[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
4_weights     *base_weights,
        const ds4_model       *mtp_model,
        const ds4_mtp_weights *mtp,
        int                    token,
        uint32_t               pos,
        float                 *logits,
        int                   *top_id) {
    return metal_graph_eval_mtp_draft_from_hc(g,
                                              base_model,
                                              base_weights,
                                              mtp_model,
                                              mtp,
                                              g->cur_hc,
                                              g->mtp_state_hc,
                                              token,
                                              pos,
                                              logits,
                                              top_id);
}

/* =========================================================================
 * Imatrix Collection.
 * =========================================================================
 *
 * The 2-bit DS4 quants care most about routed MoE experts.  For expert gate
 * and up matrices the matmul input is the FFN-normalized activation row.  For
 * expert down matrices the matmul input is the routed SwiGLU row after route
 * weighting.  During Metal prefill those tensors are already materialized as
 * `batch_ffn_norm`, `batch_router_selected`, and `batch_routed_mid`, so the
 * collector observes the exact release graph without changing inference math.
 *
 * The output is llama.cpp's legacy imatrix `.dat` format.  Entries are packed
 * by expert: one tensor entry contains `n_expert * n_columns` floats and the
 * quantizer slices the vector for each expert.
 */
typedef struct {
    float *gate_up_sum2;   /* [layer][expert][4096] */
    float *down_sum2;      /* [layer][expert][2048] */
    uint32_t gate_up_count[DS4_N_LAYER][DS4_N_EXPERT];
    uint32_t down_count[DS4_N_LAYER][DS4_N_EXPERT];
    float *ffn_norm_buf;
    float *routed_mid_buf;
    uint16_t *routed_mid_f16_buf;
    int   *selected_buf;
    float *sq_tmp;
    uint32_t cap_tokens;
    uint64_t observed_tokens;
    uint64_t observed_routes;
    uint32_t chunks;
    const char *dataset_path;
} ds4_imatrix_collector;

static bool imatrix_collector_init(ds4_imatrix_collector *c, uint32_t cap_tokens, const char *dataset_path) {
    memset(c, 0, sizeof(*c));
    c->cap_tokens = cap_tokens ? cap_tokens : 1u;
    c->dataset_path = dataset_path;
    const size_t gate_n = (size_t)DS4_N_LAYER * DS4_N_EXPERT * DS4_N_EMBD;
```

<｜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
4_weights     *base_weights,
        const ds4_model       *mtp_model,
        const ds4_mtp_weights *mtp,
        int                    token,
        uint32_t               pos,
        float                 *logits,
        int                   *top_id) {
    return metal_graph_eval_mtp_draft_from_hc(g,
                                              base_model,
                                              base_weights,
                                              mtp_model,
                                              mtp,
                                              g->cur_hc,
                                              g->mtp_state_hc,
                                              token,
                                              pos,
                                              logits,
                                              top_id);
}

/* =========================================================================
 * Imatrix Collection.
 * =========================================================================
 *
 * The 2-bit DS4 quants care most about routed MoE experts.  For expert gate
 * and up matrices the matmul input is the FFN-normalized activation row.  For
 * expert down matrices the matmul input is the routed SwiGLU row after route
 * weighting.  During Metal prefill those tensors are already materialized as
 * `batch_ffn_norm`, `batch_router_selected`, and `batch_routed_mid`, so the
 * collector observes the exact release graph without changing inference math.
 *
 * The output is llama.cpp's legacy imatrix `.dat` format.  Entries are packed
 * by expert: one tensor entry contains `n_expert * n_columns` floats and the
 * quantizer slices the vector for each expert.
 */
typedef struct {
    float *gate_up_sum2;   /* [layer][expert][4096] */
    float *down_sum2;      /* [layer][expert][2048] */
    uint32_t gate_up_count[DS4_N_LAYER][DS4_N_EXPERT];
    uint32_t down_count[DS4_N_LAYER][DS4_N_EXPERT];
    float *ffn_norm_buf;
    float *routed_mid_buf;
    uint16_t *routed_mid_f16_buf;
    int   *selected_buf;
    float *sq_tmp;
    uint32_t cap_tokens;
    uint64_t observed_tokens;
    uint64_t observed_routes;
    uint32_t chunks;
    const char *dataset_path;
} ds4_imatrix_collector;

static bool imatrix_collector_init(ds4_imatrix_collector *c, uint32_t cap_tokens, const char *dataset_path) {
    memset(c, 0, sizeof(*c));
    c->cap_tokens = cap_tokens ? cap_tokens : 1u;
    c->dataset_path = dataset_path;
    const size_t gate_n = (size_t)DS4_N_LAYER * DS4_N_EXPERT * DS4_N_EMBD;
```<｜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
4_weights     *base_weights,
        const ds4_model       *mtp_model,
        const ds4_mtp_weights *mtp,
        int                    token,
        uint32_t               pos,
        float                 *logits,
        int                   *top_id) {
    return metal_graph_eval_mtp_draft_from_hc(g,
                                              base_model,
                                              base_weights,
                                              mtp_model,
                                              mtp,
                                              g->cur_hc,
                                              g->mtp_state_hc,
                                              token,
                                              pos,
                                              logits,
                                              top_id);
}

/* =========================================================================
 * Imatrix Collection.
 * =========================================================================
 *
 * The 2-bit DS4 quants care most about routed MoE experts.  For expert gate
 * and up matrices the matmul input is the FFN-normalized activation row.  For
 * expert down matrices the matmul input is the routed SwiGLU row after route
 * weighting.  During Metal prefill those tensors are already materialized as
 * `batch_ffn_norm`, `batch_router_selected`, and `batch_routed_mid`, so the
 * collector observes the exact release graph without changing inference math.
 *
 * The output is llama.cpp's legacy imatrix `.dat` format.  Entries are packed
 * by expert: one tensor entry contains `n_expert * n_columns` floats and the
 * quantizer slices the vector for each expert.
 */
typedef struct {
    float *gate_up_sum2;   /* [layer][expert][4096] */
    float *down_sum2;      /* [layer][expert][2048] */
    uint32_t gate_up_count[DS4_N_LAYER][DS4_N_EXPERT];
    uint32_t down_count[DS4_N_LAYER][DS4_N_EXPERT];
    float *ffn_norm_buf;
    float *routed_mid_buf;
    uint16_t *routed_mid_f16_buf;
    int   *selected_buf;
    float *sq_tmp;
    uint32_t cap_tokens;
    uint64_t observed_tokens;
    uint64_t observed_routes;
    uint32_t chunks;
    const char *dataset_path;
} ds4_imatrix_collector;

static bool imatrix_collector_init(ds4_imatrix_collector *c, uint32_t cap_tokens, const char *dataset_path) {
    memset(c, 0, sizeof(*c));
    c->cap_tokens = cap_tokens ? cap_tokens : 1u;
    c->dataset_path = dataset_path;
    const size_t gate_n = (size_t)DS4_N_LAYER * DS4_N_EXPERT * DS4_N_EMBD;
```

<｜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
4_weights     *base_weights,
        const ds4_model       *mtp_model,
        const ds4_mtp_weights *mtp,
        int                    token,
        uint32_t               pos,
        float                 *logits,
        int                   *top_id) {
    return metal_graph_eval_mtp_draft_from_hc(g,
                                              base_model,
                                              base_weights,
                                              mtp_model,
                                              mtp,
                                              g->cur_hc,
                                              g->mtp_state_hc,
                                              token,
                                              pos,
                                              logits,
                                              top_id);
}

/* =========================================================================
 * Imatrix Collection.
 * =========================================================================
 *
 * The 2-bit DS4 quants care most about routed MoE experts.  For expert gate
 * and up matrices the matmul input is the FFN-normalized activation row.  For
 * expert down matrices the matmul input is the routed SwiGLU row after route
 * weighting.  During Metal prefill those tensors are already materialized as
 * `batch_ffn_norm`, `batch_router_selected`, and `batch_routed_mid`, so the
 * collector observes the exact release graph without changing inference math.
 *
 * The output is llama.cpp's legacy imatrix `.dat` format.  Entries are packed
 * by expert: one tensor entry contains `n_expert * n_columns` floats and the
 * quantizer slices the vector for each expert.
 */
typedef struct {
    float *gate_up_sum2;   /* [layer][expert][4096] */
    float *down_sum2;      /* [layer][expert][2048] */
    uint32_t gate_up_count[DS4_N_LAYER][DS4_N_EXPERT];
    uint32_t down_count[DS4_N_LAYER][DS4_N_EXPERT];
    float *ffn_norm_buf;
    float *routed_mid_buf;
    uint16_t *routed_mid_f16_buf;
    int   *selected_buf;
    float *sq_tmp;
    uint32_t cap_tokens;
    uint64_t observed_tokens;
    uint64_t observed_routes;
    uint32_t chunks;
    const char *dataset_path;
} ds4_imatrix_collector;

static bool imatrix_collector_init(ds4_imatrix_collector *c, uint32_t cap_tokens, const char *dataset_path) {
    memset(c, 0, sizeof(*c));
    c->cap_tokens = cap_tokens ? cap_tokens : 1u;
    c->dataset_path = dataset_path;
    const size_t gate_n = (size_t)DS4_N_LAYER * DS4_N_EXPERT * DS4_N_EMBD;
```<｜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
(c, 0, sizeof(*c));
    c->cap_tokens = cap_tokens ? cap_tokens : 1u;
    c->dataset_path = dataset_path;
    const size_t gate_n = (size_t)DS4_N_LAYER * DS4_N_EXPERT * DS4_N_EMBD;
    const size_t down_n = (size_t)DS4_N_LAYER * DS4_N_EXPERT * DS4_N_FF_EXP;
    c->gate_up_sum2 = xcalloc(gate_n, sizeof(c->gate_up_sum2[0]));
    c->down_sum2 = xcalloc(down_n, sizeof(c->down_sum2[0]));
    c->ffn_norm_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EMBD * sizeof(c->ffn_norm_buf[0]));
    c->routed_mid_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EXPERT_USED * DS4_N_FF_EXP * sizeof(c->routed_mid_buf[0]));
    c->routed_mid_f16_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EXPERT_USED * DS4_N_FF_EXP * sizeof(c->routed_mid_f16_buf[0]));
    c->selected_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EXPERT_USED * sizeof(c->selected_buf[0]));
    c->sq_tmp = xmalloc((size_t)DS4_N_EMBD * sizeof(c->sq_tmp[0]));
    return c->gate_up_sum2 && c->down_sum2 && c->ffn_norm_buf &&
           c->routed_mid_buf && c->routed_mid_f16_buf && c->selected_buf && c->sq_tmp;
}

static void imatrix_collector_free(ds4_imatrix_collector *c) {
    if (!c) return;
    free(c->gate_up_sum2);
    free(c->down_sum2);
    free(c->ffn_norm_buf);
    free(c->routed_mid_buf);
    free(c->routed_mid_f16_buf);
    free(c->selected_buf);
    free(c->sq_tmp);
    memset(c, 0, sizeof(*c));
}

static float *imatrix_gate_up_ptr(ds4_imatrix_collector *c, uint32_t il, uint32_t expert) {
    return c->gate_up_sum2 + ((size_t)il * DS4_N_EXPERT + expert) * DS4_N_EMBD;
}

static float *imatrix_down_ptr(ds4_imatrix_collector *c, uint32_t il, uint32_t expert) {
    return c->down_sum2 + ((size_t)il * DS4_N_EXPERT + expert) * DS4_N_FF_EXP;
}

static bool imatrix_collect_layer_batch(
        ds4_imatrix_collector *c,
        ds4_gpu_graph         *g,
        uint32_t               il,
        uint32_t               n_tokens) {
    if (!c || n_tokens == 0) return true;
    if (n_tokens > c->cap_tokens) return false;

