(m, "blk.%u.hc_attn_base.weight", il);
        l->attn_norm       = required_tensorf(m, "blk.%u.attn_norm.weight", il);
        l->attn_q_a        = required_tensorf(m, "blk.%u.attn_q_a.weight", il);
        l->attn_q_a_norm   = required_tensorf(m, "blk.%u.attn_q_a_norm.weight", il);
        l->attn_q_b        = required_tensorf(m, "blk.%u.attn_q_b.weight", il);
        l->attn_kv         = required_tensorf(m, "blk.%u.attn_kv.weight", il);
        l->attn_kv_a_norm  = required_tensorf(m, "blk.%u.attn_kv_a_norm.weight", il);
```<｜Assistant｜></think>