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

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

File: ds4.c

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

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

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

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

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

File: ds4.c

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

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

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

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


[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
b.weight", il);
        l->attn_kv         = required_tensorf(m, "blk.%u.attn_kv.weight", il);
        l->attn_kv_a_norm  = required_tensorf(m, "blk.%u.attn_kv_a_norm.weight", il);
        l->attn_sinks      = required_tensorf(m, "blk.%u.attn_sinks.weight", il);
        l->attn_output_a   = required_tensorf(m, "blk.%u.attn_output_a.weight", il);
        l->attn_output_b   = required_tensorf(m, "blk.%u.attn_output_b.weight", il);
        if (compress_ratio != 0) {
            l->attn_compressor_ape  = required_tensorf(m, "blk.%u.attn_compressor_ape.weight", il);
            l->attn_compressor_kv   = required_tensorf(m, "blk.%u.attn_compressor_kv.weight", il);
            l->attn_compressor_gate = required_tensorf(m, "blk.%u.attn_compressor_gate.weight", il);
            l->attn_compressor_norm = required_tensorf(m, "blk.%u.attn_compressor_norm.weight", il);
        }
        if (compress_ratio == 4) {
            l->indexer_attn_q_b = required_tensorf(m, "blk.%u.indexer.attn_q_b.weight", il);
            l->indexer_proj     = required_tensorf(m, "blk.%u.indexer.proj.weight", il);
            l->indexer_compressor_ape  = required_tensorf(m, "blk.%u.indexer_compressor_ape.weight", il);
            l->indexer_compressor_kv   = required_tensorf(m, "blk.%u.indexer_compressor_kv.weight", il);
            l->indexer_compressor_gate = required_tensorf(m, "blk.%u.indexer_compressor_gate.weight", il);
            l->indexer_compressor_norm = required_tensorf(m, "blk.%u.indexer_compressor_norm.weight", il);
        }
        l->hc_ffn_fn       = required_tensorf(m, "blk.%u.hc_ffn_fn.weight", il);
        l->hc_ffn_scale    = required_tensorf(m, "blk.%u.hc_ffn_scale.weight", il);
        l->hc_ffn_base     = required_tensorf(m, "blk.%u.hc_ffn_base.weight", il);
        l->ffn_norm        = required_tensorf(m, "blk.%u.ffn_norm.weight", il);
        l->ffn_gate_inp    = required_tensorf(m, "blk.%u.ffn_gate_inp.weight", il);
        l->ffn_exp_probs_b = tensor_by_namef(m, "blk.%u.exp_probs_b.bias", il);
        l->ffn_gate_exps   = required_tensorf(m, "blk.%u.ffn_gate_exps.weight", il);
        l->ffn_up_exps     = required_tensorf(m, "blk.%u.ffn_up_exps.weight", il);
        l->ffn_down_exps   = required_tensorf(m, "blk.%u.ffn_down_exps.weight", il);
        l->ffn_gate_shexp  = required_tensorf(m, "blk.%u.ffn_gate_shexp.weight", il);
        l->ffn_up_shexp    = required_tensorf(m, "blk.%u.ffn_up_shexp.weight", il);
        l->ffn_down_shexp  = required_tensorf(m, "blk.%u.ffn_down_shexp.weight", il);

        if (il < DS4_N_HASH_LAYER) {
```

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

File: ds4.c

```c
b.weight", il);
        l->attn_kv         = required_tensorf(m, "blk.%u.attn_kv.weight", il);
        l->attn_kv_a_norm  = required_tensorf(m, "blk.%u.attn_kv_a_norm.weight", il);
        l->attn_sinks      = required_tensorf(m, "blk.%u.attn_sinks.weight", il);
        l->attn_output_a   = required_tensorf(m, "blk.%u.attn_output_a.weight", il);
        l->attn_output_b   = required_tensorf(m, "blk.%u.attn_output_b.weight", il);
        if (compress_ratio != 0) {
            l->attn_compressor_ape  = required_tensorf(m, "blk.%u.attn_compressor_ape.weight", il);
            l->attn_compressor_kv   = required_tensorf(m, "blk.%u.attn_compressor_kv.weight", il);
            l->attn_compressor_gate = required_tensorf(m, "blk.%u.attn_compressor_gate.weight", il);
            l->attn_compressor_norm = required_tensorf(m, "blk.%u.attn_compressor_norm.weight", il);
        }
        if (compress_ratio == 4) {
            l->indexer_attn_q_b = required_tensorf(m, "blk.%u.indexer.attn_q_b.weight", il);
            l->indexer_proj     = required_tensorf(m, "blk.%u.indexer.proj.weight", il);
            l->indexer_compressor_ape  = required_tensorf(m, "blk.%u.indexer_compressor_ape.weight", il);
            l->indexer_compressor_kv   = required_tensorf(m, "blk.%u.indexer_compressor_kv.weight", il);
            l->indexer_compressor_gate = required_tensorf(m, "blk.%u.indexer_compressor_gate.weight", il);
            l->indexer_compressor_norm = required_tensorf(m, "blk.%u.indexer_compressor_norm.weight", il);
        }
        l->hc_ffn_fn       = required_tensorf(m, "blk.%u.hc_ffn_fn.weight", il);
        l->hc_ffn_scale    = required_tensorf(m, "blk.%u.hc_ffn_scale.weight", il);
        l->hc_ffn_base     = required_tensorf(m, "blk.%u.hc_ffn_base.weight", il);
        l->ffn_norm        = required_tensorf(m, "blk.%u.ffn_norm.weight", il);
        l->ffn_gate_inp    = required_tensorf(m, "blk.%u.ffn_gate_inp.weight", il);
        l->ffn_exp_probs_b = tensor_by_namef(m, "blk.%u.exp_probs_b.bias", il);
        l->ffn_gate_exps   = required_tensorf(m, "blk.%u.ffn_gate_exps.weight", il);
        l->ffn_up_exps     = required_tensorf(m, "blk.%u.ffn_up_exps.weight", il);
        l->ffn_down_exps   = required_tensorf(m, "blk.%u.ffn_down_exps.weight", il);
        l->ffn_gate_shexp  = required_tensorf(m, "blk.%u.ffn_gate_shexp.weight", il);
        l->ffn_up_shexp    = required_tensorf(m, "blk.%u.ffn_up_shexp.weight", il);
        l->ffn_down_shexp  = required_tensorf(m, "blk.%u.ffn_down_shexp.weight", il);

        if (il < DS4_N_HASH_LAYER) {
```<｜Assistant｜></think>


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

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

File: ds4.c

```c
b.weight", il);
        l->attn_kv         = required_tensorf(m, "blk.%u.attn_kv.weight", il);
        l->attn_kv_a_norm  = required_tensorf(m, "blk.%u.attn_kv_a_norm.weight", il);
        l->attn_sinks      = required_tensorf(m, "blk.%u.attn_sinks.weight", il);
        l->attn_output_a   = required_tensorf(m, "blk.%u.attn_output_a.weight", il);
        l->attn_output_b   = required_tensorf(m, "blk.%u.attn_output_b.weight", il);
        if (compress_ratio != 0) {
            l->attn_compressor_ape  = required_tensorf(m, "blk.%u.attn_compressor_ape.weight", il);
            l->attn_compressor_kv   = required_tensorf(m, "blk.%u.attn_compressor_kv.weight", il);
            l->attn_compressor_gate = required_tensorf(m, "blk.%u.attn_compressor_gate.weight", il);
            l->attn_compressor_norm = required_tensorf(m, "blk.%u.attn_compressor_norm.weight", il);
        }
        if (compress_ratio == 4) {
            l->indexer_attn_q_b = required_tensorf(m, "blk.%u.indexer.attn_q_b.weight", il);
            l->indexer_proj     = required_tensorf(m, "blk.%u.indexer.proj.weight", il);
            l->indexer_compressor_ape  = required_tensorf(m, "blk.%u.indexer_compressor_ape.weight", il);
            l->indexer_compressor_kv   = required_tensorf(m, "blk.%u.indexer_compressor_kv.weight", il);
            l->indexer_compressor_gate = required_tensorf(m, "blk.%u.indexer_compressor_gate.weight", il);
            l->indexer_compressor_norm = required_tensorf(m, "blk.%u.indexer_compressor_norm.weight", il);
        }
        l->hc_ffn_fn       = required_tensorf(m, "blk.%u.hc_ffn_fn.weight", il);
        l->hc_ffn_scale    = required_tensorf(m, "blk.%u.hc_ffn_scale.weight", il);
        l->hc_ffn_base     = required_tensorf(m, "blk.%u.hc_ffn_base.weight", il);
        l->ffn_norm        = required_tensorf(m, "blk.%u.ffn_norm.weight", il);
        l->ffn_gate_inp    = required_tensorf(m, "blk.%u.ffn_gate_inp.weight", il);
        l->ffn_exp_probs_b = tensor_by_namef(m, "blk.%u.exp_probs_b.bias", il);
        l->ffn_gate_exps   = required_tensorf(m, "blk.%u.ffn_gate_exps.weight", il);
        l->ffn_up_exps     = required_tensorf(m, "blk.%u.ffn_up_exps.weight", il);
        l->ffn_down_exps   = required_tensorf(m, "blk.%u.ffn_down_exps.weight", il);
        l->ffn_gate_shexp  = required_tensorf(m, "blk.%u.ffn_gate_shexp.weight", il);
        l->ffn_up_shexp    = required_tensorf(m, "blk.%u.ffn_up_shexp.weight", il);
        l->ffn_down_shexp  = required_tensorf(m, "blk.%u.ffn_down_shexp.weight", il);

        if (il < DS4_N_HASH_LAYER) {
```

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

File: ds4.c