    const uint64_t norm_bytes = (uint64_t)n_tokens * DS4_N_EMBD * sizeof(float);
    const uint64_t mid_elems = (uint64_t)n_tokens * DS4_N_EXPERT_USED * DS4_N_FF_EXP;
    const uint64_t mid_bytes = mid_elems * (g->batch_routed_mid_is_f16 ? sizeof(uint16_t) : sizeof(float));
    const uint64_t sel_bytes = (uint64_t)n_tokens * DS4_N_EXPERT_USED * sizeof(int);
    void *mid_dst = g->batch_routed_mid_is_f16
        ? (void *)c->routed_mid_f16_buf
        : (void *)c->routed_mid_buf;
    if (ds4_gpu_tensor_read(g->batch_ffn_norm, 0, c->ffn_norm_buf, norm_bytes) == 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｜>Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
(c, 0, sizeof(*c));
    c->cap_tokens = cap_tokens ? cap_tokens : 1u;
    c->dataset_path = dataset_path;
    const size_t gate_n = (size_t)DS4_N_LAYER * DS4_N_EXPERT * DS4_N_EMBD;
    const size_t down_n = (size_t)DS4_N_LAYER * DS4_N_EXPERT * DS4_N_FF_EXP;
    c->gate_up_sum2 = xcalloc(gate_n, sizeof(c->gate_up_sum2[0]));
    c->down_sum2 = xcalloc(down_n, sizeof(c->down_sum2[0]));
    c->ffn_norm_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EMBD * sizeof(c->ffn_norm_buf[0]));
    c->routed_mid_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EXPERT_USED * DS4_N_FF_EXP * sizeof(c->routed_mid_buf[0]));
    c->routed_mid_f16_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EXPERT_USED * DS4_N_FF_EXP * sizeof(c->routed_mid_f16_buf[0]));
    c->selected_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EXPERT_USED * sizeof(c->selected_buf[0]));
    c->sq_tmp = xmalloc((size_t)DS4_N_EMBD * sizeof(c->sq_tmp[0]));
    return c->gate_up_sum2 && c->down_sum2 && c->ffn_norm_buf &&
           c->routed_mid_buf && c->routed_mid_f16_buf && c->selected_buf && c->sq_tmp;
}

static void imatrix_collector_free(ds4_imatrix_collector *c) {
    if (!c) return;
    free(c->gate_up_sum2);
    free(c->down_sum2);
    free(c->ffn_norm_buf);
    free(c->routed_mid_buf);
    free(c->routed_mid_f16_buf);
    free(c->selected_buf);
    free(c->sq_tmp);
    memset(c, 0, sizeof(*c));
}

static float *imatrix_gate_up_ptr(ds4_imatrix_collector *c, uint32_t il, uint32_t expert) {
    return c->gate_up_sum2 + ((size_t)il * DS4_N_EXPERT + expert) * DS4_N_EMBD;
}

static float *imatrix_down_ptr(ds4_imatrix_collector *c, uint32_t il, uint32_t expert) {
    return c->down_sum2 + ((size_t)il * DS4_N_EXPERT + expert) * DS4_N_FF_EXP;
}

static bool imatrix_collect_layer_batch(
        ds4_imatrix_collector *c,
        ds4_gpu_graph         *g,
        uint32_t               il,
        uint32_t               n_tokens) {
    if (!c || n_tokens == 0) return true;
    if (n_tokens > c->cap_tokens) return false;

    const uint64_t norm_bytes = (uint64_t)n_tokens * DS4_N_EMBD * sizeof(float);
    const uint64_t mid_elems = (uint64_t)n_tokens * DS4_N_EXPERT_USED * DS4_N_FF_EXP;
    const uint64_t mid_bytes = mid_elems * (g->batch_routed_mid_is_f16 ? sizeof(uint16_t) : sizeof(float));
    const uint64_t sel_bytes = (uint64_t)n_tokens * DS4_N_EXPERT_USED * sizeof(int);
    void *mid_dst = g->batch_routed_mid_is_f16
        ? (void *)c->routed_mid_f16_buf
        : (void *)c->routed_mid_buf;
    if (ds4_gpu_tensor_read(g->batch_ffn_norm, 0, c->ffn_norm_buf, norm_bytes) == 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]
Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
(c, 0, sizeof(*c));
    c->cap_tokens = cap_tokens ? cap_tokens : 1u;
    c->dataset_path = dataset_path;
    const size_t gate_n = (size_t)DS4_N_LAYER * DS4_N_EXPERT * DS4_N_EMBD;
    const size_t down_n = (size_t)DS4_N_LAYER * DS4_N_EXPERT * DS4_N_FF_EXP;
    c->gate_up_sum2 = xcalloc(gate_n, sizeof(c->gate_up_sum2[0]));
    c->down_sum2 = xcalloc(down_n, sizeof(c->down_sum2[0]));
    c->ffn_norm_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EMBD * sizeof(c->ffn_norm_buf[0]));
    c->routed_mid_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EXPERT_USED * DS4_N_FF_EXP * sizeof(c->routed_mid_buf[0]));
    c->routed_mid_f16_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EXPERT_USED * DS4_N_FF_EXP * sizeof(c->routed_mid_f16_buf[0]));
    c->selected_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EXPERT_USED * sizeof(c->selected_buf[0]));
    c->sq_tmp = xmalloc((size_t)DS4_N_EMBD * sizeof(c->sq_tmp[0]));
    return c->gate_up_sum2 && c->down_sum2 && c->ffn_norm_buf &&
           c->routed_mid_buf && c->routed_mid_f16_buf && c->selected_buf && c->sq_tmp;
}

static void imatrix_collector_free(ds4_imatrix_collector *c) {
    if (!c) return;
    free(c->gate_up_sum2);
    free(c->down_sum2);
    free(c->ffn_norm_buf);
    free(c->routed_mid_buf);
    free(c->routed_mid_f16_buf);
    free(c->selected_buf);
    free(c->sq_tmp);
    memset(c, 0, sizeof(*c));
}

static float *imatrix_gate_up_ptr(ds4_imatrix_collector *c, uint32_t il, uint32_t expert) {
    return c->gate_up_sum2 + ((size_t)il * DS4_N_EXPERT + expert) * DS4_N_EMBD;
}

static float *imatrix_down_ptr(ds4_imatrix_collector *c, uint32_t il, uint32_t expert) {
    return c->down_sum2 + ((size_t)il * DS4_N_EXPERT + expert) * DS4_N_FF_EXP;
}

static bool imatrix_collect_layer_batch(
        ds4_imatrix_collector *c,
        ds4_gpu_graph         *g,
        uint32_t               il,
        uint32_t               n_tokens) {
    if (!c || n_tokens == 0) return true;
    if (n_tokens > c->cap_tokens) return false;

    const uint64_t norm_bytes = (uint64_t)n_tokens * DS4_N_EMBD * sizeof(float);
    const uint64_t mid_elems = (uint64_t)n_tokens * DS4_N_EXPERT_USED * DS4_N_FF_EXP;
    const uint64_t mid_bytes = mid_elems * (g->batch_routed_mid_is_f16 ? sizeof(uint16_t) : sizeof(float));
    const uint64_t sel_bytes = (uint64_t)n_tokens * DS4_N_EXPERT_USED * sizeof(int);
    void *mid_dst = g->batch_routed_mid_is_f16
        ? (void *)c->routed_mid_f16_buf
        : (void *)c->routed_mid_buf;
    if (ds4_gpu_tensor_read(g->batch_ffn_norm, 0, c->ffn_norm_buf, norm_bytes) == 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｜>Explain what this code does and identify the inference stage it belongs to.

File: ds4.c

```c
(c, 0, sizeof(*c));
    c->cap_tokens = cap_tokens ? cap_tokens : 1u;
    c->dataset_path = dataset_path;
    const size_t gate_n = (size_t)DS4_N_LAYER * DS4_N_EXPERT * DS4_N_EMBD;
    const size_t down_n = (size_t)DS4_N_LAYER * DS4_N_EXPERT * DS4_N_FF_EXP;
    c->gate_up_sum2 = xcalloc(gate_n, sizeof(c->gate_up_sum2[0]));
    c->down_sum2 = xcalloc(down_n, sizeof(c->down_sum2[0]));
    c->ffn_norm_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EMBD * sizeof(c->ffn_norm_buf[0]));
    c->routed_mid_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EXPERT_USED * DS4_N_FF_EXP * sizeof(c->routed_mid_buf[0]));
    c->routed_mid_f16_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EXPERT_USED * DS4_N_FF_EXP * sizeof(c->routed_mid_f16_buf[0]));
    c->selected_buf = xmalloc((size_t)c->cap_tokens * DS4_N_EXPERT_USED * sizeof(c->selected_buf[0]));
    c->sq_tmp = xmalloc((size_t)DS4_N_EMBD * sizeof(c->sq_tmp[0]));
    return c->gate_up_sum2 && c->down_sum2 && c->ffn_norm_buf &&
           c->routed_mid_buf && c->routed_mid_f16_buf && c->selected_buf && c->sq_tmp;
}

static void imatrix_collector_free(ds4_imatrix_collector *c) {
    if (!c) return;
    free(c->gate_up_sum2);
    free(c->down_sum2);
    free(c->ffn_norm_buf);
    free(c->routed_mid_buf);
    free(c->routed_mid_f16_buf);
    free(c->selected_buf);
    free(c->sq_tmp);
    memset(c, 0, sizeof(*c));
}

static float *imatrix_gate_up_ptr(ds4_imatrix_collector *c, uint32_t il, uint32_t expert) {
    return c->gate_up_sum2 + ((size_t)il * DS4_N_EXPERT + expert) * DS4_N_EMBD;
}

static float *imatrix_down_ptr(ds4_imatrix_collector *c, uint32_t il, uint32_t expert) {
    return c->down_sum2 + ((size_t)il * DS4_N_EXPERT + expert) * DS4_N_FF_EXP;
}

static bool imatrix_collect_layer_batch(
        ds4_imatrix_collector *c,
        ds4_gpu_graph         *g,
        uint32_t               il,
        uint32_t               n_tokens) {
    if (!c || n_tokens == 0) return true;
    if (n_tokens > c->cap_tokens) return false;

    const uint64_t norm_bytes = (uint64_t)n_tokens * DS4_N_EMBD * sizeof(float);
    const uint64_t mid_elems = (uint64_t)n_tokens * DS4_N_EXPERT_USED * DS4_N_FF_EXP;
    const uint64_t mid_bytes = mid_elems * (g->batch_routed_mid_is_f16 ? sizeof(uint16_t) : sizeof(float));
    const uint64_t sel_bytes = (uint64_t)n_tokens * DS4_N_EXPERT_USED * sizeof(int);
    void *mid_dst = g->batch_routed_mid_is_f16
        ? (void *)c->routed_mid_f16_buf
        : (void *)c->routed_mid_buf;
    if (ds4_gpu_tensor_read(g->batch_ffn_norm, 0, c->ffn_norm_buf, norm_bytes) == 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]
Suggest a minimal correctness-preserving optimization for this excerpt.

File: ds4.c

```c
outed_mid_is_f16
        ? (void *)c->routed_mid_f16_buf
        : (void *)c->routed_mid_buf;
    if (ds4_gpu_tensor_read(g->batch_ffn_norm, 0, c->ffn_norm_buf, norm_bytes) == 0 ||
        ds4_gpu_tensor_read(g->batch_routed_mid, 0, mid_dst, mid_bytes) == 0 ||
        ds4_gpu_tensor_read(g->batch_router_selected, 0, c->selected_buf, sel_bytes) == 0)
    {
        return false;
    }

    for (uint32_t t = 0; t < n_tokens; t++) {
        const float *x = c->ffn_norm_buf + (size_t)t * DS4_N_EMBD;
        for (uint32_t i = 0; i < DS4_N_EMBD; i++) c->sq_tmp[i] = x[i] * x[i];

        for (uint32_t slot = 0; slot < DS4_N_EXPERT_USED; slot++) {
            const int expert = c->selected_buf[(size_t)t * DS4_N_EXPERT_USED + slot];
            if (expert < 0 || expert >= DS4_N_EXPERT) continue;

            float *gate_up = imatrix_gate_up_ptr(c, il, (uint32_t)expert);
            for (uint32_t i = 0; i < DS4_N_EMBD; i++) gate_up[i] += c->sq_tmp[i];
            c->gate_up_count[il][expert]++;

            float *down = imatrix_down_ptr(c, il, (uint32_t)expert);
            const size_t mid_off = ((size_t)t * DS4_N_EXPERT_USED + slot) * DS4_N_FF_EXP;
            if (g->batch_routed_mid_is_f16) {
                const uint16_t *mid = c->routed_mid_f16_buf + mid_off;
                for (uint32_t i = 0; i < DS4_N_FF_EXP; i++) {
                    const float v = f16_to_f32(mid[i]);
                    down[i] += v * v;
                }
            } else {
                const float *mid = c->routed_mid_buf + mid_off;
                for (uint32_t i = 0; i < DS4_N_FF_EXP; i++) down[i] += mid[i] * mid[i];
            }
            c->down_count[il][expert]++;
            c->observed_routes++;
        }
    }
    c->observed_tokens += n_tokens;
    c->chunks++;
    return true;
}

static void imatrix_write_i32(FILE *fp, int32_t v) {
    if (fwrite(&v, sizeof(v), 1, fp) != 1) ds4_die("failed to write imatrix");
}

static void imatrix_write_entry(
        FILE       *fp,
        const char *name,
        const float *sum2,
        const uint32_t *counts,
        uint32_t n_expert,
        uint32_t n_col) {
    const int32_t len = (int32_t)strlen(name);
    const int32_t ncall = 1;
    const int32_t nval = (int32_t)((uint64_t)n_expert * n_col);
    imatrix_write_i32(fp, len);
    if (fwrite(name, 1, (size_t)len, fp) != (size_t)len) ds4_die("failed to write imatrix name");
    imatrix_write_i32(fp, ncall);
    imatrix_write_i32(fp, nval);

    float *tmp = xmalloc((size_t)n_col * sizeof(tmp[0]));
    for (uint32_t e = 0; e < n_expert; e++) {
```

<｜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
outed_mid_is_f16
        ? (void *)c->routed_mid_f16_buf
        : (void *)c->routed_mid_buf;
    if (ds4_gpu_tensor_read(g->batch_ffn_norm, 0, c->ffn_norm_buf, norm_bytes) == 0 ||
        ds4_gpu_tensor_read(g->batch_routed_mid, 0, mid_dst, mid_bytes) == 0 ||
        ds4_gpu_tensor_read(g->batch_router_selected, 0, c->selected_buf, sel_bytes) == 0)
    {
        return false;
    }

    for (uint32_t t = 0; t < n_tokens; t++) {
        const float *x = c->ffn_norm_buf + (size_t)t * DS4_N_EMBD;
        for (uint32_t i = 0; i < DS4_N_EMBD; i++) c->sq_tmp[i] = x[i] * x[i];

        for (uint32_t slot = 0; slot < DS4_N_EXPERT_USED; slot++) {
            const int expert = c->selected_buf[(size_t)t * DS4_N_EXPERT_USED + slot];
            if (expert < 0 || expert >= DS4_N_EXPERT) continue;

            float *gate_up = imatrix_gate_up_ptr(c, il, (uint32_t)expert);
            for (uint32_t i = 0; i < DS4_N_EMBD; i++) gate_up[i] += c->sq_tmp[i];
            c->gate_up_count[il][expert]++;

            float *down = imatrix_down_ptr(c, il, (uint32_t)expert);
            const size_t mid_off = ((size_t)t * DS4_N_EXPERT_USED + slot) * DS4_N_FF_EXP;
            if (g->batch_routed_mid_is_f16) {
                const uint16_t *mid = c->routed_mid_f16_buf + mid_off;
                for (uint32_t i = 0; i < DS4_N_FF_EXP; i++) {
                    const float v = f16_to_f32(mid[i]);
                    down[i] += v * v;
                }
            } else {
                const float *mid = c->routed_mid_buf + mid_off;
                for (uint32_t i = 0; i < DS4_N_FF_EXP; i++) down[i] += mid[i] * mid[i];
            }
            c->down_count[il][expert]++;
            c->observed_routes++;
        }
    }
    c->observed_tokens += n_tokens;
    c->chunks++;
    return true;
}

static void imatrix_write_i32(FILE *fp, int32_t v) {
    if (fwrite(&v, sizeof(v), 1, fp) != 1) ds4_die("failed to write imatrix");
}

static void imatrix_write_entry(
        FILE       *fp,
        const char *name,
        const float *sum2,
        const uint32_t *counts,
        uint32_t n_expert,
        uint32_t n_col) {
    const int32_t len = (int32_t)strlen(name);
    const int32_t ncall = 1;
    const int32_t nval = (int32_t)((uint64_t)n_expert * n_col);
    imatrix_write_i32(fp, len);
    if (fwrite(name, 1, (size_t)len, fp) != (size_t)len) ds4_die("failed to write imatrix name");
    imatrix_write_i32(fp, ncall);
    imatrix_write_i32(fp, nval);

    float *tmp = xmalloc((size_t)n_col * sizeof(tmp[0]));
    for (uint32_t e = 0; e < n_expert; e++) {
```<｜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
outed_mid_is_f16
        ? (void *)c->routed_mid_f16_buf
        : (void *)c->routed_mid_buf;
    if (ds4_gpu_tensor_read(g->batch_ffn_norm, 0, c->ffn_norm_buf, norm_bytes) == 0 ||
        ds4_gpu_tensor_read(g->batch_routed_mid, 0, mid_dst, mid_bytes) == 0 ||
        ds4_gpu_tensor_read(g->batch_router_selected, 0, c->selected_buf, sel_bytes) == 0)
    {
        return false;
    }

    for (uint32_t t = 0; t < n_tokens; t++) {
        const float *x = c->ffn_norm_buf + (size_t)t * DS4_N_EMBD;
        for (uint32_t i = 0; i < DS4_N_EMBD; i++) c->sq_tmp[i] = x[i] * x[i];

        for (uint32_t slot = 0; slot < DS4_N_EXPERT_USED; slot++) {
            const int expert = c->selected_buf[(size_t)t * DS4_N_EXPERT_USED + slot];
            if (expert < 0 || expert >= DS4_N_EXPERT) continue;

            float *gate_up = imatrix_gate_up_ptr(c, il, (uint32_t)expert);
            for (uint32_t i = 0; i < DS4_N_EMBD; i++) gate_up[i] += c->sq_tmp[i];
            c->gate_up_count[il][expert]++;

            float *down = imatrix_down_ptr(c, il, (uint32_t)expert);
            const size_t mid_off = ((size_t)t * DS4_N_EXPERT_USED + slot) * DS4_N_FF_EXP;
            if (g->batch_routed_mid_is_f16) {
                const uint16_t *mid = c->routed_mid_f16_buf + mid_off;
                for (uint32_t i = 0; i < DS4_N_FF_EXP; i++) {
                    const float v = f16_to_f32(mid[i]);
                    down[i] += v * v;
                }
            } else {
                const float *mid = c->routed_mid_buf + mid_off;
                for (uint32_t i = 0; i < DS4_N_FF_EXP; i++) down[i] += mid[i] * mid[i];
            }
            c->down_count[il][expert]++;
            c->observed_routes++;
        }
    }
    c->observed_tokens += n_tokens;
    c->chunks++;
    return true;
}

static void imatrix_write_i32(FILE *fp, int32_t v) {
    if (fwrite(&v, sizeof(v), 1, fp) != 1) ds4_die("failed to write imatrix");
}

static void imatrix_write_entry(
        FILE       *fp,
        const char *name,
        const float *sum2,
        const uint32_t *counts,
        uint32_t n_expert,
        uint32_t n_col) {
    const int32_t len = (int32_t)strlen(name);
    const int32_t ncall = 1;
    const int32_t nval = (int32_t)((uint64_t)n_expert * n_col);
    imatrix_write_i32(fp, len);
    if (fwrite(name, 1, (size_t)len, fp) != (size_t)len) ds4_die("failed to write imatrix name");
    imatrix_write_i32(fp, ncall);
    imatrix_write_i32(fp, nval);

    float *tmp = xmalloc((size_t)n_col * sizeof(tmp[0]));
    for (uint32_t e = 0; e < n_expert; e++) {
```

<｜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
outed_mid_is_f16
        ? (void *)c->routed_mid_f16_buf
        : (void *)c->routed_mid_buf;
    if (ds4_gpu_tensor_read(g->batch_ffn_norm, 0, c->ffn_norm_buf, norm_bytes) == 0 ||
        ds4_gpu_tensor_read(g->batch_routed_mid, 0, mid_dst, mid_bytes) == 0 ||
        ds4_gpu_tensor_read(g->batch_router_selected, 0, c->selected_buf, sel_bytes) == 0)
    {
        return false;
    }

    for (uint32_t t = 0; t < n_tokens; t++) {
        const float *x = c->ffn_norm_buf + (size_t)t * DS4_N_EMBD;
        for (uint32_t i = 0; i < DS4_N_EMBD; i++) c->sq_tmp[i] = x[i] * x[i];

        for (uint32_t slot = 0; slot < DS4_N_EXPERT_USED; slot++) {
            const int expert = c->selected_buf[(size_t)t * DS4_N_EXPERT_USED + slot];
            if (expert < 0 || expert >= DS4_N_EXPERT) continue;

            float *gate_up = imatrix_gate_up_ptr(c, il, (uint32_t)expert);
            for (uint32_t i = 0; i < DS4_N_EMBD; i++) gate_up[i] += c->sq_tmp[i];
            c->gate_up_count[il][expert]++;

            float *down = imatrix_down_ptr(c, il, (uint32_t)expert);
            const size_t mid_off = ((size_t)t * DS4_N_EXPERT_USED + slot) * DS4_N_FF_EXP;
            if (g->batch_routed_mid_is_f16) {
                const uint16_t *mid = c->routed_mid_f16_buf + mid_off;
                for (uint32_t i = 0; i < DS4_N_FF_EXP; i++) {
                    const float v = f16_to_f32(mid[i]);
                    down[i] += v * v;
                }
            } else {
                const float *mid = c->routed_mid_buf + mid_off;
                for (uint32_t i = 0; i < DS4_N_FF_EXP; i++) down[i] += mid[i] * mid[i];
            }
            c->down_count[il][expert]++;
            c->observed_routes++;
        }
    }
    c->observed_tokens += n_tokens;
    c->chunks++;
    return true;
}

static void imatrix_write_i32(FILE *fp, int32_t v) {
    if (fwrite(&v, sizeof(v), 1, fp) != 1) ds4_die("failed to write imatrix");
}

static void imatrix_write_entry(
        FILE       *fp,
        const char *name,
        const float *sum2,
        const uint32_t *counts,
        uint32_t n_expert,
        uint32_t n_col) {
    const int32_t len = (int32_t)strlen(name);
    const int32_t ncall = 1;
    const int32_t nval = (int32_t)((uint64_t)n_expert * n_col);
    imatrix_write_i32(fp, len);
    if (fwrite(name, 1, (size_t)len, fp) != (size_t)len) ds4_die("failed to write imatrix name");
    imatrix_write_i32(fp, ncall);
    imatrix_write_i32(fp, nval);

    float *tmp = xmalloc((size_t)n_col * sizeof(tmp[0]));
    for (uint32_t e = 0; e < n_expert; e++) {
```<｜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
name");
    imatrix_write_i32(fp, ncall);
    imatrix_write_i32(fp, nval);