```c
b.weight", il);
        l->attn_kv         = required_tensorf(m, "blk.%u.attn_kv.weight", il);
        l->attn_kv_a_norm  = required_tensorf(m, "blk.%u.attn_kv_a_norm.weight", il);
        l->attn_sinks      = required_tensorf(m, "blk.%u.attn_sinks.weight", il);
        l->attn_output_a   = required_tensorf(m, "blk.%u.attn_output_a.weight", il);
        l->attn_output_b   = required_tensorf(m, "blk.%u.attn_output_b.weight", il);
        if (compress_ratio != 0) {
            l->attn_compressor_ape  = required_tensorf(m, "blk.%u.attn_compressor_ape.weight", il);
            l->attn_compressor_kv   = required_tensorf(m, "blk.%u.attn_compressor_kv.weight", il);
            l->attn_compressor_gate = required_tensorf(m, "blk.%u.attn_compressor_gate.weight", il);
            l->attn_compressor_norm = required_tensorf(m, "blk.%u.attn_compressor_norm.weight", il);
        }
        if (compress_ratio == 4) {
            l->indexer_attn_q_b = required_tensorf(m, "blk.%u.indexer.attn_q_b.weight", il);
            l->indexer_proj     = required_tensorf(m, "blk.%u.indexer.proj.weight", il);
            l->indexer_compressor_ape  = required_tensorf(m, "blk.%u.indexer_compressor_ape.weight", il);
            l->indexer_compressor_kv   = required_tensorf(m, "blk.%u.indexer_compressor_kv.weight", il);
            l->indexer_compressor_gate = required_tensorf(m, "blk.%u.indexer_compressor_gate.weight", il);
            l->indexer_compressor_norm = required_tensorf(m, "blk.%u.indexer_compressor_norm.weight", il);
        }
        l->hc_ffn_fn       = required_tensorf(m, "blk.%u.hc_ffn_fn.weight", il);
        l->hc_ffn_scale    = required_tensorf(m, "blk.%u.hc_ffn_scale.weight", il);
        l->hc_ffn_base     = required_tensorf(m, "blk.%u.hc_ffn_base.weight", il);
        l->ffn_norm        = required_tensorf(m, "blk.%u.ffn_norm.weight", il);
        l->ffn_gate_inp    = required_tensorf(m, "blk.%u.ffn_gate_inp.weight", il);
        l->ffn_exp_probs_b = tensor_by_namef(m, "blk.%u.exp_probs_b.bias", il);
        l->ffn_gate_exps   = required_tensorf(m, "blk.%u.ffn_gate_exps.weight", il);
        l->ffn_up_exps     = required_tensorf(m, "blk.%u.ffn_up_exps.weight", il);
        l->ffn_down_exps   = required_tensorf(m, "blk.%u.ffn_down_exps.weight", il);
        l->ffn_gate_shexp  = required_tensorf(m, "blk.%u.ffn_gate_shexp.weight", il);
        l->ffn_up_shexp    = required_tensorf(m, "blk.%u.ffn_up_shexp.weight", il);
        l->ffn_down_shexp  = required_tensorf(m, "blk.%u.ffn_down_shexp.weight", il);

        if (il < DS4_N_HASH_LAYER) {
```<｜Assistant｜><think>


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

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

File: ds4.c

```c
= required_tensorf(m, "blk.%u.ffn_up_shexp.weight", il);
        l->ffn_down_shexp  = required_tensorf(m, "blk.%u.ffn_down_shexp.weight", il);

        if (il < DS4_N_HASH_LAYER) {
            l->ffn_gate_tid2eid = required_tensorf(m, "blk.%u.ffn_gate_tid2eid.weight", il);
        }
    }

    weights_validate_layout(w);
}

static void mtp_weights_bind(ds4_mtp_weights *w, const ds4_model *m) {
    memset(w, 0, sizeof(*w));

    w->hc_head_base  = required_tensor(m, "mtp.0.hc_head_base.weight");
    w->hc_head_fn    = required_tensor(m, "mtp.0.hc_head_fn.weight");
    w->hc_head_scale = required_tensor(m, "mtp.0.hc_head_scale.weight");
    w->e_proj        = required_tensor(m, "mtp.0.e_proj.weight");
    w->h_proj        = required_tensor(m, "mtp.0.h_proj.weight");
    w->enorm         = required_tensor(m, "mtp.0.enorm.weight");
    w->hnorm         = required_tensor(m, "mtp.0.hnorm.weight");
    w->norm          = required_tensor(m, "mtp.0.norm.weight");

    ds4_layer_weights *l = &w->block;
    l->hc_attn_fn      = required_tensor(m, "mtp.0.hc_attn_fn.weight");
    l->hc_attn_scale   = required_tensor(m, "mtp.0.hc_attn_scale.weight");
    l->hc_attn_base    = required_tensor(m, "mtp.0.hc_attn_base.weight");
    l->attn_norm       = required_tensor(m, "mtp.0.attn_norm.weight");
    l->attn_q_a        = required_tensor(m, "mtp.0.attn_q_a.weight");
    l->attn_q_a_norm   = required_tensor(m, "mtp.0.attn_q_a_norm.weight");
    l->attn_q_b        = required_tensor(m, "mtp.0.attn_q_b.weight");
    l->attn_kv         = required_tensor(m, "mtp.0.attn_kv.weight");
    l->attn_kv_a_norm  = required_tensor(m, "mtp.0.attn_kv_a_norm.weight");
    l->attn_sinks      = required_tensor(m, "mtp.0.attn_sinks.weight");
    l->attn_output_a   = required_tensor(m, "mtp.0.attn_output_a.weight");
    l->attn_output_b   = required_tensor(m, "mtp.0.attn_output_b.weight");
    l->hc_ffn_fn       = required_tensor(m, "mtp.0.hc_ffn_fn.weight");
    l->hc_ffn_scale    = required_tensor(m, "mtp.0.hc_ffn_scale.weight");
    l->hc_ffn_base     = required_tensor(m, "mtp.0.hc_ffn_base.weight");
    l->ffn_norm        = required_tensor(m, "mtp.0.ffn_norm.weight");
    l->ffn_gate_inp    = required_tensor(m, "mtp.0.ffn_gate_inp.weight");
    l->ffn_exp_probs_b = required_tensor(m, "mtp.0.exp_probs_b.bias");
    l->ffn_gate_exps   = required_tensor(m, "mtp.0.ffn_gate_exps.weight");
    l->ffn_up_exps     = required_tensor(m, "mtp.0.ffn_up_exps.weight");
    l->ffn_down_exps   = required_tensor(m, "mtp.0.ffn_down_exps.weight");
```

<｜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
= required_tensorf(m, "blk.%u.ffn_up_shexp.weight", il);
        l->ffn_down_shexp  = required_tensorf(m, "blk.%u.ffn_down_shexp.weight", il);

        if (il < DS4_N_HASH_LAYER) {
            l->ffn_gate_tid2eid = required_tensorf(m, "blk.%u.ffn_gate_tid2eid.weight", il);
        }
    }

    weights_validate_layout(w);
}

static void mtp_weights_bind(ds4_mtp_weights *w, const ds4_model *m) {
    memset(w, 0, sizeof(*w));

    w->hc_head_base  = required_tensor(m, "mtp.0.hc_head_base.weight");
    w->hc_head_fn    = required_tensor(m, "mtp.0.hc_head_fn.weight");
    w->hc_head_scale = required_tensor(m, "mtp.0.hc_head_scale.weight");
    w->e_proj        = required_tensor(m, "mtp.0.e_proj.weight");
    w->h_proj        = required_tensor(m, "mtp.0.h_proj.weight");
    w->enorm         = required_tensor(m, "mtp.0.enorm.weight");
    w->hnorm         = required_tensor(m, "mtp.0.hnorm.weight");
    w->norm          = required_tensor(m, "mtp.0.norm.weight");

    ds4_layer_weights *l = &w->block;
    l->hc_attn_fn      = required_tensor(m, "mtp.0.hc_attn_fn.weight");
    l->hc_attn_scale   = required_tensor(m, "mtp.0.hc_attn_scale.weight");
    l->hc_attn_base    = required_tensor(m, "mtp.0.hc_attn_base.weight");
    l->attn_norm       = required_tensor(m, "mtp.0.attn_norm.weight");
    l->attn_q_a        = required_tensor(m, "mtp.0.attn_q_a.weight");
    l->attn_q_a_norm   = required_tensor(m, "mtp.0.attn_q_a_norm.weight");
    l->attn_q_b        = required_tensor(m, "mtp.0.attn_q_b.weight");
    l->attn_kv         = required_tensor(m, "mtp.0.attn_kv.weight");
    l->attn_kv_a_norm  = required_tensor(m, "mtp.0.attn_kv_a_norm.weight");
    l->attn_sinks      = required_tensor(m, "mtp.0.attn_sinks.weight");
    l->attn_output_a   = required_tensor(m, "mtp.0.attn_output_a.weight");
    l->attn_output_b   = required_tensor(m, "mtp.0.attn_output_b.weight");
    l->hc_ffn_fn       = required_tensor(m, "mtp.0.hc_ffn_fn.weight");
    l->hc_ffn_scale    = required_tensor(m, "mtp.0.hc_ffn_scale.weight");
    l->hc_ffn_base     = required_tensor(m, "mtp.0.hc_ffn_base.weight");
    l->ffn_norm        = required_tensor(m, "mtp.0.ffn_norm.weight");
    l->ffn_gate_inp    = required_tensor(m, "mtp.0.ffn_gate_inp.weight");
    l->ffn_exp_probs_b = required_tensor(m, "mtp.0.exp_probs_b.bias");
    l->ffn_gate_exps   = required_tensor(m, "mtp.0.ffn_gate_exps.weight");
    l->ffn_up_exps     = required_tensor(m, "mtp.0.ffn_up_exps.weight");
    l->ffn_down_exps   = required_tensor(m, "mtp.0.ffn_down_exps.weight");
```<｜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
= required_tensorf(m, "blk.%u.ffn_up_shexp.weight", il);
        l->ffn_down_shexp  = required_tensorf(m, "blk.%u.ffn_down_shexp.weight", il);

        if (il < DS4_N_HASH_LAYER) {
            l->ffn_gate_tid2eid = required_tensorf(m, "blk.%u.ffn_gate_tid2eid.weight", il);
        }
    }

    weights_validate_layout(w);
}

static void mtp_weights_bind(ds4_mtp_weights *w, const ds4_model *m) {
    memset(w, 0, sizeof(*w));

    w->hc_head_base  = required_tensor(m, "mtp.0.hc_head_base.weight");
    w->hc_head_fn    = required_tensor(m, "mtp.0.hc_head_fn.weight");
    w->hc_head_scale = required_tensor(m, "mtp.0.hc_head_scale.weight");
    w->e_proj        = required_tensor(m, "mtp.0.e_proj.weight");
    w->h_proj        = required_tensor(m, "mtp.0.h_proj.weight");
    w->enorm         = required_tensor(m, "mtp.0.enorm.weight");
    w->hnorm         = required_tensor(m, "mtp.0.hnorm.weight");
    w->norm          = required_tensor(m, "mtp.0.norm.weight");