    float *tmp = xmalloc((size_t)n_col * sizeof(tmp[0]));
    for (uint32_t e = 0; e < n_expert; e++) {
        const uint32_t count = counts[e];
        const float *src = sum2 + (size_t)e * n_col;
        if (count == 0) {
            for (uint32_t i = 0; i < n_col; i++) tmp[i] = 1.0f;
        } else {
            const float inv = 1.0f / (float)count;
            for (uint32_t i = 0; i < n_col; i++) tmp[i] = src[i] * inv;
        }
        if (fwrite(tmp, sizeof(tmp[0]), n_col, fp) != n_col) ds4_die("failed to write imatrix values");
    }
    free(tmp);
}

static bool imatrix_collector_save(
        const ds4_imatrix_collector *c,
        const ds4_weights           *weights,
        const char                  *path) {
    FILE *fp = fopen(path, "wb");
    if (!fp) {
        fprintf(stderr, "ds4: failed to open imatrix output %s: %s\n", path, strerror(errno));
        return false;
    }

    const int32_t entries = (int32_t)(DS4_N_LAYER * 3);
    imatrix_write_i32(fp, entries);
    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        const ds4_layer_weights *layer = &weights->layer[il];
        char name[256];
        snprintf(name, sizeof(name), "%.*s", (int)layer->ffn_gate_exps->name.len, layer->ffn_gate_exps->name.ptr);
        imatrix_write_entry(fp, name,
                            c->gate_up_sum2 + (size_t)il * DS4_N_EXPERT * DS4_N_EMBD,
                            c->gate_up_count[il],
                            DS4_N_EXPERT,
                            DS4_N_EMBD);
        snprintf(name, sizeof(name), "%.*s", (int)layer->ffn_up_exps->name.len, layer->ffn_up_exps->name.ptr);
        imatrix_write_entry(fp, name,
                            c->gate_up_sum2 + (size_t)il * DS4_N_EXPERT * DS4_N_EMBD,
                            c->gate_up_count[il],
                            DS4_N_EXPERT,
                            DS4_N_EMBD);
        snprintf(name, sizeof(name), "%.*s", (int)layer->ffn_down_exps->name.len, layer->ffn_down_exps->name.ptr);
        imatrix_write_entry(fp, name,
                            c->down_sum2 + (size_t)il * DS4_N_EXPERT * DS4_N_FF_EXP,
                            c->down_count[il],
                            DS4_N_EXPERT,
                            DS4_N_FF_EXP);
    }

    const int32_t chunks = (int32_t)c->chunks;
    imatrix_write_i32(fp, chunks);
    const char *dataset = c->dataset_path ? c->dataset_path : "";
    const int32_t dataset_len = (int32_t)strlen(dataset);
    imatrix_write_i32(fp, dataset_len);
```

<｜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
name");
    imatrix_write_i32(fp, ncall);
    imatrix_write_i32(fp, nval);

    float *tmp = xmalloc((size_t)n_col * sizeof(tmp[0]));
    for (uint32_t e = 0; e < n_expert; e++) {
        const uint32_t count = counts[e];
        const float *src = sum2 + (size_t)e * n_col;
        if (count == 0) {
            for (uint32_t i = 0; i < n_col; i++) tmp[i] = 1.0f;
        } else {
            const float inv = 1.0f / (float)count;
            for (uint32_t i = 0; i < n_col; i++) tmp[i] = src[i] * inv;
        }
        if (fwrite(tmp, sizeof(tmp[0]), n_col, fp) != n_col) ds4_die("failed to write imatrix values");
    }
    free(tmp);
}

static bool imatrix_collector_save(
        const ds4_imatrix_collector *c,
        const ds4_weights           *weights,
        const char                  *path) {
    FILE *fp = fopen(path, "wb");
    if (!fp) {
        fprintf(stderr, "ds4: failed to open imatrix output %s: %s\n", path, strerror(errno));
        return false;
    }

    const int32_t entries = (int32_t)(DS4_N_LAYER * 3);
    imatrix_write_i32(fp, entries);
    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        const ds4_layer_weights *layer = &weights->layer[il];
        char name[256];
        snprintf(name, sizeof(name), "%.*s", (int)layer->ffn_gate_exps->name.len, layer->ffn_gate_exps->name.ptr);
        imatrix_write_entry(fp, name,
                            c->gate_up_sum2 + (size_t)il * DS4_N_EXPERT * DS4_N_EMBD,
                            c->gate_up_count[il],
                            DS4_N_EXPERT,
                            DS4_N_EMBD);
        snprintf(name, sizeof(name), "%.*s", (int)layer->ffn_up_exps->name.len, layer->ffn_up_exps->name.ptr);
        imatrix_write_entry(fp, name,
                            c->gate_up_sum2 + (size_t)il * DS4_N_EXPERT * DS4_N_EMBD,
                            c->gate_up_count[il],
                            DS4_N_EXPERT,
                            DS4_N_EMBD);
        snprintf(name, sizeof(name), "%.*s", (int)layer->ffn_down_exps->name.len, layer->ffn_down_exps->name.ptr);
        imatrix_write_entry(fp, name,
                            c->down_sum2 + (size_t)il * DS4_N_EXPERT * DS4_N_FF_EXP,
                            c->down_count[il],
                            DS4_N_EXPERT,
                            DS4_N_FF_EXP);
    }

    const int32_t chunks = (int32_t)c->chunks;
    imatrix_write_i32(fp, chunks);
    const char *dataset = c->dataset_path ? c->dataset_path : "";
    const int32_t dataset_len = (int32_t)strlen(dataset);
    imatrix_write_i32(fp, dataset_len);
```<｜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
name");
    imatrix_write_i32(fp, ncall);
    imatrix_write_i32(fp, nval);

    float *tmp = xmalloc((size_t)n_col * sizeof(tmp[0]));
    for (uint32_t e = 0; e < n_expert; e++) {
        const uint32_t count = counts[e];
        const float *src = sum2 + (size_t)e * n_col;
        if (count == 0) {
            for (uint32_t i = 0; i < n_col; i++) tmp[i] = 1.0f;
        } else {
            const float inv = 1.0f / (float)count;
            for (uint32_t i = 0; i < n_col; i++) tmp[i] = src[i] * inv;
        }
        if (fwrite(tmp, sizeof(tmp[0]), n_col, fp) != n_col) ds4_die("failed to write imatrix values");
    }
    free(tmp);
}

static bool imatrix_collector_save(
        const ds4_imatrix_collector *c,
        const ds4_weights           *weights,
        const char                  *path) {
    FILE *fp = fopen(path, "wb");
    if (!fp) {
        fprintf(stderr, "ds4: failed to open imatrix output %s: %s\n", path, strerror(errno));
        return false;
    }

    const int32_t entries = (int32_t)(DS4_N_LAYER * 3);
    imatrix_write_i32(fp, entries);
    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        const ds4_layer_weights *layer = &weights->layer[il];
        char name[256];
        snprintf(name, sizeof(name), "%.*s", (int)layer->ffn_gate_exps->name.len, layer->ffn_gate_exps->name.ptr);
        imatrix_write_entry(fp, name,
                            c->gate_up_sum2 + (size_t)il * DS4_N_EXPERT * DS4_N_EMBD,
                            c->gate_up_count[il],
                            DS4_N_EXPERT,
                            DS4_N_EMBD);
        snprintf(name, sizeof(name), "%.*s", (int)layer->ffn_up_exps->name.len, layer->ffn_up_exps->name.ptr);
        imatrix_write_entry(fp, name,
                            c->gate_up_sum2 + (size_t)il * DS4_N_EXPERT * DS4_N_EMBD,
                            c->gate_up_count[il],
                            DS4_N_EXPERT,
                            DS4_N_EMBD);
        snprintf(name, sizeof(name), "%.*s", (int)layer->ffn_down_exps->name.len, layer->ffn_down_exps->name.ptr);
        imatrix_write_entry(fp, name,
                            c->down_sum2 + (size_t)il * DS4_N_EXPERT * DS4_N_FF_EXP,
                            c->down_count[il],
                            DS4_N_EXPERT,
                            DS4_N_FF_EXP);
    }

    const int32_t chunks = (int32_t)c->chunks;
    imatrix_write_i32(fp, chunks);
    const char *dataset = c->dataset_path ? c->dataset_path : "";
    const int32_t dataset_len = (int32_t)strlen(dataset);
    imatrix_write_i32(fp, dataset_len);
```

<｜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
name");
    imatrix_write_i32(fp, ncall);
    imatrix_write_i32(fp, nval);

    float *tmp = xmalloc((size_t)n_col * sizeof(tmp[0]));
    for (uint32_t e = 0; e < n_expert; e++) {
        const uint32_t count = counts[e];
        const float *src = sum2 + (size_t)e * n_col;
        if (count == 0) {
            for (uint32_t i = 0; i < n_col; i++) tmp[i] = 1.0f;
        } else {
            const float inv = 1.0f / (float)count;
            for (uint32_t i = 0; i < n_col; i++) tmp[i] = src[i] * inv;
        }
        if (fwrite(tmp, sizeof(tmp[0]), n_col, fp) != n_col) ds4_die("failed to write imatrix values");
    }
    free(tmp);
}

static bool imatrix_collector_save(
        const ds4_imatrix_collector *c,
        const ds4_weights           *weights,
        const char                  *path) {
    FILE *fp = fopen(path, "wb");
    if (!fp) {
        fprintf(stderr, "ds4: failed to open imatrix output %s: %s\n", path, strerror(errno));
        return false;
    }

    const int32_t entries = (int32_t)(DS4_N_LAYER * 3);
    imatrix_write_i32(fp, entries);
    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        const ds4_layer_weights *layer = &weights->layer[il];
        char name[256];
        snprintf(name, sizeof(name), "%.*s", (int)layer->ffn_gate_exps->name.len, layer->ffn_gate_exps->name.ptr);
        imatrix_write_entry(fp, name,
                            c->gate_up_sum2 + (size_t)il * DS4_N_EXPERT * DS4_N_EMBD,
                            c->gate_up_count[il],
                            DS4_N_EXPERT,
                            DS4_N_EMBD);
        snprintf(name, sizeof(name), "%.*s", (int)layer->ffn_up_exps->name.len, layer->ffn_up_exps->name.ptr);
        imatrix_write_entry(fp, name,
                            c->gate_up_sum2 + (size_t)il * DS4_N_EXPERT * DS4_N_EMBD,
                            c->gate_up_count[il],
                            DS4_N_EXPERT,
                            DS4_N_EMBD);
        snprintf(name, sizeof(name), "%.*s", (int)layer->ffn_down_exps->name.len, layer->ffn_down_exps->name.ptr);
        imatrix_write_entry(fp, name,
                            c->down_sum2 + (size_t)il * DS4_N_EXPERT * DS4_N_FF_EXP,
                            c->down_count[il],
                            DS4_N_EXPERT,
                            DS4_N_FF_EXP);
    }

    const int32_t chunks = (int32_t)c->chunks;
    imatrix_write_i32(fp, chunks);
    const char *dataset = c->dataset_path ? c->dataset_path : "";
    const int32_t dataset_len = (int32_t)strlen(dataset);
    imatrix_write_i32(fp, dataset_len);
```<｜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
i32(fp, chunks);
    const char *dataset = c->dataset_path ? c->dataset_path : "";
    const int32_t dataset_len = (int32_t)strlen(dataset);
    imatrix_write_i32(fp, dataset_len);
    if (dataset_len && fwrite(dataset, 1, (size_t)dataset_len, fp) != (size_t)dataset_len) {
        ds4_die("failed to write imatrix dataset name");
    }

    if (fclose(fp) != 0) {
        fprintf(stderr, "ds4: failed to close imatrix output %s: %s\n", path, strerror(errno));
        return false;
    }
    return true;
}

static bool metal_graph_reset_prefill_state(ds4_gpu_graph *g) {
    memset(g->layer_n_index_comp, 0, sizeof(g->layer_n_index_comp));
    g->mtp_n_raw = 0;
    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        const uint32_t ratio = ds4_layer_compress_ratio(il);
        if (ratio == 0) continue;
        const uint32_t coff = ratio == 4 ? 2u : 1u;
        const uint64_t attn_width = (uint64_t)coff * DS4_N_HEAD_DIM;
        const uint64_t attn_rows = (uint64_t)coff * ratio;
        if (!metal_tensor_fill_f32(g->layer_attn_state_kv[il], 0.0f, attn_width * attn_rows)) return false;
        if (!metal_tensor_fill_f32(g->layer_attn_state_score[il], DS4_NEG_INF, attn_width * attn_rows)) return false;
        if (ratio == 4) {
            const uint64_t index_width = (uint64_t)coff * DS4_N_INDEXER_HEAD_DIM;
            const uint64_t index_rows = (uint64_t)coff * ratio;
            if (!metal_tensor_fill_f32(g->layer_index_state_kv[il], 0.0f, index_width * index_rows)) return false;
            if (!metal_tensor_fill_f32(g->layer_index_state_score[il], DS4_NEG_INF, index_width * index_rows)) return false;
        }
    }
    return true;
}

/* Execute Metal prefill in layer-major order so intermediate activations stay
 * on the GPU and cache state is built exactly once. */
static bool metal_graph_prefill_layer_major(
        ds4_gpu_graph *g,
        const ds4_model       *model,
        const ds4_weights     *weights,
        const token_vec       *prompt,
        int                    n_tokens,
        float                 *logits,
        bool                   show_progress,
        ds4_imatrix_collector *imatrix) {
    if (n_tokens <= 0 || n_tokens > prompt->len || (uint32_t)n_tokens > g->prefill_cap) return false;

    bool ok = metal_graph_upload_prompt_tokens(g->prefill_tokens, prompt, 0, (uint32_t)n_tokens);
    if (!ok) return false;

    if (!metal_graph_warmup_prefill_kernels(g, model, weights, (uint32_t)n_tokens)) return false;

    const bool split_profile = getenv("DS4_METAL_GRAPH_PREFILL_SPLIT_PROFILE") != NULL;
    /*
```

<｜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
i32(fp, chunks);
    const char *dataset = c->dataset_path ? c->dataset_path : "";
    const int32_t dataset_len = (int32_t)strlen(dataset);
    imatrix_write_i32(fp, dataset_len);
    if (dataset_len && fwrite(dataset, 1, (size_t)dataset_len, fp) != (size_t)dataset_len) {
        ds4_die("failed to write imatrix dataset name");
    }

    if (fclose(fp) != 0) {
        fprintf(stderr, "ds4: failed to close imatrix output %s: %s\n", path, strerror(errno));
        return false;
    }
    return true;
}

static bool metal_graph_reset_prefill_state(ds4_gpu_graph *g) {
    memset(g->layer_n_index_comp, 0, sizeof(g->layer_n_index_comp));
    g->mtp_n_raw = 0;
    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        const uint32_t ratio = ds4_layer_compress_ratio(il);
        if (ratio == 0) continue;
        const uint32_t coff = ratio == 4 ? 2u : 1u;
        const uint64_t attn_width = (uint64_t)coff * DS4_N_HEAD_DIM;
        const uint64_t attn_rows = (uint64_t)coff * ratio;
        if (!metal_tensor_fill_f32(g->layer_attn_state_kv[il], 0.0f, attn_width * attn_rows)) return false;
        if (!metal_tensor_fill_f32(g->layer_attn_state_score[il], DS4_NEG_INF, attn_width * attn_rows)) return false;
        if (ratio == 4) {
            const uint64_t index_width = (uint64_t)coff * DS4_N_INDEXER_HEAD_DIM;
            const uint64_t index_rows = (uint64_t)coff * ratio;
            if (!metal_tensor_fill_f32(g->layer_index_state_kv[il], 0.0f, index_width * index_rows)) return false;
            if (!metal_tensor_fill_f32(g->layer_index_state_score[il], DS4_NEG_INF, index_width * index_rows)) return false;
        }
    }
    return true;
}

/* Execute Metal prefill in layer-major order so intermediate activations stay
 * on the GPU and cache state is built exactly once. */
static bool metal_graph_prefill_layer_major(
        ds4_gpu_graph *g,
        const ds4_model       *model,
        const ds4_weights     *weights,
        const token_vec       *prompt,
        int                    n_tokens,
        float                 *logits,
        bool                   show_progress,
        ds4_imatrix_collector *imatrix) {
    if (n_tokens <= 0 || n_tokens > prompt->len || (uint32_t)n_tokens > g->prefill_cap) return false;

    bool ok = metal_graph_upload_prompt_tokens(g->prefill_tokens, prompt, 0, (uint32_t)n_tokens);
    if (!ok) return false;

    if (!metal_graph_warmup_prefill_kernels(g, model, weights, (uint32_t)n_tokens)) return false;

    const bool split_profile = getenv("DS4_METAL_GRAPH_PREFILL_SPLIT_PROFILE") != NULL;
    /*
```<｜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
i32(fp, chunks);
    const char *dataset = c->dataset_path ? c->dataset_path : "";
    const int32_t dataset_len = (int32_t)strlen(dataset);
    imatrix_write_i32(fp, dataset_len);
    if (dataset_len && fwrite(dataset, 1, (size_t)dataset_len, fp) != (size_t)dataset_len) {
        ds4_die("failed to write imatrix dataset name");
    }

    if (fclose(fp) != 0) {
        fprintf(stderr, "ds4: failed to close imatrix output %s: %s\n", path, strerror(errno));
        return false;
    }
    return true;
}

static bool metal_graph_reset_prefill_state(ds4_gpu_graph *g) {
    memset(g->layer_n_index_comp, 0, sizeof(g->layer_n_index_comp));
    g->mtp_n_raw = 0;
    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        const uint32_t ratio = ds4_layer_compress_ratio(il);
        if (ratio == 0) continue;
        const uint32_t coff = ratio == 4 ? 2u : 1u;
        const uint64_t attn_width = (uint64_t)coff * DS4_N_HEAD_DIM;
        const uint64_t attn_rows = (uint64_t)coff * ratio;
        if (!metal_tensor_fill_f32(g->layer_attn_state_kv[il], 0.0f, attn_width * attn_rows)) return false;
        if (!metal_tensor_fill_f32(g->layer_attn_state_score[il], DS4_NEG_INF, attn_width * attn_rows)) return false;
        if (ratio == 4) {
            const uint64_t index_width = (uint64_t)coff * DS4_N_INDEXER_HEAD_DIM;
            const uint64_t index_rows = (uint64_t)coff * ratio;
            if (!metal_tensor_fill_f32(g->layer_index_state_kv[il], 0.0f, index_width * index_rows)) return false;
            if (!metal_tensor_fill_f32(g->layer_index_state_score[il], DS4_NEG_INF, index_width * index_rows)) return false;
        }
    }
    return true;
}

/* Execute Metal prefill in layer-major order so intermediate activations stay
 * on the GPU and cache state is built exactly once. */
static bool metal_graph_prefill_layer_major(
        ds4_gpu_graph *g,
        const ds4_model       *model,
        const ds4_weights     *weights,
        const token_vec       *prompt,
        int                    n_tokens,
        float                 *logits,
        bool                   show_progress,
        ds4_imatrix_collector *imatrix) {
    if (n_tokens <= 0 || n_tokens > prompt->len || (uint32_t)n_tokens > g->prefill_cap) return false;

    bool ok = metal_graph_upload_prompt_tokens(g->prefill_tokens, prompt, 0, (uint32_t)n_tokens);
    if (!ok) return false;

    if (!metal_graph_warmup_prefill_kernels(g, model, weights, (uint32_t)n_tokens)) return false;

    const bool split_profile = getenv("DS4_METAL_GRAPH_PREFILL_SPLIT_PROFILE") != NULL;
    /*
```

<｜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
i32(fp, chunks);
    const char *dataset = c->dataset_path ? c->dataset_path : "";
    const int32_t dataset_len = (int32_t)strlen(dataset);
    imatrix_write_i32(fp, dataset_len);
    if (dataset_len && fwrite(dataset, 1, (size_t)dataset_len, fp) != (size_t)dataset_len) {
        ds4_die("failed to write imatrix dataset name");
    }

    if (fclose(fp) != 0) {
        fprintf(stderr, "ds4: failed to close imatrix output %s: %s\n", path, strerror(errno));
        return false;
    }
    return true;
}

static bool metal_graph_reset_prefill_state(ds4_gpu_graph *g) {
    memset(g->layer_n_index_comp, 0, sizeof(g->layer_n_index_comp));
    g->mtp_n_raw = 0;
    for (uint32_t il = 0; il < DS4_N_LAYER; il++) {
        const uint32_t ratio = ds4_layer_compress_ratio(il);
        if (ratio == 0) continue;
        const uint32_t coff = ratio == 4 ? 2u : 1u;
        const uint64_t attn_width = (uint64_t)coff * DS4_N_HEAD_DIM;
        const uint64_t attn_rows = (uint64_t)coff * ratio;
        if (!metal_tensor_fill_f32(g->layer_attn_state_kv[il], 0.0f, attn_width * attn_rows)) return false;
        if (!metal_tensor_fill_f32(g->layer_attn_state_score[il], DS4_NEG_INF, attn_width * attn_rows)) return false;
        if (ratio == 4) {
            const uint64_t index_width = (uint64_t)coff * DS4_N_INDEXER_HEAD_DIM;
            const uint64_t index_rows = (uint64_t)coff * ratio;
            if (!metal_tensor_fill_f32(g->layer_index_state_kv[il], 0.0f, index_width * index_rows)) return false;
            if (!metal_tensor_fill_f32(g->layer_index_state_score[il], DS4_NEG_INF, index_width * index_rows)) return false;
        }
    }
    return true;
}

/* Execute Metal prefill in layer-major order so intermediate activations stay
 * on the GPU and cache state is built exactly once. */
static bool metal_graph_prefill_layer_major(
        ds4_gpu_graph *g,
        const ds4_model       *model,
        const ds4_weights     *weights,
        const token_vec       *prompt,
        int                    n_tokens,
        float                 *logits,
        bool                   show_progress,
        ds4_imatrix_collector *imatrix) {
    if (n_tokens <= 0 || n_tokens > prompt->len || (uint32_t)n_tokens > g->prefill_cap) return false;

    bool ok = metal_graph_upload_prompt_tokens(g->prefill_tokens, prompt, 0, (uint32_t)n_tokens);
    if (!ok) return false;

    if (!metal_graph_warmup_prefill_kernels(g, model, weights, (uint32_t)n_tokens)) return false;

    const bool split_profile = getenv("DS4_METAL_GRAPH_PREFILL_SPLIT_PROFILE") != NULL;
    /*
```<｜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
l_graph_warmup_prefill_kernels(g, model, weights, (uint32_t)n_tokens)) return false;

    const bool split_profile = getenv("DS4_METAL_GRAPH_PREFILL_SPLIT_PROFILE") != NULL;
    /*
     * A full long-prompt prefill can keep the GPU busy long enough for macOS
     * to watchdog WindowServer. Keep short prompts in one command buffer for
     * low overhead, but submit long prompts layer by layer so the display
     * server gets regular scheduling points.
     */
    const bool split_commands = split_profile || n_tokens > 2048 || imatrix != NULL;
    const bool profile = getenv("DS4_METAL_GRAPH_PREFILL_PROFILE") != NULL || split_profile;
    const double t0 = profile ? now_sec() : 0.0;
    double encode_s = 0.0;
    double execute_s = 0.0;