    ds4_layer_weights *l = &w->block;
    l->hc_attn_fn      = required_tensor(m, "mtp.0.hc_attn_fn.weight");
    l->hc_attn_scale   = required_tensor(m, "mtp.0.hc_attn_scale.weight");
    l->hc_attn_base    = required_tensor(m, "mtp.0.hc_attn_base.weight");
    l->attn_norm       = required_tensor(m, "mtp.0.attn_norm.weight");
    l->attn_q_a        = required_tensor(m, "mtp.0.attn_q_a.weight");
    l->attn_q_a_norm   = required_tensor(m, "mtp.0.attn_q_a_norm.weight");
    l->attn_q_b        = required_tensor(m, "mtp.0.attn_q_b.weight");
    l->attn_kv         = required_tensor(m, "mtp.0.attn_kv.weight");
    l->attn_kv_a_norm  = required_tensor(m, "mtp.0.attn_kv_a_norm.weight");
    l->attn_sinks      = required_tensor(m, "mtp.0.attn_sinks.weight");
    l->attn_output_a   = required_tensor(m, "mtp.0.attn_output_a.weight");
    l->attn_output_b   = required_tensor(m, "mtp.0.attn_output_b.weight");
    l->hc_ffn_fn       = required_tensor(m, "mtp.0.hc_ffn_fn.weight");
    l->hc_ffn_scale    = required_tensor(m, "mtp.0.hc_ffn_scale.weight");
    l->hc_ffn_base     = required_tensor(m, "mtp.0.hc_ffn_base.weight");
    l->ffn_norm        = required_tensor(m, "mtp.0.ffn_norm.weight");
    l->ffn_gate_inp    = required_tensor(m, "mtp.0.ffn_gate_inp.weight");
    l->ffn_exp_probs_b = required_tensor(m, "mtp.0.exp_probs_b.bias");
    l->ffn_gate_exps   = required_tensor(m, "mtp.0.ffn_gate_exps.weight");
    l->ffn_up_exps     = required_tensor(m, "mtp.0.ffn_up_exps.weight");
    l->ffn_down_exps   = required_tensor(m, "mtp.0.ffn_down_exps.weight");
```

<｜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
= required_tensorf(m, "blk.%u.ffn_up_shexp.weight", il);
        l->ffn_down_shexp  = required_tensorf(m, "blk.%u.ffn_down_shexp.weight", il);

        if (il < DS4_N_HASH_LAYER) {
            l->ffn_gate_tid2eid = required_tensorf(m, "blk.%u.ffn_gate_tid2eid.weight", il);
        }
    }

    weights_validate_layout(w);
}

static void mtp_weights_bind(ds4_mtp_weights *w, const ds4_model *m) {
    memset(w, 0, sizeof(*w));

    w->hc_head_base  = required_tensor(m, "mtp.0.hc_head_base.weight");
    w->hc_head_fn    = required_tensor(m, "mtp.0.hc_head_fn.weight");
    w->hc_head_scale = required_tensor(m, "mtp.0.hc_head_scale.weight");
    w->e_proj        = required_tensor(m, "mtp.0.e_proj.weight");
    w->h_proj        = required_tensor(m, "mtp.0.h_proj.weight");
    w->enorm         = required_tensor(m, "mtp.0.enorm.weight");
    w->hnorm         = required_tensor(m, "mtp.0.hnorm.weight");
    w->norm          = required_tensor(m, "mtp.0.norm.weight");

    ds4_layer_weights *l = &w->block;
    l->hc_attn_fn      = required_tensor(m, "mtp.0.hc_attn_fn.weight");
    l->hc_attn_scale   = required_tensor(m, "mtp.0.hc_attn_scale.weight");
    l->hc_attn_base    = required_tensor(m, "mtp.0.hc_attn_base.weight");
    l->attn_norm       = required_tensor(m, "mtp.0.attn_norm.weight");
    l->attn_q_a        = required_tensor(m, "mtp.0.attn_q_a.weight");
    l->attn_q_a_norm   = required_tensor(m, "mtp.0.attn_q_a_norm.weight");
    l->attn_q_b        = required_tensor(m, "mtp.0.attn_q_b.weight");
    l->attn_kv         = required_tensor(m, "mtp.0.attn_kv.weight");
    l->attn_kv_a_norm  = required_tensor(m, "mtp.0.attn_kv_a_norm.weight");
    l->attn_sinks      = required_tensor(m, "mtp.0.attn_sinks.weight");
    l->attn_output_a   = required_tensor(m, "mtp.0.attn_output_a.weight");
    l->attn_output_b   = required_tensor(m, "mtp.0.attn_output_b.weight");
    l->hc_ffn_fn       = required_tensor(m, "mtp.0.hc_ffn_fn.weight");
    l->hc_ffn_scale    = required_tensor(m, "mtp.0.hc_ffn_scale.weight");
    l->hc_ffn_base     = required_tensor(m, "mtp.0.hc_ffn_base.weight");
    l->ffn_norm        = required_tensor(m, "mtp.0.ffn_norm.weight");
    l->ffn_gate_inp    = required_tensor(m, "mtp.0.ffn_gate_inp.weight");
    l->ffn_exp_probs_b = required_tensor(m, "mtp.0.exp_probs_b.bias");
    l->ffn_gate_exps   = required_tensor(m, "mtp.0.ffn_gate_exps.weight");
    l->ffn_up_exps     = required_tensor(m, "mtp.0.ffn_up_exps.weight");
    l->ffn_down_exps   = required_tensor(m, "mtp.0.ffn_down_exps.weight");
```<｜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
, "mtp.0.ffn_gate_exps.weight");
    l->ffn_up_exps     = required_tensor(m, "mtp.0.ffn_up_exps.weight");
    l->ffn_down_exps   = required_tensor(m, "mtp.0.ffn_down_exps.weight");
    l->ffn_gate_shexp  = required_tensor(m, "mtp.0.ffn_gate_shexp.weight");
    l->ffn_up_shexp    = required_tensor(m, "mtp.0.ffn_up_shexp.weight");
    l->ffn_down_shexp  = required_tensor(m, "mtp.0.ffn_down_shexp.weight");

    mtp_weights_validate_layout(w);
}

static void weights_free(ds4_weights *w) {
    memset(w, 0, sizeof(*w));
}

/* Load one token embedding row and expand it to float activations. */
static void embed_token_f16(const ds4_model *m, const ds4_weights *w, int token, float *out) {
    ds4_tensor *te = w->token_embd;
    if (token < 0 || (uint64_t)token >= te->dim[1]) {
        ds4_die("token id is outside the embedding table");
    }

    const uint16_t *base = tensor_data(m, te);
    const uint64_t stride = te->dim[0];
    const uint16_t *row = base + (uint64_t)token * stride;

    for (uint64_t i = 0; i < stride; i++) {
        out[i] = f16_to_f32(row[i]);
    }
}

/* RMSNorm without a learned scale, used by hyper-connection control vectors. */
static void rms_norm_no_weight(float *out, const float *x, uint64_t n, float eps) {
    double ss = 0.0;
    for (uint64_t i = 0; i < n; i++) ss += (double)x[i] * x[i];

    const float scale = 1.0f / sqrtf((float)(ss / (double)n) + eps);
    for (uint64_t i = 0; i < n; i++) out[i] = x[i] * scale;
}

/* Standard DS4 RMSNorm with learned per-channel scale. */
static void rms_norm_weight(float *out, const float *x, const float *weight, uint64_t n, float eps) {
    double ss = 0.0;
    for (uint64_t i = 0; i < n; i++) ss += (double)x[i] * x[i];

    const float scale = 1.0f / sqrtf((float)(ss / (double)n) + eps);
    for (uint64_t i = 0; i < n; i++) out[i] = x[i] * scale * weight[i];
}

/* Normalize each attention head independently after Q projection. */
static void head_rms_norm_inplace(float *x, uint32_t n_head, uint32_t head_dim, float eps) {
    for (uint32_t h = 0; h < n_head; h++) {
        float *head = x + (uint64_t)h * head_dim;
        double ss = 0.0;
        for (uint32_t i = 0; i < head_dim; i++) ss += (double)head[i] * head[i];

        const float scale = 1.0f / sqrtf((float)(ss / (double)head_dim) + eps);
        for (uint32_t i = 0; i < head_dim; i++) head[i] *= scale;
    }
}

typedef struct {
    float *out;
    const uint16_t *data;
    const float *x;
    uint64_t in_dim;
} matvec_f16_ctx;

static inline float dot_f16_row(const uint16_t *row, const float *x, uint64_t n) {
```

<｜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
, "mtp.0.ffn_gate_exps.weight");
    l->ffn_up_exps     = required_tensor(m, "mtp.0.ffn_up_exps.weight");
    l->ffn_down_exps   = required_tensor(m, "mtp.0.ffn_down_exps.weight");
    l->ffn_gate_shexp  = required_tensor(m, "mtp.0.ffn_gate_shexp.weight");
    l->ffn_up_shexp    = required_tensor(m, "mtp.0.ffn_up_shexp.weight");
    l->ffn_down_shexp  = required_tensor(m, "mtp.0.ffn_down_shexp.weight");

    mtp_weights_validate_layout(w);
}

static void weights_free(ds4_weights *w) {
    memset(w, 0, sizeof(*w));
}

/* Load one token embedding row and expand it to float activations. */
static void embed_token_f16(const ds4_model *m, const ds4_weights *w, int token, float *out) {
    ds4_tensor *te = w->token_embd;
    if (token < 0 || (uint64_t)token >= te->dim[1]) {
        ds4_die("token id is outside the embedding table");
    }

    const uint16_t *base = tensor_data(m, te);
    const uint64_t stride = te->dim[0];
    const uint16_t *row = base + (uint64_t)token * stride;

    for (uint64_t i = 0; i < stride; i++) {
        out[i] = f16_to_f32(row[i]);
    }
}

/* RMSNorm without a learned scale, used by hyper-connection control vectors. */
static void rms_norm_no_weight(float *out, const float *x, uint64_t n, float eps) {
    double ss = 0.0;
    for (uint64_t i = 0; i < n; i++) ss += (double)x[i] * x[i];

    const float scale = 1.0f / sqrtf((float)(ss / (double)n) + eps);
    for (uint64_t i = 0; i < n; i++) out[i] = x[i] * scale;
}

/* Standard DS4 RMSNorm with learned per-channel scale. */
static void rms_norm_weight(float *out, const float *x, const float *weight, uint64_t n, float eps) {
    double ss = 0.0;
    for (uint64_t i = 0; i < n; i++) ss += (double)x[i] * x[i];

    const float scale = 1.0f / sqrtf((float)(ss / (double)n) + eps);
    for (uint64_t i = 0; i < n; i++) out[i] = x[i] * scale * weight[i];
}

/* Normalize each attention head independently after Q projection. */
static void head_rms_norm_inplace(float *x, uint32_t n_head, uint32_t head_dim, float eps) {
    for (uint32_t h = 0; h < n_head; h++) {
        float *head = x + (uint64_t)h * head_dim;
        double ss = 0.0;
        for (uint32_t i = 0; i < head_dim; i++) ss += (double)head[i] * head[i];

        const float scale = 1.0f / sqrtf((float)(ss / (double)head_dim) + eps);
        for (uint32_t i = 0; i < head_dim; i++) head[i] *= scale;
    }
}

typedef struct {
    float *out;
    const uint16_t *data;
    const float *x;
    uint64_t in_dim;
} matvec_f16_ctx;

static inline float dot_f16_row(const uint16_t *row, const float *x, uint64_t n) {
```<｜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
, "mtp.0.ffn_gate_exps.weight");
    l->ffn_up_exps     = required_tensor(m, "mtp.0.ffn_up_exps.weight");
    l->ffn_down_exps   = required_tensor(m, "mtp.0.ffn_down_exps.weight");
    l->ffn_gate_shexp  = required_tensor(m, "mtp.0.ffn_gate_shexp.weight");
    l->ffn_up_shexp    = required_tensor(m, "mtp.0.ffn_up_shexp.weight");
    l->ffn_down_shexp  = required_tensor(m, "mtp.0.ffn_down_shexp.weight");

    mtp_weights_validate_layout(w);
}

static void weights_free(ds4_weights *w) {
    memset(w, 0, sizeof(*w));
}

/* Load one token embedding row and expand it to float activations. */
static void embed_token_f16(const ds4_model *m, const ds4_weights *w, int token, float *out) {
    ds4_tensor *te = w->token_embd;
    if (token < 0 || (uint64_t)token >= te->dim[1]) {
        ds4_die("token id is outside the embedding table");
    }

    const uint16_t *base = tensor_data(m, te);
    const uint64_t stride = te->dim[0];
    const uint16_t *row = base + (uint64_t)token * stride;

    for (uint64_t i = 0; i < stride; i++) {
        out[i] = f16_to_f32(row[i]);
    }
}