    if (!split_commands) {
        ok = metal_graph_upload_prompt_embeddings_hc(g->batch_cur_hc,
                                                     g->prefill_tokens,
                                                     model,
                                                     weights,
                                                     prompt,
                                                     0,
                                                     (uint32_t)n_tokens);
        if (ok) ok = ds4_gpu_begin_commands() != 0;
        for (uint32_t il = 0; ok && il < DS4_N_LAYER; il++) {
            ok = metal_graph_encode_layer_batch(g,
                                                model,
                                                &weights->layer[il],
                                                il,
                                                0,
                                                (uint32_t)n_tokens);
            if (show_progress) {
                fprintf(stderr, "ds4: gpu prefill layer %u/%u\r", il + 1, (uint32_t)DS4_N_LAYER);
                fflush(stderr);
            }
        }
        if (show_progress) fputc('\n', stderr);

        const uint64_t hc_dim = (uint64_t)DS4_N_HC * DS4_N_EMBD;
        uint32_t output_row = (uint32_t)n_tokens - 1u;
        const char *output_row_env = getenv("DS4_METAL_GRAPH_OUTPUT_ROW");
        if (output_row_env && output_row_env[0]) {
            char *end = NULL;
            unsigned long v = strtoul(output_row_env, &end, 10);
            if (end != output_row_env && v < (unsigned long)n_tokens) {
                output_row = (uint32_t)v;
            }
        }
        ds4_gpu_tensor *last_hc = NULL;
        ds4_gpu_tensor *saved_cur = g->cur_hc;
        if (ok) {
            last_hc = metal_graph_tensor_row_view(g->batch_cur_hc, output_row, hc_dim);
```

<｜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
l_graph_warmup_prefill_kernels(g, model, weights, (uint32_t)n_tokens)) return false;

    const bool split_profile = getenv("DS4_METAL_GRAPH_PREFILL_SPLIT_PROFILE") != NULL;
    /*
     * A full long-prompt prefill can keep the GPU busy long enough for macOS
     * to watchdog WindowServer. Keep short prompts in one command buffer for
     * low overhead, but submit long prompts layer by layer so the display
     * server gets regular scheduling points.
     */
    const bool split_commands = split_profile || n_tokens > 2048 || imatrix != NULL;
    const bool profile = getenv("DS4_METAL_GRAPH_PREFILL_PROFILE") != NULL || split_profile;
    const double t0 = profile ? now_sec() : 0.0;
    double encode_s = 0.0;
    double execute_s = 0.0;

    if (!split_commands) {
        ok = metal_graph_upload_prompt_embeddings_hc(g->batch_cur_hc,
                                                     g->prefill_tokens,
                                                     model,
                                                     weights,
                                                     prompt,
                                                     0,
                                                     (uint32_t)n_tokens);
        if (ok) ok = ds4_gpu_begin_commands() != 0;
        for (uint32_t il = 0; ok && il < DS4_N_LAYER; il++) {
            ok = metal_graph_encode_layer_batch(g,
                                                model,
                                                &weights->layer[il],
                                                il,
                                                0,
                                                (uint32_t)n_tokens);
            if (show_progress) {
                fprintf(stderr, "ds4: gpu prefill layer %u/%u\r", il + 1, (uint32_t)DS4_N_LAYER);
                fflush(stderr);
            }
        }
        if (show_progress) fputc('\n', stderr);

        const uint64_t hc_dim = (uint64_t)DS4_N_HC * DS4_N_EMBD;
        uint32_t output_row = (uint32_t)n_tokens - 1u;
        const char *output_row_env = getenv("DS4_METAL_GRAPH_OUTPUT_ROW");
        if (output_row_env && output_row_env[0]) {
            char *end = NULL;
            unsigned long v = strtoul(output_row_env, &end, 10);
            if (end != output_row_env && v < (unsigned long)n_tokens) {
                output_row = (uint32_t)v;
            }
        }
        ds4_gpu_tensor *last_hc = NULL;
        ds4_gpu_tensor *saved_cur = g->cur_hc;
        if (ok) {
            last_hc = metal_graph_tensor_row_view(g->batch_cur_hc, output_row, hc_dim);
```<｜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
l_graph_warmup_prefill_kernels(g, model, weights, (uint32_t)n_tokens)) return false;

    const bool split_profile = getenv("DS4_METAL_GRAPH_PREFILL_SPLIT_PROFILE") != NULL;
    /*
     * A full long-prompt prefill can keep the GPU busy long enough for macOS
     * to watchdog WindowServer. Keep short prompts in one command buffer for
     * low overhead, but submit long prompts layer by layer so the display
     * server gets regular scheduling points.
     */
    const bool split_commands = split_profile || n_tokens > 2048 || imatrix != NULL;
    const bool profile = getenv("DS4_METAL_GRAPH_PREFILL_PROFILE") != NULL || split_profile;
    const double t0 = profile ? now_sec() : 0.0;
    double encode_s = 0.0;
    double execute_s = 0.0;

    if (!split_commands) {
        ok = metal_graph_upload_prompt_embeddings_hc(g->batch_cur_hc,
                                                     g->prefill_tokens,
                                                     model,
                                                     weights,
                                                     prompt,
                                                     0,
                                                     (uint32_t)n_tokens);
        if (ok) ok = ds4_gpu_begin_commands() != 0;
        for (uint32_t il = 0; ok && il < DS4_N_LAYER; il++) {
            ok = metal_graph_encode_layer_batch(g,
                                                model,
                                                &weights->layer[il],
                                                il,
                                                0,
                                                (uint32_t)n_tokens);
            if (show_progress) {
                fprintf(stderr, "ds4: gpu prefill layer %u/%u\r", il + 1, (uint32_t)DS4_N_LAYER);
                fflush(stderr);
            }
        }
        if (show_progress) fputc('\n', stderr);

        const uint64_t hc_dim = (uint64_t)DS4_N_HC * DS4_N_EMBD;
        uint32_t output_row = (uint32_t)n_tokens - 1u;
        const char *output_row_env = getenv("DS4_METAL_GRAPH_OUTPUT_ROW");
        if (output_row_env && output_row_env[0]) {
            char *end = NULL;
            unsigned long v = strtoul(output_row_env, &end, 10);
            if (end != output_row_env && v < (unsigned long)n_tokens) {
                output_row = (uint32_t)v;
            }
        }
        ds4_gpu_tensor *last_hc = NULL;
        ds4_gpu_tensor *saved_cur = g->cur_hc;
        if (ok) {
            last_hc = metal_graph_tensor_row_view(g->batch_cur_hc, output_row, hc_dim);
```

<｜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
l_graph_warmup_prefill_kernels(g, model, weights, (uint32_t)n_tokens)) return false;

    const bool split_profile = getenv("DS4_METAL_GRAPH_PREFILL_SPLIT_PROFILE") != NULL;
    /*
     * A full long-prompt prefill can keep the GPU busy long enough for macOS
     * to watchdog WindowServer. Keep short prompts in one command buffer for
     * low overhead, but submit long prompts layer by layer so the display
     * server gets regular scheduling points.
     */
    const bool split_commands = split_profile || n_tokens > 2048 || imatrix != NULL;
    const bool profile = getenv("DS4_METAL_GRAPH_PREFILL_PROFILE") != NULL || split_profile;
    const double t0 = profile ? now_sec() : 0.0;
    double encode_s = 0.0;
    double execute_s = 0.0;

    if (!split_commands) {
        ok = metal_graph_upload_prompt_embeddings_hc(g->batch_cur_hc,
                                                     g->prefill_tokens,
                                                     model,
                                                     weights,
                                                     prompt,
                                                     0,
                                                     (uint32_t)n_tokens);
        if (ok) ok = ds4_gpu_begin_commands() != 0;
        for (uint32_t il = 0; ok && il < DS4_N_LAYER; il++) {
            ok = metal_graph_encode_layer_batch(g,
                                                model,
                                                &weights->layer[il],
                                                il,
                                                0,
                                                (uint32_t)n_tokens);
            if (show_progress) {
                fprintf(stderr, "ds4: gpu prefill layer %u/%u\r", il + 1, (uint32_t)DS4_N_LAYER);
                fflush(stderr);
            }
        }
        if (show_progress) fputc('\n', stderr);

        const uint64_t hc_dim = (uint64_t)DS4_N_HC * DS4_N_EMBD;
        uint32_t output_row = (uint32_t)n_tokens - 1u;
        const char *output_row_env = getenv("DS4_METAL_GRAPH_OUTPUT_ROW");
        if (output_row_env && output_row_env[0]) {
            char *end = NULL;
            unsigned long v = strtoul(output_row_env, &end, 10);
            if (end != output_row_env && v < (unsigned long)n_tokens) {
                output_row = (uint32_t)v;
            }
        }
        ds4_gpu_tensor *last_hc = NULL;
        ds4_gpu_tensor *saved_cur = g->cur_hc;
        if (ok) {
            last_hc = metal_graph_tensor_row_view(g->batch_cur_hc, output_row, hc_dim);
```<｜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
gpu_tensor *last_hc = NULL;
        ds4_gpu_tensor *saved_cur = g->cur_hc;
        if (ok) {
            last_hc = metal_graph_tensor_row_view(g->batch_cur_hc, output_row, hc_dim);
            ok = last_hc != NULL;
        }
        if (ok) {
            g->cur_hc = last_hc;
            ok = metal_graph_encode_output_head(g, model, weights, weights->output->dim[1]);
            g->cur_hc = saved_cur;
        }

        const double t_encoded = profile ? now_sec() : 0.0;
        if (ok) ok = ds4_gpu_end_commands() != 0;
        const double t_done = profile ? now_sec() : 0.0;
        g->cur_hc = saved_cur;
        if (last_hc) ds4_gpu_tensor_free(last_hc);
        if (!ok) {
            if (ds4_gpu_synchronize() == 0) {
                fprintf(stderr, "ds4: Metal synchronize after whole-prefill graph failure also failed\n");
            }
            return false;
        }

        const double t_before_read = profile ? now_sec() : 0.0;
        if (logits) {
            ok = ds4_gpu_tensor_read(g->logits, 0, logits, (uint64_t)DS4_N_VOCAB * sizeof(float)) != 0;
        }
        if (profile) {
            const double t_read = now_sec();
            fprintf(stderr,
                    "ds4: gpu graph prefill total tokens=%d encode=%.3f ms execute=%.3f ms read=%.3f ms total=%.3f ms\n",
                    n_tokens,
                    (t_encoded - t0) * 1000.0,
                    (t_done - t_encoded) * 1000.0,
                    (t_read - t_before_read) * 1000.0,
                    (t_read - t0) * 1000.0);
        }
        return ok;
    }

    double t_layer0 = profile ? now_sec() : 0.0;
    ok = metal_graph_upload_prompt_embeddings_hc(g->batch_cur_hc,
                                                 g->prefill_tokens,
                                                 model,
                                                 weights,
                                                 prompt,
                                                 0,
                                                 (uint32_t)n_tokens);
    const double t_embed_encoded = profile ? now_sec() : 0.0;
    const double t_embed_done = profile ? now_sec() : 0.0;
    if (profile) {
        encode_s += t_embed_encoded - t_layer0;
        execute_s += t_embed_done - t_embed_encoded;
        if (split_profile) {
            fprintf(stderr,
                    "ds4: metal layer-major prefill embed encode=%.3f ms execute=%.3f ms\n",
                    (t_embed_encoded - t_layer0) * 1000.0,
                    (t_embed_done - t_embed_encoded) * 1000.0);
        }
    }
    if (!ok) {
```

<｜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
gpu_tensor *last_hc = NULL;
        ds4_gpu_tensor *saved_cur = g->cur_hc;
        if (ok) {
            last_hc = metal_graph_tensor_row_view(g->batch_cur_hc, output_row, hc_dim);
            ok = last_hc != NULL;
        }
        if (ok) {
            g->cur_hc = last_hc;
            ok = metal_graph_encode_output_head(g, model, weights, weights->output->dim[1]);
            g->cur_hc = saved_cur;
        }

        const double t_encoded = profile ? now_sec() : 0.0;
        if (ok) ok = ds4_gpu_end_commands() != 0;
        const double t_done = profile ? now_sec() : 0.0;
        g->cur_hc = saved_cur;
        if (last_hc) ds4_gpu_tensor_free(last_hc);
        if (!ok) {
            if (ds4_gpu_synchronize() == 0) {
                fprintf(stderr, "ds4: Metal synchronize after whole-prefill graph failure also failed\n");
            }
            return false;
        }

        const double t_before_read = profile ? now_sec() : 0.0;
        if (logits) {
            ok = ds4_gpu_tensor_read(g->logits, 0, logits, (uint64_t)DS4_N_VOCAB * sizeof(float)) != 0;
        }
        if (profile) {
            const double t_read = now_sec();
            fprintf(stderr,
                    "ds4: gpu graph prefill total tokens=%d encode=%.3f ms execute=%.3f ms read=%.3f ms total=%.3f ms\n",
                    n_tokens,
                    (t_encoded - t0) * 1000.0,
                    (t_done - t_encoded) * 1000.0,
                    (t_read - t_before_read) * 1000.0,
                    (t_read - t0) * 1000.0);
        }
        return ok;
    }

    double t_layer0 = profile ? now_sec() : 0.0;
    ok = metal_graph_upload_prompt_embeddings_hc(g->batch_cur_hc,
                                                 g->prefill_tokens,
                                                 model,
                                                 weights,
                                                 prompt,
                                                 0,
                                                 (uint32_t)n_tokens);
    const double t_embed_encoded = profile ? now_sec() : 0.0;
    const double t_embed_done = profile ? now_sec() : 0.0;
    if (profile) {
        encode_s += t_embed_encoded - t_layer0;
        execute_s += t_embed_done - t_embed_encoded;
        if (split_profile) {
            fprintf(stderr,
                    "ds4: metal layer-major prefill embed encode=%.3f ms execute=%.3f ms\n",
                    (t_embed_encoded - t_layer0) * 1000.0,
                    (t_embed_done - t_embed_encoded) * 1000.0);
        }
    }
    if (!ok) {
```<｜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
gpu_tensor *last_hc = NULL;
        ds4_gpu_tensor *saved_cur = g->cur_hc;
        if (ok) {
            last_hc = metal_graph_tensor_row_view(g->batch_cur_hc, output_row, hc_dim);
            ok = last_hc != NULL;
        }
        if (ok) {
            g->cur_hc = last_hc;
            ok = metal_graph_encode_output_head(g, model, weights, weights->output->dim[1]);
            g->cur_hc = saved_cur;
        }

        const double t_encoded = profile ? now_sec() : 0.0;
        if (ok) ok = ds4_gpu_end_commands() != 0;
        const double t_done = profile ? now_sec() : 0.0;
        g->cur_hc = saved_cur;
        if (last_hc) ds4_gpu_tensor_free(last_hc);
        if (!ok) {
            if (ds4_gpu_synchronize() == 0) {
                fprintf(stderr, "ds4: Metal synchronize after whole-prefill graph failure also failed\n");
            }
            return false;
        }

        const double t_before_read = profile ? now_sec() : 0.0;
        if (logits) {
            ok = ds4_gpu_tensor_read(g->logits, 0, logits, (uint64_t)DS4_N_VOCAB * sizeof(float)) != 0;
        }
        if (profile) {
            const double t_read = now_sec();
            fprintf(stderr,
                    "ds4: gpu graph prefill total tokens=%d encode=%.3f ms execute=%.3f ms read=%.3f ms total=%.3f ms\n",
                    n_tokens,
                    (t_encoded - t0) * 1000.0,
                    (t_done - t_encoded) * 1000.0,
                    (t_read - t_before_read) * 1000.0,
                    (t_read - t0) * 1000.0);
        }
        return ok;
    }

    double t_layer0 = profile ? now_sec() : 0.0;
    ok = metal_graph_upload_prompt_embeddings_hc(g->batch_cur_hc,
                                                 g->prefill_tokens,
                                                 model,
                                                 weights,
                                                 prompt,
                                                 0,
                                                 (uint32_t)n_tokens);
    const double t_embed_encoded = profile ? now_sec() : 0.0;
    const double t_embed_done = profile ? now_sec() : 0.0;
    if (profile) {
        encode_s += t_embed_encoded - t_layer0;
        execute_s += t_embed_done - t_embed_encoded;
        if (split_profile) {
            fprintf(stderr,
                    "ds4: metal layer-major prefill embed encode=%.3f ms execute=%.3f ms\n",
                    (t_embed_encoded - t_layer0) * 1000.0,
                    (t_embed_done - t_embed_encoded) * 1000.0);
        }
    }
    if (!ok) {
```

<｜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
gpu_tensor *last_hc = NULL;
        ds4_gpu_tensor *saved_cur = g->cur_hc;
        if (ok) {
            last_hc = metal_graph_tensor_row_view(g->batch_cur_hc, output_row, hc_dim);
            ok = last_hc != NULL;
        }
        if (ok) {
            g->cur_hc = last_hc;
            ok = metal_graph_encode_output_head(g, model, weights, weights->output->dim[1]);
            g->cur_hc = saved_cur;
        }

        const double t_encoded = profile ? now_sec() : 0.0;
        if (ok) ok = ds4_gpu_end_commands() != 0;
        const double t_done = profile ? now_sec() : 0.0;
        g->cur_hc = saved_cur;
        if (last_hc) ds4_gpu_tensor_free(last_hc);
        if (!ok) {
            if (ds4_gpu_synchronize() == 0) {
                fprintf(stderr, "ds4: Metal synchronize after whole-prefill graph failure also failed\n");
            }
            return false;
        }

        const double t_before_read = profile ? now_sec() : 0.0;
        if (logits) {
            ok = ds4_gpu_tensor_read(g->logits, 0, logits, (uint64_t)DS4_N_VOCAB * sizeof(float)) != 0;
        }
        if (profile) {
            const double t_read = now_sec();
            fprintf(stderr,
                    "ds4: gpu graph prefill total tokens=%d encode=%.3f ms execute=%.3f ms read=%.3f ms total=%.3f ms\n",
                    n_tokens,
                    (t_encoded - t0) * 1000.0,
                    (t_done - t_encoded) * 1000.0,
                    (t_read - t_before_read) * 1000.0,
                    (t_read - t0) * 1000.0);
        }
        return ok;
    }

    double t_layer0 = profile ? now_sec() : 0.0;
    ok = metal_graph_upload_prompt_embeddings_hc(g->batch_cur_hc,
                                                 g->prefill_tokens,
                                                 model,
                                                 weights,
                                                 prompt,
                                                 0,
                                                 (uint32_t)n_tokens);
    const double t_embed_encoded = profile ? now_sec() : 0.0;
    const double t_embed_done = profile ? now_sec() : 0.0;
    if (profile) {
        encode_s += t_embed_encoded - t_layer0;
        execute_s += t_embed_done - t_embed_encoded;
        if (split_profile) {
            fprintf(stderr,
                    "ds4: metal layer-major prefill embed encode=%.3f ms execute=%.3f ms\n",
                    (t_embed_encoded - t_layer0) * 1000.0,
                    (t_embed_done - t_embed_encoded) * 1000.0);
        }
    }
    if (!ok) {
```<｜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
get_high_s16(q8sums.val[1])));
        sum += dmin * (float)vaddvq_s32(vaddq_s32(s0, s1));

        int isum = 0;
        int is = 0;
        for (int j = 0; j < QK_K / 128; j++) {
            const uint8x16x2_t q2bits = vld1q_u8_x2(q2);
            q2 += 32;

#define DS4_Q2_DOT_NOSHIFT(scale_index) do {                                           \
                const int8x16x2_t q8bytes = vld1q_s8_x2(q8);                           \
                q8 += 32;                                                              \
                const int8x16_t q2lo = vreinterpretq_s8_u8(vandq_u8(q2bits.val[0], m3));\
                const int8x16_t q2hi = vreinterpretq_s8_u8(vandq_u8(q2bits.val[1], m3));\
                isum += vaddvq_s32(vdotq_s32(zero, q2lo, q8bytes.val[0])) *            \
                        scale_lanes[is + (scale_index)];                               \
                isum += vaddvq_s32(vdotq_s32(zero, q2hi, q8bytes.val[1])) *            \
                        scale_lanes[is + 1 + (scale_index)];                           \
            } while (0)

#define DS4_Q2_DOT_SHIFT(shift, scale_index) do {                                      \
                const int8x16x2_t q8bytes = vld1q_s8_x2(q8);                           \
                q8 += 32;                                                              \
                const int8x16_t q2lo = vreinterpretq_s8_u8(                            \
                    vandq_u8(vshrq_n_u8(q2bits.val[0], (shift)), m3));                 \
                const int8x16_t q2hi = vreinterpretq_s8_u8(                            \
                    vandq_u8(vshrq_n_u8(q2bits.val[1], (shift)), m3));                 \
                isum += vaddvq_s32(vdotq_s32(zero, q2lo, q8bytes.val[0])) *            \
                        scale_lanes[is + (scale_index)];                               \
                isum += vaddvq_s32(vdotq_s32(zero, q2hi, q8bytes.val[1])) *            \
                        scale_lanes[is + 1 + (scale_index)];                           \
            } while (0)

            DS4_Q2_DOT_NOSHIFT(0);
            DS4_Q2_DOT_SHIFT(2, 2);
            DS4_Q2_DOT_SHIFT(4, 4);
            DS4_Q2_DOT_SHIFT(6, 6);
            is += 8;

#undef DS4_Q2_DOT_NOSHIFT
#undef DS4_Q2_DOT_SHIFT
        }

        sum += d * (float)isum;
    }

    *s = sum;
#else
    float sumf = 0.0f;

    for (int i = 0; i < nb; i++) {
        const uint8_t *q2 = x[i].qs;
        const int8_t *q8 = y[i].qs;
        const uint8_t *sc = x[i].scales;

        int summs = 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｜>Suggest a minimal correctness-preserving optimization for this excerpt.