/* RMSNorm without a learned scale, used by hyper-connection control vectors. */
static void rms_norm_no_weight(float *out, const float *x, uint64_t n, float eps) {
    double ss = 0.0;
    for (uint64_t i = 0; i < n; i++) ss += (double)x[i] * x[i];

    const float scale = 1.0f / sqrtf((float)(ss / (double)n) + eps);
    for (uint64_t i = 0; i < n; i++) out[i] = x[i] * scale;
}

/* Standard DS4 RMSNorm with learned per-channel scale. */
static void rms_norm_weight(float *out, const float *x, const float *weight, uint64_t n, float eps) {
    double ss = 0.0;
    for (uint64_t i = 0; i < n; i++) ss += (double)x[i] * x[i];

    const float scale = 1.0f / sqrtf((float)(ss / (double)n) + eps);
    for (uint64_t i = 0; i < n; i++) out[i] = x[i] * scale * weight[i];
}

/* Normalize each attention head independently after Q projection. */
static void head_rms_norm_inplace(float *x, uint32_t n_head, uint32_t head_dim, float eps) {
    for (uint32_t h = 0; h < n_head; h++) {
        float *head = x + (uint64_t)h * head_dim;
        double ss = 0.0;
        for (uint32_t i = 0; i < head_dim; i++) ss += (double)head[i] * head[i];

        const float scale = 1.0f / sqrtf((float)(ss / (double)head_dim) + eps);
        for (uint32_t i = 0; i < head_dim; i++) head[i] *= scale;
    }
}

typedef struct {
    float *out;
    const uint16_t *data;
    const float *x;
    uint64_t in_dim;
} matvec_f16_ctx;

static inline float dot_f16_row(const uint16_t *row, const float *x, uint64_t n) {
```

<｜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
, "mtp.0.ffn_gate_exps.weight");
    l->ffn_up_exps     = required_tensor(m, "mtp.0.ffn_up_exps.weight");
    l->ffn_down_exps   = required_tensor(m, "mtp.0.ffn_down_exps.weight");
    l->ffn_gate_shexp  = required_tensor(m, "mtp.0.ffn_gate_shexp.weight");
    l->ffn_up_shexp    = required_tensor(m, "mtp.0.ffn_up_shexp.weight");
    l->ffn_down_shexp  = required_tensor(m, "mtp.0.ffn_down_shexp.weight");

    mtp_weights_validate_layout(w);
}

static void weights_free(ds4_weights *w) {
    memset(w, 0, sizeof(*w));
}

/* Load one token embedding row and expand it to float activations. */
static void embed_token_f16(const ds4_model *m, const ds4_weights *w, int token, float *out) {
    ds4_tensor *te = w->token_embd;
    if (token < 0 || (uint64_t)token >= te->dim[1]) {
        ds4_die("token id is outside the embedding table");
    }

    const uint16_t *base = tensor_data(m, te);
    const uint64_t stride = te->dim[0];
    const uint16_t *row = base + (uint64_t)token * stride;

    for (uint64_t i = 0; i < stride; i++) {
        out[i] = f16_to_f32(row[i]);
    }
}

/* RMSNorm without a learned scale, used by hyper-connection control vectors. */
static void rms_norm_no_weight(float *out, const float *x, uint64_t n, float eps) {
    double ss = 0.0;
    for (uint64_t i = 0; i < n; i++) ss += (double)x[i] * x[i];

    const float scale = 1.0f / sqrtf((float)(ss / (double)n) + eps);
    for (uint64_t i = 0; i < n; i++) out[i] = x[i] * scale;
}

/* Standard DS4 RMSNorm with learned per-channel scale. */
static void rms_norm_weight(float *out, const float *x, const float *weight, uint64_t n, float eps) {
    double ss = 0.0;
    for (uint64_t i = 0; i < n; i++) ss += (double)x[i] * x[i];

    const float scale = 1.0f / sqrtf((float)(ss / (double)n) + eps);
    for (uint64_t i = 0; i < n; i++) out[i] = x[i] * scale * weight[i];
}

/* Normalize each attention head independently after Q projection. */
static void head_rms_norm_inplace(float *x, uint32_t n_head, uint32_t head_dim, float eps) {
    for (uint32_t h = 0; h < n_head; h++) {
        float *head = x + (uint64_t)h * head_dim;
        double ss = 0.0;
        for (uint32_t i = 0; i < head_dim; i++) ss += (double)head[i] * head[i];

        const float scale = 1.0f / sqrtf((float)(ss / (double)head_dim) + eps);
        for (uint32_t i = 0; i < head_dim; i++) head[i] *= scale;
    }
}

typedef struct {
    float *out;
    const uint16_t *data;
    const float *x;
    uint64_t in_dim;
} matvec_f16_ctx;

static inline float dot_f16_row(const uint16_t *row, const float *x, uint64_t n) {
```<｜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
float *out;
    const uint16_t *data;
    const float *x;
    uint64_t in_dim;
} matvec_f16_ctx;

static inline float dot_f16_row(const uint16_t *row, const float *x, uint64_t n) {
#if defined(__ARM_NEON)
    uint64_t i = 0;
    float32x4_t acc0 = vdupq_n_f32(0.0f);
    float32x4_t acc1 = vdupq_n_f32(0.0f);
    for (; i + 8 <= n; i += 8) {
        const float16x8_t hv = vreinterpretq_f16_u16(vld1q_u16(row + i));
        const float32x4_t h0 = vcvt_f32_f16(vget_low_f16(hv));
        const float32x4_t h1 = vcvt_f32_f16(vget_high_f16(hv));
        acc0 = vfmaq_f32(acc0, h0, vld1q_f32(x + i));
        acc1 = vfmaq_f32(acc1, h1, vld1q_f32(x + i + 4));
    }

    float acc = vaddvq_f32(vaddq_f32(acc0, acc1));
    for (; i < n; i++) acc += f16_to_f32(row[i]) * x[i];
    return acc;
#else
    float acc = 0.0f;
    for (uint64_t i = 0; i < n; i++) acc += f16_to_f32(row[i]) * x[i];
    return acc;
#endif
}

static void matvec_f16_worker(void *vctx, uint64_t row0, uint64_t row1) {
    matvec_f16_ctx *ctx = vctx;

    for (uint64_t o = row0; o < row1; o++) {
        const uint16_t *row = ctx->data + o * ctx->in_dim;
        ctx->out[o] = dot_f16_row(row, ctx->x, ctx->in_dim);
    }
}

/* Dense F16 matvec for small control projections such as HC and router heads. */
static void matvec_f16(float *out, const ds4_model *m, const ds4_tensor *w, const float *x) {
    if (w->type != 1 || w->ndim != 2) ds4_die("expected a 2D F16 tensor");

    const uint64_t in_dim = w->dim[0];
    const uint64_t out_dim = w->dim[1];
    matvec_f16_ctx ctx = {
        .out = out,
        .data = tensor_data(m, w),
        .x = x,
        .in_dim = in_dim,
    };

    const uint64_t ops = in_dim * out_dim;
    const uint64_t min_rows = ops >= 262144 ? 1 : 512;
    ds4_parallel_for_min_rows(out_dim, matvec_f16_worker, &ctx, min_rows);
}

static void matvec_f16_serial(float *out, const ds4_model *m, const ds4_tensor *w, const float *x) {
    if (w->type != 1 || w->ndim != 2) ds4_die("expected a 2D F16 tensor");

    const uint64_t in_dim = w->dim[0];
    const uint64_t out_dim = w->dim[1];
    const uint16_t *data = tensor_data(m, w);
    for (uint64_t o = 0; o < out_dim; o++) {
        out[o] = dot_f16_row(data + o * in_dim, x, in_dim);
    }
}

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t in_dim;
    uint64_t row0;
    uint64_t blocks;
} matvec_q8_0_ctx;

typedef struct {
    float *out0;
    float *out1;
    const uint8_t *data0;
    const uint8_t *data1;
    const int8_t *xq;
    const float *xscale;
```

<｜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
float *out;
    const uint16_t *data;
    const float *x;
    uint64_t in_dim;
} matvec_f16_ctx;

static inline float dot_f16_row(const uint16_t *row, const float *x, uint64_t n) {
#if defined(__ARM_NEON)
    uint64_t i = 0;
    float32x4_t acc0 = vdupq_n_f32(0.0f);
    float32x4_t acc1 = vdupq_n_f32(0.0f);
    for (; i + 8 <= n; i += 8) {
        const float16x8_t hv = vreinterpretq_f16_u16(vld1q_u16(row + i));
        const float32x4_t h0 = vcvt_f32_f16(vget_low_f16(hv));
        const float32x4_t h1 = vcvt_f32_f16(vget_high_f16(hv));
        acc0 = vfmaq_f32(acc0, h0, vld1q_f32(x + i));
        acc1 = vfmaq_f32(acc1, h1, vld1q_f32(x + i + 4));
    }

    float acc = vaddvq_f32(vaddq_f32(acc0, acc1));
    for (; i < n; i++) acc += f16_to_f32(row[i]) * x[i];
    return acc;
#else
    float acc = 0.0f;
    for (uint64_t i = 0; i < n; i++) acc += f16_to_f32(row[i]) * x[i];
    return acc;
#endif
}

static void matvec_f16_worker(void *vctx, uint64_t row0, uint64_t row1) {
    matvec_f16_ctx *ctx = vctx;

    for (uint64_t o = row0; o < row1; o++) {
        const uint16_t *row = ctx->data + o * ctx->in_dim;
        ctx->out[o] = dot_f16_row(row, ctx->x, ctx->in_dim);
    }
}

/* Dense F16 matvec for small control projections such as HC and router heads. */
static void matvec_f16(float *out, const ds4_model *m, const ds4_tensor *w, const float *x) {
    if (w->type != 1 || w->ndim != 2) ds4_die("expected a 2D F16 tensor");

    const uint64_t in_dim = w->dim[0];
    const uint64_t out_dim = w->dim[1];
    matvec_f16_ctx ctx = {
        .out = out,
        .data = tensor_data(m, w),
        .x = x,
        .in_dim = in_dim,
    };

    const uint64_t ops = in_dim * out_dim;
    const uint64_t min_rows = ops >= 262144 ? 1 : 512;
    ds4_parallel_for_min_rows(out_dim, matvec_f16_worker, &ctx, min_rows);
}

static void matvec_f16_serial(float *out, const ds4_model *m, const ds4_tensor *w, const float *x) {
    if (w->type != 1 || w->ndim != 2) ds4_die("expected a 2D F16 tensor");

    const uint64_t in_dim = w->dim[0];
    const uint64_t out_dim = w->dim[1];
    const uint16_t *data = tensor_data(m, w);
    for (uint64_t o = 0; o < out_dim; o++) {
        out[o] = dot_f16_row(data + o * in_dim, x, in_dim);
    }
}

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t in_dim;
    uint64_t row0;
    uint64_t blocks;
} matvec_q8_0_ctx;

typedef struct {
    float *out0;
    float *out1;
    const uint8_t *data0;
    const uint8_t *data1;
    const int8_t *xq;
    const float *xscale;
```<｜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
float *out;
    const uint16_t *data;
    const float *x;
    uint64_t in_dim;
} matvec_f16_ctx;

static inline float dot_f16_row(const uint16_t *row, const float *x, uint64_t n) {
#if defined(__ARM_NEON)
    uint64_t i = 0;
    float32x4_t acc0 = vdupq_n_f32(0.0f);
    float32x4_t acc1 = vdupq_n_f32(0.0f);
    for (; i + 8 <= n; i += 8) {
        const float16x8_t hv = vreinterpretq_f16_u16(vld1q_u16(row + i));
        const float32x4_t h0 = vcvt_f32_f16(vget_low_f16(hv));
        const float32x4_t h1 = vcvt_f32_f16(vget_high_f16(hv));
        acc0 = vfmaq_f32(acc0, h0, vld1q_f32(x + i));
        acc1 = vfmaq_f32(acc1, h1, vld1q_f32(x + i + 4));
    }

    float acc = vaddvq_f32(vaddq_f32(acc0, acc1));
    for (; i < n; i++) acc += f16_to_f32(row[i]) * x[i];
    return acc;
#else
    float acc = 0.0f;
    for (uint64_t i = 0; i < n; i++) acc += f16_to_f32(row[i]) * x[i];
    return acc;
#endif
}

static void matvec_f16_worker(void *vctx, uint64_t row0, uint64_t row1) {
    matvec_f16_ctx *ctx = vctx;

    for (uint64_t o = row0; o < row1; o++) {
        const uint16_t *row = ctx->data + o * ctx->in_dim;
        ctx->out[o] = dot_f16_row(row, ctx->x, ctx->in_dim);
    }
}

/* Dense F16 matvec for small control projections such as HC and router heads. */
static void matvec_f16(float *out, const ds4_model *m, const ds4_tensor *w, const float *x) {
    if (w->type != 1 || w->ndim != 2) ds4_die("expected a 2D F16 tensor");

    const uint64_t in_dim = w->dim[0];
    const uint64_t out_dim = w->dim[1];
    matvec_f16_ctx ctx = {
        .out = out,
        .data = tensor_data(m, w),
        .x = x,
        .in_dim = in_dim,
    };

    const uint64_t ops = in_dim * out_dim;
    const uint64_t min_rows = ops >= 262144 ? 1 : 512;
    ds4_parallel_for_min_rows(out_dim, matvec_f16_worker, &ctx, min_rows);
}

static void matvec_f16_serial(float *out, const ds4_model *m, const ds4_tensor *w, const float *x) {
    if (w->type != 1 || w->ndim != 2) ds4_die("expected a 2D F16 tensor");

    const uint64_t in_dim = w->dim[0];
    const uint64_t out_dim = w->dim[1];
    const uint16_t *data = tensor_data(m, w);
    for (uint64_t o = 0; o < out_dim; o++) {
        out[o] = dot_f16_row(data + o * in_dim, x, in_dim);
    }
}

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t in_dim;
    uint64_t row0;
    uint64_t blocks;
} matvec_q8_0_ctx;

typedef struct {
    float *out0;
    float *out1;
    const uint8_t *data0;
    const uint8_t *data1;
    const int8_t *xq;
    const float *xscale;
```

<｜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
float *out;
    const uint16_t *data;
    const float *x;
    uint64_t in_dim;
} matvec_f16_ctx;

static inline float dot_f16_row(const uint16_t *row, const float *x, uint64_t n) {
#if defined(__ARM_NEON)
    uint64_t i = 0;
    float32x4_t acc0 = vdupq_n_f32(0.0f);
    float32x4_t acc1 = vdupq_n_f32(0.0f);
    for (; i + 8 <= n; i += 8) {
        const float16x8_t hv = vreinterpretq_f16_u16(vld1q_u16(row + i));
        const float32x4_t h0 = vcvt_f32_f16(vget_low_f16(hv));
        const float32x4_t h1 = vcvt_f32_f16(vget_high_f16(hv));
        acc0 = vfmaq_f32(acc0, h0, vld1q_f32(x + i));
        acc1 = vfmaq_f32(acc1, h1, vld1q_f32(x + i + 4));
    }

    float acc = vaddvq_f32(vaddq_f32(acc0, acc1));
    for (; i < n; i++) acc += f16_to_f32(row[i]) * x[i];
    return acc;
#else
    float acc = 0.0f;
    for (uint64_t i = 0; i < n; i++) acc += f16_to_f32(row[i]) * x[i];
    return acc;
#endif
}

static void matvec_f16_worker(void *vctx, uint64_t row0, uint64_t row1) {
    matvec_f16_ctx *ctx = vctx;

    for (uint64_t o = row0; o < row1; o++) {
        const uint16_t *row = ctx->data + o * ctx->in_dim;
        ctx->out[o] = dot_f16_row(row, ctx->x, ctx->in_dim);
    }
}

/* Dense F16 matvec for small control projections such as HC and router heads. */
static void matvec_f16(float *out, const ds4_model *m, const ds4_tensor *w, const float *x) {
    if (w->type != 1 || w->ndim != 2) ds4_die("expected a 2D F16 tensor");

    const uint64_t in_dim = w->dim[0];
    const uint64_t out_dim = w->dim[1];
    matvec_f16_ctx ctx = {
        .out = out,
        .data = tensor_data(m, w),
        .x = x,
        .in_dim = in_dim,
    };

    const uint64_t ops = in_dim * out_dim;
    const uint64_t min_rows = ops >= 262144 ? 1 : 512;
    ds4_parallel_for_min_rows(out_dim, matvec_f16_worker, &ctx, min_rows);
}

static void matvec_f16_serial(float *out, const ds4_model *m, const ds4_tensor *w, const float *x) {
    if (w->type != 1 || w->ndim != 2) ds4_die("expected a 2D F16 tensor");

    const uint64_t in_dim = w->dim[0];
    const uint64_t out_dim = w->dim[1];
    const uint16_t *data = tensor_data(m, w);
    for (uint64_t o = 0; o < out_dim; o++) {
        out[o] = dot_f16_row(data + o * in_dim, x, in_dim);
    }
}

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t in_dim;
    uint64_t row0;
    uint64_t blocks;
} matvec_q8_0_ctx;

typedef struct {
    float *out0;
    float *out1;
    const uint8_t *data0;
    const uint8_t *data1;
    const int8_t *xq;
    const float *xscale;
```<｜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
_t blocks;
} matvec_q8_0_ctx;

typedef struct {
    float *out0;
    float *out1;
    const uint8_t *data0;
    const uint8_t *data1;
    const int8_t *xq;
    const float *xscale;
    uint64_t in_dim;
    uint64_t blocks;
} matvec_q8_0_pair_ctx;

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t in_dim;
    uint64_t blocks;
    uint64_t rank;
} matvec_q8_0_grouped_ctx;

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t n_tok;
    uint64_t n_groups;
    uint64_t group_dim;
    uint64_t blocks;
    uint64_t rank;
} matmul_q8_0_grouped_batch_ctx;

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t n_tok;
    uint64_t in_dim;
    uint64_t out_dim;
    uint64_t blocks;
} matmul_q8_0_batch_ctx;

typedef struct {
    float *out0;
    float *out1;
    const uint8_t *data0;
    const uint8_t *data1;
    const int8_t *xq;
    const float *xscale;
    uint64_t n_tok;
    uint64_t in_dim;
    uint64_t out_dim;
    uint64_t blocks;
} matmul_q8_0_pair_batch_ctx;

typedef struct {
    const float *x;
    int8_t *xq;
    float *xscale;
    uint64_t in_dim;
    uint64_t blocks;
} quantize_q8_0_batch_ctx;

static inline int32_t dot_i8_32(const int8_t *a, const int8_t *b, uint64_t n) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if (n == 32) {
        int32x4_t acc = vdupq_n_s32(0);
        acc = vdotq_s32(acc, vld1q_s8(a),      vld1q_s8(b));
        acc = vdotq_s32(acc, vld1q_s8(a + 16), vld1q_s8(b + 16));
        return vaddvq_s32(acc);
    }
#endif
    int32_t sum = 0;
    for (uint64_t i = 0; i < n; i++) sum += (int32_t)a[i] * (int32_t)b[i];
    return sum;
}

static inline float dot_q8_0_row(
        const uint8_t *row,
        const int8_t  *xq,
        const float   *xscale,
        uint64_t       in_dim,
        uint64_t       blocks) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if ((in_dim & 31u) == 0) {
        float32x4_t accv0 = vdupq_n_f32(0.0f);
        float32x4_t accv1 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t scale_bits0;
            uint16_t scale_bits1;
            memcpy(&scale_bits0, row + b * 34, sizeof(scale_bits0));
            memcpy(&scale_bits1, row + (b + 1) * 34, sizeof(scale_bits1));

            const int8_t *qs0 = (const int8_t *)(row + b * 34 + 2);
            const int8_t *qs1 = (const int8_t *)(row + (b + 1) * 34 + 2);
```

<｜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
_t blocks;
} matvec_q8_0_ctx;

typedef struct {
    float *out0;
    float *out1;
    const uint8_t *data0;
    const uint8_t *data1;
    const int8_t *xq;
    const float *xscale;
    uint64_t in_dim;
    uint64_t blocks;
} matvec_q8_0_pair_ctx;

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t in_dim;
    uint64_t blocks;
    uint64_t rank;
} matvec_q8_0_grouped_ctx;

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t n_tok;
    uint64_t n_groups;
    uint64_t group_dim;
    uint64_t blocks;
    uint64_t rank;
} matmul_q8_0_grouped_batch_ctx;

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t n_tok;
    uint64_t in_dim;
    uint64_t out_dim;
    uint64_t blocks;
} matmul_q8_0_batch_ctx;

typedef struct {
    float *out0;
    float *out1;
    const uint8_t *data0;
    const uint8_t *data1;
    const int8_t *xq;
    const float *xscale;
    uint64_t n_tok;
    uint64_t in_dim;
    uint64_t out_dim;
    uint64_t blocks;
} matmul_q8_0_pair_batch_ctx;

typedef struct {
    const float *x;
    int8_t *xq;
    float *xscale;
    uint64_t in_dim;
    uint64_t blocks;
} quantize_q8_0_batch_ctx;

static inline int32_t dot_i8_32(const int8_t *a, const int8_t *b, uint64_t n) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if (n == 32) {
        int32x4_t acc = vdupq_n_s32(0);
        acc = vdotq_s32(acc, vld1q_s8(a),      vld1q_s8(b));
        acc = vdotq_s32(acc, vld1q_s8(a + 16), vld1q_s8(b + 16));
        return vaddvq_s32(acc);
    }
#endif
    int32_t sum = 0;
    for (uint64_t i = 0; i < n; i++) sum += (int32_t)a[i] * (int32_t)b[i];
    return sum;
}

static inline float dot_q8_0_row(
        const uint8_t *row,
        const int8_t  *xq,
        const float   *xscale,
        uint64_t       in_dim,
        uint64_t       blocks) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if ((in_dim & 31u) == 0) {
        float32x4_t accv0 = vdupq_n_f32(0.0f);
        float32x4_t accv1 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t scale_bits0;
            uint16_t scale_bits1;
            memcpy(&scale_bits0, row + b * 34, sizeof(scale_bits0));
            memcpy(&scale_bits1, row + (b + 1) * 34, sizeof(scale_bits1));

            const int8_t *qs0 = (const int8_t *)(row + b * 34 + 2);
            const int8_t *qs1 = (const int8_t *)(row + (b + 1) * 34 + 2);
```<｜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
_t blocks;
} matvec_q8_0_ctx;

typedef struct {
    float *out0;
    float *out1;
    const uint8_t *data0;
    const uint8_t *data1;
    const int8_t *xq;
    const float *xscale;
    uint64_t in_dim;
    uint64_t blocks;
} matvec_q8_0_pair_ctx;