File: ds4.c

```c
get_high_s16(q8sums.val[1])));
        sum += dmin * (float)vaddvq_s32(vaddq_s32(s0, s1));

        int isum = 0;
        int is = 0;
        for (int j = 0; j < QK_K / 128; j++) {
            const uint8x16x2_t q2bits = vld1q_u8_x2(q2);
            q2 += 32;

#define DS4_Q2_DOT_NOSHIFT(scale_index) do {                                           \
                const int8x16x2_t q8bytes = vld1q_s8_x2(q8);                           \
                q8 += 32;                                                              \
                const int8x16_t q2lo = vreinterpretq_s8_u8(vandq_u8(q2bits.val[0], m3));\
                const int8x16_t q2hi = vreinterpretq_s8_u8(vandq_u8(q2bits.val[1], m3));\
                isum += vaddvq_s32(vdotq_s32(zero, q2lo, q8bytes.val[0])) *            \
                        scale_lanes[is + (scale_index)];                               \
                isum += vaddvq_s32(vdotq_s32(zero, q2hi, q8bytes.val[1])) *            \
                        scale_lanes[is + 1 + (scale_index)];                           \
            } while (0)

#define DS4_Q2_DOT_SHIFT(shift, scale_index) do {                                      \
                const int8x16x2_t q8bytes = vld1q_s8_x2(q8);                           \
                q8 += 32;                                                              \
                const int8x16_t q2lo = vreinterpretq_s8_u8(                            \
                    vandq_u8(vshrq_n_u8(q2bits.val[0], (shift)), m3));                 \
                const int8x16_t q2hi = vreinterpretq_s8_u8(                            \
                    vandq_u8(vshrq_n_u8(q2bits.val[1], (shift)), m3));                 \
                isum += vaddvq_s32(vdotq_s32(zero, q2lo, q8bytes.val[0])) *            \
                        scale_lanes[is + (scale_index)];                               \
                isum += vaddvq_s32(vdotq_s32(zero, q2hi, q8bytes.val[1])) *            \
                        scale_lanes[is + 1 + (scale_index)];                           \
            } while (0)

            DS4_Q2_DOT_NOSHIFT(0);
            DS4_Q2_DOT_SHIFT(2, 2);
            DS4_Q2_DOT_SHIFT(4, 4);
            DS4_Q2_DOT_SHIFT(6, 6);
            is += 8;

#undef DS4_Q2_DOT_NOSHIFT
#undef DS4_Q2_DOT_SHIFT
        }

        sum += d * (float)isum;
    }

    *s = sum;
#else
    float sumf = 0.0f;

    for (int i = 0; i < nb; i++) {
        const uint8_t *q2 = x[i].qs;
        const int8_t *q8 = y[i].qs;
        const uint8_t *sc = x[i].scales;

        int summs = 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]
Suggest a minimal correctness-preserving optimization for this excerpt.

File: ds4.c

```c
get_high_s16(q8sums.val[1])));
        sum += dmin * (float)vaddvq_s32(vaddq_s32(s0, s1));

        int isum = 0;
        int is = 0;
        for (int j = 0; j < QK_K / 128; j++) {
            const uint8x16x2_t q2bits = vld1q_u8_x2(q2);
            q2 += 32;

#define DS4_Q2_DOT_NOSHIFT(scale_index) do {                                           \
                const int8x16x2_t q8bytes = vld1q_s8_x2(q8);                           \
                q8 += 32;                                                              \
                const int8x16_t q2lo = vreinterpretq_s8_u8(vandq_u8(q2bits.val[0], m3));\
                const int8x16_t q2hi = vreinterpretq_s8_u8(vandq_u8(q2bits.val[1], m3));\
                isum += vaddvq_s32(vdotq_s32(zero, q2lo, q8bytes.val[0])) *            \
                        scale_lanes[is + (scale_index)];                               \
                isum += vaddvq_s32(vdotq_s32(zero, q2hi, q8bytes.val[1])) *            \
                        scale_lanes[is + 1 + (scale_index)];                           \
            } while (0)

#define DS4_Q2_DOT_SHIFT(shift, scale_index) do {                                      \
                const int8x16x2_t q8bytes = vld1q_s8_x2(q8);                           \
                q8 += 32;                                                              \
                const int8x16_t q2lo = vreinterpretq_s8_u8(                            \
                    vandq_u8(vshrq_n_u8(q2bits.val[0], (shift)), m3));                 \
                const int8x16_t q2hi = vreinterpretq_s8_u8(                            \
                    vandq_u8(vshrq_n_u8(q2bits.val[1], (shift)), m3));                 \
                isum += vaddvq_s32(vdotq_s32(zero, q2lo, q8bytes.val[0])) *            \
                        scale_lanes[is + (scale_index)];                               \
                isum += vaddvq_s32(vdotq_s32(zero, q2hi, q8bytes.val[1])) *            \
                        scale_lanes[is + 1 + (scale_index)];                           \
            } while (0)

            DS4_Q2_DOT_NOSHIFT(0);
            DS4_Q2_DOT_SHIFT(2, 2);
            DS4_Q2_DOT_SHIFT(4, 4);
            DS4_Q2_DOT_SHIFT(6, 6);
            is += 8;

#undef DS4_Q2_DOT_NOSHIFT
#undef DS4_Q2_DOT_SHIFT
        }

        sum += d * (float)isum;
    }

    *s = sum;
#else
    float sumf = 0.0f;

    for (int i = 0; i < nb; i++) {
        const uint8_t *q2 = x[i].qs;
        const int8_t *q8 = y[i].qs;
        const uint8_t *sc = x[i].scales;

        int summs = 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｜>Suggest a minimal correctness-preserving optimization for this excerpt.

File: ds4.c

```c
get_high_s16(q8sums.val[1])));
        sum += dmin * (float)vaddvq_s32(vaddq_s32(s0, s1));

        int isum = 0;
        int is = 0;
        for (int j = 0; j < QK_K / 128; j++) {
            const uint8x16x2_t q2bits = vld1q_u8_x2(q2);
            q2 += 32;

#define DS4_Q2_DOT_NOSHIFT(scale_index) do {                                           \
                const int8x16x2_t q8bytes = vld1q_s8_x2(q8);                           \
                q8 += 32;                                                              \
                const int8x16_t q2lo = vreinterpretq_s8_u8(vandq_u8(q2bits.val[0], m3));\
                const int8x16_t q2hi = vreinterpretq_s8_u8(vandq_u8(q2bits.val[1], m3));\
                isum += vaddvq_s32(vdotq_s32(zero, q2lo, q8bytes.val[0])) *            \
                        scale_lanes[is + (scale_index)];                               \
                isum += vaddvq_s32(vdotq_s32(zero, q2hi, q8bytes.val[1])) *            \
                        scale_lanes[is + 1 + (scale_index)];                           \
            } while (0)

#define DS4_Q2_DOT_SHIFT(shift, scale_index) do {                                      \
                const int8x16x2_t q8bytes = vld1q_s8_x2(q8);                           \
                q8 += 32;                                                              \
                const int8x16_t q2lo = vreinterpretq_s8_u8(                            \
                    vandq_u8(vshrq_n_u8(q2bits.val[0], (shift)), m3));                 \
                const int8x16_t q2hi = vreinterpretq_s8_u8(                            \
                    vandq_u8(vshrq_n_u8(q2bits.val[1], (shift)), m3));                 \
                isum += vaddvq_s32(vdotq_s32(zero, q2lo, q8bytes.val[0])) *            \
                        scale_lanes[is + (scale_index)];                               \
                isum += vaddvq_s32(vdotq_s32(zero, q2hi, q8bytes.val[1])) *            \
                        scale_lanes[is + 1 + (scale_index)];                           \
            } while (0)

            DS4_Q2_DOT_NOSHIFT(0);
            DS4_Q2_DOT_SHIFT(2, 2);
            DS4_Q2_DOT_SHIFT(4, 4);
            DS4_Q2_DOT_SHIFT(6, 6);
            is += 8;

#undef DS4_Q2_DOT_NOSHIFT
#undef DS4_Q2_DOT_SHIFT
        }

        sum += d * (float)isum;
    }

    *s = sum;
#else
    float sumf = 0.0f;

    for (int i = 0; i < nb; i++) {
        const uint8_t *q2 = x[i].qs;
        const int8_t *q8 = y[i].qs;
        const uint8_t *sc = x[i].scales;

        int summs = 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
.3f ms execute=%.3f ms\n",
                    (t_embed_encoded - t_layer0) * 1000.0,
                    (t_embed_done - t_embed_encoded) * 1000.0);
        }
    }
    if (!ok) {
        if (ds4_gpu_synchronize() == 0) {
            fprintf(stderr, "ds4: Metal synchronize after layer-major prefill embed failure also failed\n");
        }
        return false;
    }

    for (uint32_t il = 0; ok && il < DS4_N_LAYER; il++) {
        if (split_profile) {
            const double t_attn0 = now_sec();
            ok = ds4_gpu_begin_commands() != 0;
            if (ok) ok = metal_graph_encode_layer_attention_batch(g,
                                                                  model,
                                                                  &weights->layer[il],
                                                                  il,
                                                                  0,
                                                                  (uint32_t)n_tokens);
            const double t_attn_encoded = now_sec();
            if (ok) ok = ds4_gpu_end_commands() != 0;
            const double t_attn_done = now_sec();

            const double t_ffn0 = now_sec();
            if (ok) ok = ds4_gpu_begin_commands() != 0;
            if (ok) ok = metal_graph_encode_layer_ffn_batch(g,
                                                            model,
                                                            &weights->layer[il],
                                                            il,
                                                            0,
                                                            (uint32_t)n_tokens);
            if (ok) {
                ds4_gpu_tensor *tmp = g->batch_cur_hc;
                g->batch_cur_hc = g->batch_next_hc;
                g->batch_next_hc = tmp;
            }
            const double t_ffn_encoded = now_sec();
            if (ok) ok = ds4_gpu_end_commands() != 0;
            const double t_ffn_done = now_sec();
            if (ok && imatrix) ok = imatrix_collect_layer_batch(imatrix, g, il, (uint32_t)n_tokens);

            encode_s += (t_attn_encoded - t_attn0) + (t_ffn_encoded - t_ffn0);
            execute_s += (t_attn_done - t_attn_encoded) + (t_ffn_done - t_ffn_encoded);
            fprintf(stderr,
                    "ds4: metal layer-major prefill layer %u attn encode=%.3f execute=%.3f ms ffn encode=%.3f execute=%.3f ms\n",
                    il,
                    (t_attn_encoded - t_attn0) * 1000.0,
                    (t_attn_done - t_attn_encoded) * 1000.0,
```

<｜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
.3f ms execute=%.3f ms\n",
                    (t_embed_encoded - t_layer0) * 1000.0,
                    (t_embed_done - t_embed_encoded) * 1000.0);
        }
    }
    if (!ok) {
        if (ds4_gpu_synchronize() == 0) {
            fprintf(stderr, "ds4: Metal synchronize after layer-major prefill embed failure also failed\n");
        }
        return false;
    }

    for (uint32_t il = 0; ok && il < DS4_N_LAYER; il++) {
        if (split_profile) {
            const double t_attn0 = now_sec();
            ok = ds4_gpu_begin_commands() != 0;
            if (ok) ok = metal_graph_encode_layer_attention_batch(g,
                                                                  model,
                                                                  &weights->layer[il],
                                                                  il,
                                                                  0,
                                                                  (uint32_t)n_tokens);
            const double t_attn_encoded = now_sec();
            if (ok) ok = ds4_gpu_end_commands() != 0;
            const double t_attn_done = now_sec();

            const double t_ffn0 = now_sec();
            if (ok) ok = ds4_gpu_begin_commands() != 0;
            if (ok) ok = metal_graph_encode_layer_ffn_batch(g,
                                                            model,
                                                            &weights->layer[il],
                                                            il,
                                                            0,
                                                            (uint32_t)n_tokens);
            if (ok) {
                ds4_gpu_tensor *tmp = g->batch_cur_hc;
                g->batch_cur_hc = g->batch_next_hc;
                g->batch_next_hc = tmp;
            }
            const double t_ffn_encoded = now_sec();
            if (ok) ok = ds4_gpu_end_commands() != 0;
            const double t_ffn_done = now_sec();
            if (ok && imatrix) ok = imatrix_collect_layer_batch(imatrix, g, il, (uint32_t)n_tokens);

            encode_s += (t_attn_encoded - t_attn0) + (t_ffn_encoded - t_ffn0);
            execute_s += (t_attn_done - t_attn_encoded) + (t_ffn_done - t_ffn_encoded);
            fprintf(stderr,
                    "ds4: metal layer-major prefill layer %u attn encode=%.3f execute=%.3f ms ffn encode=%.3f execute=%.3f ms\n",
                    il,
                    (t_attn_encoded - t_attn0) * 1000.0,
                    (t_attn_done - t_attn_encoded) * 1000.0,
```<｜Assistant｜></think>