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t in_dim;
    uint64_t blocks;
    uint64_t rank;
} matvec_q8_0_grouped_ctx;

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t n_tok;
    uint64_t n_groups;
    uint64_t group_dim;
    uint64_t blocks;
    uint64_t rank;
} matmul_q8_0_grouped_batch_ctx;

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t n_tok;
    uint64_t in_dim;
    uint64_t out_dim;
    uint64_t blocks;
} matmul_q8_0_batch_ctx;

typedef struct {
    float *out0;
    float *out1;
    const uint8_t *data0;
    const uint8_t *data1;
    const int8_t *xq;
    const float *xscale;
    uint64_t n_tok;
    uint64_t in_dim;
    uint64_t out_dim;
    uint64_t blocks;
} matmul_q8_0_pair_batch_ctx;

typedef struct {
    const float *x;
    int8_t *xq;
    float *xscale;
    uint64_t in_dim;
    uint64_t blocks;
} quantize_q8_0_batch_ctx;

static inline int32_t dot_i8_32(const int8_t *a, const int8_t *b, uint64_t n) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if (n == 32) {
        int32x4_t acc = vdupq_n_s32(0);
        acc = vdotq_s32(acc, vld1q_s8(a),      vld1q_s8(b));
        acc = vdotq_s32(acc, vld1q_s8(a + 16), vld1q_s8(b + 16));
        return vaddvq_s32(acc);
    }
#endif
    int32_t sum = 0;
    for (uint64_t i = 0; i < n; i++) sum += (int32_t)a[i] * (int32_t)b[i];
    return sum;
}

static inline float dot_q8_0_row(
        const uint8_t *row,
        const int8_t  *xq,
        const float   *xscale,
        uint64_t       in_dim,
        uint64_t       blocks) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if ((in_dim & 31u) == 0) {
        float32x4_t accv0 = vdupq_n_f32(0.0f);
        float32x4_t accv1 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t scale_bits0;
            uint16_t scale_bits1;
            memcpy(&scale_bits0, row + b * 34, sizeof(scale_bits0));
            memcpy(&scale_bits1, row + (b + 1) * 34, sizeof(scale_bits1));

            const int8_t *qs0 = (const int8_t *)(row + b * 34 + 2);
            const int8_t *qs1 = (const int8_t *)(row + (b + 1) * 34 + 2);
```

<｜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
_t blocks;
} matvec_q8_0_ctx;

typedef struct {
    float *out0;
    float *out1;
    const uint8_t *data0;
    const uint8_t *data1;
    const int8_t *xq;
    const float *xscale;
    uint64_t in_dim;
    uint64_t blocks;
} matvec_q8_0_pair_ctx;

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t in_dim;
    uint64_t blocks;
    uint64_t rank;
} matvec_q8_0_grouped_ctx;

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t n_tok;
    uint64_t n_groups;
    uint64_t group_dim;
    uint64_t blocks;
    uint64_t rank;
} matmul_q8_0_grouped_batch_ctx;

typedef struct {
    float *out;
    const uint8_t *data;
    const int8_t *xq;
    const float *xscale;
    uint64_t n_tok;
    uint64_t in_dim;
    uint64_t out_dim;
    uint64_t blocks;
} matmul_q8_0_batch_ctx;

typedef struct {
    float *out0;
    float *out1;
    const uint8_t *data0;
    const uint8_t *data1;
    const int8_t *xq;
    const float *xscale;
    uint64_t n_tok;
    uint64_t in_dim;
    uint64_t out_dim;
    uint64_t blocks;
} matmul_q8_0_pair_batch_ctx;

typedef struct {
    const float *x;
    int8_t *xq;
    float *xscale;
    uint64_t in_dim;
    uint64_t blocks;
} quantize_q8_0_batch_ctx;

static inline int32_t dot_i8_32(const int8_t *a, const int8_t *b, uint64_t n) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if (n == 32) {
        int32x4_t acc = vdupq_n_s32(0);
        acc = vdotq_s32(acc, vld1q_s8(a),      vld1q_s8(b));
        acc = vdotq_s32(acc, vld1q_s8(a + 16), vld1q_s8(b + 16));
        return vaddvq_s32(acc);
    }
#endif
    int32_t sum = 0;
    for (uint64_t i = 0; i < n; i++) sum += (int32_t)a[i] * (int32_t)b[i];
    return sum;
}

static inline float dot_q8_0_row(
        const uint8_t *row,
        const int8_t  *xq,
        const float   *xscale,
        uint64_t       in_dim,
        uint64_t       blocks) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if ((in_dim & 31u) == 0) {
        float32x4_t accv0 = vdupq_n_f32(0.0f);
        float32x4_t accv1 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t scale_bits0;
            uint16_t scale_bits1;
            memcpy(&scale_bits0, row + b * 34, sizeof(scale_bits0));
            memcpy(&scale_bits1, row + (b + 1) * 34, sizeof(scale_bits1));

            const int8_t *qs0 = (const int8_t *)(row + b * 34 + 2);
            const int8_t *qs1 = (const int8_t *)(row + (b + 1) * 34 + 2);
```<｜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
+ (b + 1) * 34, sizeof(scale_bits1));

            const int8_t *qs0 = (const int8_t *)(row + b * 34 + 2);
            const int8_t *qs1 = (const int8_t *)(row + (b + 1) * 34 + 2);
            const int8_t *xq0 = xq + b * 32;
            const int8_t *xq1 = xq + (b + 1) * 32;

            int32x4_t dot0 = vdupq_n_s32(0);
            dot0 = vdotq_s32(dot0, vld1q_s8(qs0),      vld1q_s8(xq0));
            dot0 = vdotq_s32(dot0, vld1q_s8(qs0 + 16), vld1q_s8(xq0 + 16));

            int32x4_t dot1 = vdupq_n_s32(0);
            dot1 = vdotq_s32(dot1, vld1q_s8(qs1),      vld1q_s8(xq1));
            dot1 = vdotq_s32(dot1, vld1q_s8(qs1 + 16), vld1q_s8(xq1 + 16));

            accv0 = vfmaq_n_f32(accv0, vcvtq_f32_s32(dot0), f16_to_f32(scale_bits0) * xscale[b]);
            accv1 = vfmaq_n_f32(accv1, vcvtq_f32_s32(dot1), f16_to_f32(scale_bits1) * xscale[b + 1]);
        }

        if (b < blocks) {
            uint16_t scale_bits;
            memcpy(&scale_bits, row + b * 34, sizeof(scale_bits));
            const int8_t *qs = (const int8_t *)(row + b * 34 + 2);
            const int8_t *xqb = xq + b * 32;
            int32x4_t dot = vdupq_n_s32(0);
            dot = vdotq_s32(dot, vld1q_s8(qs),      vld1q_s8(xqb));
            dot = vdotq_s32(dot, vld1q_s8(qs + 16), vld1q_s8(xqb + 16));
            accv0 = vfmaq_n_f32(accv0, vcvtq_f32_s32(dot), f16_to_f32(scale_bits) * xscale[b]);
        }

        return vaddvq_f32(vaddq_f32(accv0, accv1));
    }
#endif

    float acc = 0.0f;
    for (uint64_t b = 0; b < blocks; b++) {
        uint16_t scale_bits;
        memcpy(&scale_bits, row + b * 34, sizeof(scale_bits));
        const int8_t *qs = (const int8_t *)(row + b * 34 + 2);

        const uint64_t i0 = b * 32;
        const uint64_t n = in_dim - i0 < 32 ? in_dim - i0 : 32;
        acc += f16_to_f32(scale_bits) * xscale[b] * (float)dot_i8_32(qs, xq + i0, n);
    }
    return acc;
}

static inline void dot_q8_0_row_2(
        const uint8_t *row,
        const int8_t  *xq0,
        const float   *xscale0,
        const int8_t  *xq1,
        const float   *xscale1,
        uint64_t       in_dim,
        uint64_t       blocks,
        float         *out0,
        float         *out1) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if ((in_dim & 31u) == 0) {
        float32x4_t acc00 = vdupq_n_f32(0.0f);
        float32x4_t acc01 = vdupq_n_f32(0.0f);
        float32x4_t acc10 = vdupq_n_f32(0.0f);
        float32x4_t acc11 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t scale_bits0;
```

<｜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
+ (b + 1) * 34, sizeof(scale_bits1));

            const int8_t *qs0 = (const int8_t *)(row + b * 34 + 2);
            const int8_t *qs1 = (const int8_t *)(row + (b + 1) * 34 + 2);
            const int8_t *xq0 = xq + b * 32;
            const int8_t *xq1 = xq + (b + 1) * 32;

            int32x4_t dot0 = vdupq_n_s32(0);
            dot0 = vdotq_s32(dot0, vld1q_s8(qs0),      vld1q_s8(xq0));
            dot0 = vdotq_s32(dot0, vld1q_s8(qs0 + 16), vld1q_s8(xq0 + 16));

            int32x4_t dot1 = vdupq_n_s32(0);
            dot1 = vdotq_s32(dot1, vld1q_s8(qs1),      vld1q_s8(xq1));
            dot1 = vdotq_s32(dot1, vld1q_s8(qs1 + 16), vld1q_s8(xq1 + 16));

            accv0 = vfmaq_n_f32(accv0, vcvtq_f32_s32(dot0), f16_to_f32(scale_bits0) * xscale[b]);
            accv1 = vfmaq_n_f32(accv1, vcvtq_f32_s32(dot1), f16_to_f32(scale_bits1) * xscale[b + 1]);
        }

        if (b < blocks) {
            uint16_t scale_bits;
            memcpy(&scale_bits, row + b * 34, sizeof(scale_bits));
            const int8_t *qs = (const int8_t *)(row + b * 34 + 2);
            const int8_t *xqb = xq + b * 32;
            int32x4_t dot = vdupq_n_s32(0);
            dot = vdotq_s32(dot, vld1q_s8(qs),      vld1q_s8(xqb));
            dot = vdotq_s32(dot, vld1q_s8(qs + 16), vld1q_s8(xqb + 16));
            accv0 = vfmaq_n_f32(accv0, vcvtq_f32_s32(dot), f16_to_f32(scale_bits) * xscale[b]);
        }

        return vaddvq_f32(vaddq_f32(accv0, accv1));
    }
#endif

    float acc = 0.0f;
    for (uint64_t b = 0; b < blocks; b++) {
        uint16_t scale_bits;
        memcpy(&scale_bits, row + b * 34, sizeof(scale_bits));
        const int8_t *qs = (const int8_t *)(row + b * 34 + 2);

        const uint64_t i0 = b * 32;
        const uint64_t n = in_dim - i0 < 32 ? in_dim - i0 : 32;
        acc += f16_to_f32(scale_bits) * xscale[b] * (float)dot_i8_32(qs, xq + i0, n);
    }
    return acc;
}

static inline void dot_q8_0_row_2(
        const uint8_t *row,
        const int8_t  *xq0,
        const float   *xscale0,
        const int8_t  *xq1,
        const float   *xscale1,
        uint64_t       in_dim,
        uint64_t       blocks,
        float         *out0,
        float         *out1) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if ((in_dim & 31u) == 0) {
        float32x4_t acc00 = vdupq_n_f32(0.0f);
        float32x4_t acc01 = vdupq_n_f32(0.0f);
        float32x4_t acc10 = vdupq_n_f32(0.0f);
        float32x4_t acc11 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t scale_bits0;
```<｜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
+ (b + 1) * 34, sizeof(scale_bits1));

            const int8_t *qs0 = (const int8_t *)(row + b * 34 + 2);
            const int8_t *qs1 = (const int8_t *)(row + (b + 1) * 34 + 2);
            const int8_t *xq0 = xq + b * 32;
            const int8_t *xq1 = xq + (b + 1) * 32;

            int32x4_t dot0 = vdupq_n_s32(0);
            dot0 = vdotq_s32(dot0, vld1q_s8(qs0),      vld1q_s8(xq0));
            dot0 = vdotq_s32(dot0, vld1q_s8(qs0 + 16), vld1q_s8(xq0 + 16));

            int32x4_t dot1 = vdupq_n_s32(0);
            dot1 = vdotq_s32(dot1, vld1q_s8(qs1),      vld1q_s8(xq1));
            dot1 = vdotq_s32(dot1, vld1q_s8(qs1 + 16), vld1q_s8(xq1 + 16));

            accv0 = vfmaq_n_f32(accv0, vcvtq_f32_s32(dot0), f16_to_f32(scale_bits0) * xscale[b]);
            accv1 = vfmaq_n_f32(accv1, vcvtq_f32_s32(dot1), f16_to_f32(scale_bits1) * xscale[b + 1]);
        }

        if (b < blocks) {
            uint16_t scale_bits;
            memcpy(&scale_bits, row + b * 34, sizeof(scale_bits));
            const int8_t *qs = (const int8_t *)(row + b * 34 + 2);
            const int8_t *xqb = xq + b * 32;
            int32x4_t dot = vdupq_n_s32(0);
            dot = vdotq_s32(dot, vld1q_s8(qs),      vld1q_s8(xqb));
            dot = vdotq_s32(dot, vld1q_s8(qs + 16), vld1q_s8(xqb + 16));
            accv0 = vfmaq_n_f32(accv0, vcvtq_f32_s32(dot), f16_to_f32(scale_bits) * xscale[b]);
        }

        return vaddvq_f32(vaddq_f32(accv0, accv1));
    }
#endif

    float acc = 0.0f;
    for (uint64_t b = 0; b < blocks; b++) {
        uint16_t scale_bits;
        memcpy(&scale_bits, row + b * 34, sizeof(scale_bits));
        const int8_t *qs = (const int8_t *)(row + b * 34 + 2);

        const uint64_t i0 = b * 32;
        const uint64_t n = in_dim - i0 < 32 ? in_dim - i0 : 32;
        acc += f16_to_f32(scale_bits) * xscale[b] * (float)dot_i8_32(qs, xq + i0, n);
    }
    return acc;
}

static inline void dot_q8_0_row_2(
        const uint8_t *row,
        const int8_t  *xq0,
        const float   *xscale0,
        const int8_t  *xq1,
        const float   *xscale1,
        uint64_t       in_dim,
        uint64_t       blocks,
        float         *out0,
        float         *out1) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if ((in_dim & 31u) == 0) {
        float32x4_t acc00 = vdupq_n_f32(0.0f);
        float32x4_t acc01 = vdupq_n_f32(0.0f);
        float32x4_t acc10 = vdupq_n_f32(0.0f);
        float32x4_t acc11 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t scale_bits0;
```

<｜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
+ (b + 1) * 34, sizeof(scale_bits1));

            const int8_t *qs0 = (const int8_t *)(row + b * 34 + 2);
            const int8_t *qs1 = (const int8_t *)(row + (b + 1) * 34 + 2);
            const int8_t *xq0 = xq + b * 32;
            const int8_t *xq1 = xq + (b + 1) * 32;

            int32x4_t dot0 = vdupq_n_s32(0);
            dot0 = vdotq_s32(dot0, vld1q_s8(qs0),      vld1q_s8(xq0));
            dot0 = vdotq_s32(dot0, vld1q_s8(qs0 + 16), vld1q_s8(xq0 + 16));

            int32x4_t dot1 = vdupq_n_s32(0);
            dot1 = vdotq_s32(dot1, vld1q_s8(qs1),      vld1q_s8(xq1));
            dot1 = vdotq_s32(dot1, vld1q_s8(qs1 + 16), vld1q_s8(xq1 + 16));

            accv0 = vfmaq_n_f32(accv0, vcvtq_f32_s32(dot0), f16_to_f32(scale_bits0) * xscale[b]);
            accv1 = vfmaq_n_f32(accv1, vcvtq_f32_s32(dot1), f16_to_f32(scale_bits1) * xscale[b + 1]);
        }

        if (b < blocks) {
            uint16_t scale_bits;
            memcpy(&scale_bits, row + b * 34, sizeof(scale_bits));
            const int8_t *qs = (const int8_t *)(row + b * 34 + 2);
            const int8_t *xqb = xq + b * 32;
            int32x4_t dot = vdupq_n_s32(0);
            dot = vdotq_s32(dot, vld1q_s8(qs),      vld1q_s8(xqb));
            dot = vdotq_s32(dot, vld1q_s8(qs + 16), vld1q_s8(xqb + 16));
            accv0 = vfmaq_n_f32(accv0, vcvtq_f32_s32(dot), f16_to_f32(scale_bits) * xscale[b]);
        }

        return vaddvq_f32(vaddq_f32(accv0, accv1));
    }
#endif

    float acc = 0.0f;
    for (uint64_t b = 0; b < blocks; b++) {
        uint16_t scale_bits;
        memcpy(&scale_bits, row + b * 34, sizeof(scale_bits));
        const int8_t *qs = (const int8_t *)(row + b * 34 + 2);

        const uint64_t i0 = b * 32;
        const uint64_t n = in_dim - i0 < 32 ? in_dim - i0 : 32;
        acc += f16_to_f32(scale_bits) * xscale[b] * (float)dot_i8_32(qs, xq + i0, n);
    }
    return acc;
}

static inline void dot_q8_0_row_2(
        const uint8_t *row,
        const int8_t  *xq0,
        const float   *xscale0,
        const int8_t  *xq1,
        const float   *xscale1,
        uint64_t       in_dim,
        uint64_t       blocks,
        float         *out0,
        float         *out1) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if ((in_dim & 31u) == 0) {
        float32x4_t acc00 = vdupq_n_f32(0.0f);
        float32x4_t acc01 = vdupq_n_f32(0.0f);
        float32x4_t acc10 = vdupq_n_f32(0.0f);
        float32x4_t acc11 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t scale_bits0;
```<｜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
32x4_t acc10 = vdupq_n_f32(0.0f);
        float32x4_t acc11 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t scale_bits0;
            uint16_t scale_bits1;
            memcpy(&scale_bits0, row + b * 34, sizeof(scale_bits0));
            memcpy(&scale_bits1, row + (b + 1) * 34, sizeof(scale_bits1));

            const int8_t *qs0 = (const int8_t *)(row + b * 34 + 2);
            const int8_t *qs1 = (const int8_t *)(row + (b + 1) * 34 + 2);

            int32x4_t d00 = vdupq_n_s32(0);
            d00 = vdotq_s32(d00, vld1q_s8(qs0),      vld1q_s8(xq0 + b * 32));
            d00 = vdotq_s32(d00, vld1q_s8(qs0 + 16), vld1q_s8(xq0 + b * 32 + 16));
            int32x4_t d01 = vdupq_n_s32(0);
            d01 = vdotq_s32(d01, vld1q_s8(qs1),      vld1q_s8(xq0 + (b + 1) * 32));
            d01 = vdotq_s32(d01, vld1q_s8(qs1 + 16), vld1q_s8(xq0 + (b + 1) * 32 + 16));

            int32x4_t d10 = vdupq_n_s32(0);
            d10 = vdotq_s32(d10, vld1q_s8(qs0),      vld1q_s8(xq1 + b * 32));
            d10 = vdotq_s32(d10, vld1q_s8(qs0 + 16), vld1q_s8(xq1 + b * 32 + 16));
            int32x4_t d11 = vdupq_n_s32(0);
            d11 = vdotq_s32(d11, vld1q_s8(qs1),      vld1q_s8(xq1 + (b + 1) * 32));
            d11 = vdotq_s32(d11, vld1q_s8(qs1 + 16), vld1q_s8(xq1 + (b + 1) * 32 + 16));

            const float s0 = f16_to_f32(scale_bits0);
            const float s1 = f16_to_f32(scale_bits1);
            acc00 = vfmaq_n_f32(acc00, vcvtq_f32_s32(d00), s0 * xscale0[b]);
            acc01 = vfmaq_n_f32(acc01, vcvtq_f32_s32(d01), s1 * xscale0[b + 1]);
            acc10 = vfmaq_n_f32(acc10, vcvtq_f32_s32(d10), s0 * xscale1[b]);
            acc11 = vfmaq_n_f32(acc11, vcvtq_f32_s32(d11), s1 * xscale1[b + 1]);
        }

        if (b < blocks) {
            uint16_t scale_bits;
            memcpy(&scale_bits, row + b * 34, sizeof(scale_bits));
            const int8_t *qs = (const int8_t *)(row + b * 34 + 2);

            int32x4_t d0 = vdupq_n_s32(0);
            d0 = vdotq_s32(d0, vld1q_s8(qs),      vld1q_s8(xq0 + b * 32));
            d0 = vdotq_s32(d0, vld1q_s8(qs + 16), vld1q_s8(xq0 + b * 32 + 16));
            int32x4_t d1 = vdupq_n_s32(0);
            d1 = vdotq_s32(d1, vld1q_s8(qs),      vld1q_s8(xq1 + b * 32));
            d1 = vdotq_s32(d1, vld1q_s8(qs + 16), vld1q_s8(xq1 + b * 32 + 16));

            const float s0 = f16_to_f32(scale_bits);
            acc00 = vfmaq_n_f32(acc00, vcvtq_f32_s32(d0), s0 * xscale0[b]);
            acc10 = vfmaq_n_f32(acc10, vcvtq_f32_s32(d1), s0 * xscale1[b]);
        }
```

<｜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
32x4_t acc10 = vdupq_n_f32(0.0f);
        float32x4_t acc11 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t scale_bits0;
            uint16_t scale_bits1;
            memcpy(&scale_bits0, row + b * 34, sizeof(scale_bits0));
            memcpy(&scale_bits1, row + (b + 1) * 34, sizeof(scale_bits1));

            const int8_t *qs0 = (const int8_t *)(row + b * 34 + 2);
            const int8_t *qs1 = (const int8_t *)(row + (b + 1) * 34 + 2);

            int32x4_t d00 = vdupq_n_s32(0);
            d00 = vdotq_s32(d00, vld1q_s8(qs0),      vld1q_s8(xq0 + b * 32));
            d00 = vdotq_s32(d00, vld1q_s8(qs0 + 16), vld1q_s8(xq0 + b * 32 + 16));
            int32x4_t d01 = vdupq_n_s32(0);
            d01 = vdotq_s32(d01, vld1q_s8(qs1),      vld1q_s8(xq0 + (b + 1) * 32));
            d01 = vdotq_s32(d01, vld1q_s8(qs1 + 16), vld1q_s8(xq0 + (b + 1) * 32 + 16));

            int32x4_t d10 = vdupq_n_s32(0);
            d10 = vdotq_s32(d10, vld1q_s8(qs0),      vld1q_s8(xq1 + b * 32));
            d10 = vdotq_s32(d10, vld1q_s8(qs0 + 16), vld1q_s8(xq1 + b * 32 + 16));
            int32x4_t d11 = vdupq_n_s32(0);
            d11 = vdotq_s32(d11, vld1q_s8(qs1),      vld1q_s8(xq1 + (b + 1) * 32));
            d11 = vdotq_s32(d11, vld1q_s8(qs1 + 16), vld1q_s8(xq1 + (b + 1) * 32 + 16));

            const float s0 = f16_to_f32(scale_bits0);
            const float s1 = f16_to_f32(scale_bits1);
            acc00 = vfmaq_n_f32(acc00, vcvtq_f32_s32(d00), s0 * xscale0[b]);
            acc01 = vfmaq_n_f32(acc01, vcvtq_f32_s32(d01), s1 * xscale0[b + 1]);
            acc10 = vfmaq_n_f32(acc10, vcvtq_f32_s32(d10), s0 * xscale1[b]);
            acc11 = vfmaq_n_f32(acc11, vcvtq_f32_s32(d11), s1 * xscale1[b + 1]);
        }

        if (b < blocks) {
            uint16_t scale_bits;
            memcpy(&scale_bits, row + b * 34, sizeof(scale_bits));
            const int8_t *qs = (const int8_t *)(row + b * 34 + 2);

            int32x4_t d0 = vdupq_n_s32(0);
            d0 = vdotq_s32(d0, vld1q_s8(qs),      vld1q_s8(xq0 + b * 32));
            d0 = vdotq_s32(d0, vld1q_s8(qs + 16), vld1q_s8(xq0 + b * 32 + 16));
            int32x4_t d1 = vdupq_n_s32(0);
            d1 = vdotq_s32(d1, vld1q_s8(qs),      vld1q_s8(xq1 + b * 32));
            d1 = vdotq_s32(d1, vld1q_s8(qs + 16), vld1q_s8(xq1 + b * 32 + 16));

            const float s0 = f16_to_f32(scale_bits);
            acc00 = vfmaq_n_f32(acc00, vcvtq_f32_s32(d0), s0 * xscale0[b]);
            acc10 = vfmaq_n_f32(acc10, vcvtq_f32_s32(d1), s0 * xscale1[b]);
        }
```<｜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
32x4_t acc10 = vdupq_n_f32(0.0f);
        float32x4_t acc11 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t scale_bits0;
            uint16_t scale_bits1;
            memcpy(&scale_bits0, row + b * 34, sizeof(scale_bits0));
            memcpy(&scale_bits1, row + (b + 1) * 34, sizeof(scale_bits1));

            const int8_t *qs0 = (const int8_t *)(row + b * 34 + 2);
            const int8_t *qs1 = (const int8_t *)(row + (b + 1) * 34 + 2);

            int32x4_t d00 = vdupq_n_s32(0);
            d00 = vdotq_s32(d00, vld1q_s8(qs0),      vld1q_s8(xq0 + b * 32));
            d00 = vdotq_s32(d00, vld1q_s8(qs0 + 16), vld1q_s8(xq0 + b * 32 + 16));
            int32x4_t d01 = vdupq_n_s32(0);
            d01 = vdotq_s32(d01, vld1q_s8(qs1),      vld1q_s8(xq0 + (b + 1) * 32));
            d01 = vdotq_s32(d01, vld1q_s8(qs1 + 16), vld1q_s8(xq0 + (b + 1) * 32 + 16));

            int32x4_t d10 = vdupq_n_s32(0);
            d10 = vdotq_s32(d10, vld1q_s8(qs0),      vld1q_s8(xq1 + b * 32));
            d10 = vdotq_s32(d10, vld1q_s8(qs0 + 16), vld1q_s8(xq1 + b * 32 + 16));
            int32x4_t d11 = vdupq_n_s32(0);
            d11 = vdotq_s32(d11, vld1q_s8(qs1),      vld1q_s8(xq1 + (b + 1) * 32));
            d11 = vdotq_s32(d11, vld1q_s8(qs1 + 16), vld1q_s8(xq1 + (b + 1) * 32 + 16));

            const float s0 = f16_to_f32(scale_bits0);
            const float s1 = f16_to_f32(scale_bits1);
            acc00 = vfmaq_n_f32(acc00, vcvtq_f32_s32(d00), s0 * xscale0[b]);
            acc01 = vfmaq_n_f32(acc01, vcvtq_f32_s32(d01), s1 * xscale0[b + 1]);
            acc10 = vfmaq_n_f32(acc10, vcvtq_f32_s32(d10), s0 * xscale1[b]);
            acc11 = vfmaq_n_f32(acc11, vcvtq_f32_s32(d11), s1 * xscale1[b + 1]);
        }

        if (b < blocks) {
            uint16_t scale_bits;
            memcpy(&scale_bits, row + b * 34, sizeof(scale_bits));
            const int8_t *qs = (const int8_t *)(row + b * 34 + 2);

            int32x4_t d0 = vdupq_n_s32(0);
            d0 = vdotq_s32(d0, vld1q_s8(qs),      vld1q_s8(xq0 + b * 32));
            d0 = vdotq_s32(d0, vld1q_s8(qs + 16), vld1q_s8(xq0 + b * 32 + 16));
            int32x4_t d1 = vdupq_n_s32(0);
            d1 = vdotq_s32(d1, vld1q_s8(qs),      vld1q_s8(xq1 + b * 32));
            d1 = vdotq_s32(d1, vld1q_s8(qs + 16), vld1q_s8(xq1 + b * 32 + 16));

            const float s0 = f16_to_f32(scale_bits);
            acc00 = vfmaq_n_f32(acc00, vcvtq_f32_s32(d0), s0 * xscale0[b]);
            acc10 = vfmaq_n_f32(acc10, vcvtq_f32_s32(d1), s0 * xscale1[b]);
        }
```

<｜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
32x4_t acc10 = vdupq_n_f32(0.0f);
        float32x4_t acc11 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t scale_bits0;
            uint16_t scale_bits1;
            memcpy(&scale_bits0, row + b * 34, sizeof(scale_bits0));
            memcpy(&scale_bits1, row + (b + 1) * 34, sizeof(scale_bits1));

            const int8_t *qs0 = (const int8_t *)(row + b * 34 + 2);
            const int8_t *qs1 = (const int8_t *)(row + (b + 1) * 34 + 2);

            int32x4_t d00 = vdupq_n_s32(0);
            d00 = vdotq_s32(d00, vld1q_s8(qs0),      vld1q_s8(xq0 + b * 32));
            d00 = vdotq_s32(d00, vld1q_s8(qs0 + 16), vld1q_s8(xq0 + b * 32 + 16));
            int32x4_t d01 = vdupq_n_s32(0);
            d01 = vdotq_s32(d01, vld1q_s8(qs1),      vld1q_s8(xq0 + (b + 1) * 32));
            d01 = vdotq_s32(d01, vld1q_s8(qs1 + 16), vld1q_s8(xq0 + (b + 1) * 32 + 16));

            int32x4_t d10 = vdupq_n_s32(0);
            d10 = vdotq_s32(d10, vld1q_s8(qs0),      vld1q_s8(xq1 + b * 32));
            d10 = vdotq_s32(d10, vld1q_s8(qs0 + 16), vld1q_s8(xq1 + b * 32 + 16));
            int32x4_t d11 = vdupq_n_s32(0);
            d11 = vdotq_s32(d11, vld1q_s8(qs1),      vld1q_s8(xq1 + (b + 1) * 32));
            d11 = vdotq_s32(d11, vld1q_s8(qs1 + 16), vld1q_s8(xq1 + (b + 1) * 32 + 16));

            const float s0 = f16_to_f32(scale_bits0);
            const float s1 = f16_to_f32(scale_bits1);
            acc00 = vfmaq_n_f32(acc00, vcvtq_f32_s32(d00), s0 * xscale0[b]);
            acc01 = vfmaq_n_f32(acc01, vcvtq_f32_s32(d01), s1 * xscale0[b + 1]);
            acc10 = vfmaq_n_f32(acc10, vcvtq_f32_s32(d10), s0 * xscale1[b]);
            acc11 = vfmaq_n_f32(acc11, vcvtq_f32_s32(d11), s1 * xscale1[b + 1]);
        }

        if (b < blocks) {
            uint16_t scale_bits;
            memcpy(&scale_bits, row + b * 34, sizeof(scale_bits));
            const int8_t *qs = (const int8_t *)(row + b * 34 + 2);

            int32x4_t d0 = vdupq_n_s32(0);
            d0 = vdotq_s32(d0, vld1q_s8(qs),      vld1q_s8(xq0 + b * 32));
            d0 = vdotq_s32(d0, vld1q_s8(qs + 16), vld1q_s8(xq0 + b * 32 + 16));
            int32x4_t d1 = vdupq_n_s32(0);
            d1 = vdotq_s32(d1, vld1q_s8(qs),      vld1q_s8(xq1 + b * 32));
            d1 = vdotq_s32(d1, vld1q_s8(qs + 16), vld1q_s8(xq1 + b * 32 + 16));

            const float s0 = f16_to_f32(scale_bits);
            acc00 = vfmaq_n_f32(acc00, vcvtq_f32_s32(d0), s0 * xscale0[b]);
            acc10 = vfmaq_n_f32(acc10, vcvtq_f32_s32(d1), s0 * xscale1[b]);
        }
```<｜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
_f32(scale_bits);
            acc00 = vfmaq_n_f32(acc00, vcvtq_f32_s32(d0), s0 * xscale0[b]);
            acc10 = vfmaq_n_f32(acc10, vcvtq_f32_s32(d1), s0 * xscale1[b]);
        }

        *out0 = vaddvq_f32(vaddq_f32(acc00, acc01));
        *out1 = vaddvq_f32(vaddq_f32(acc10, acc11));
        return;
    }
#endif

    *out0 = dot_q8_0_row(row, xq0, xscale0, in_dim, blocks);
    *out1 = dot_q8_0_row(row, xq1, xscale1, in_dim, blocks);
}

static inline DS4_MAYBE_UNUSED void dot_q8_0_row_pair(
        const uint8_t *row0,
        const uint8_t *row1,
        const int8_t  *xq,
        const float   *xscale,
        uint64_t       in_dim,
        uint64_t       blocks,
        float         *out0,
        float         *out1) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if ((in_dim & 31u) == 0) {
        float32x4_t acc00 = vdupq_n_f32(0.0f);
        float32x4_t acc01 = vdupq_n_f32(0.0f);
        float32x4_t acc10 = vdupq_n_f32(0.0f);
        float32x4_t acc11 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t s00, s01, s10, s11;
            memcpy(&s00, row0 + b * 34, sizeof(s00));
            memcpy(&s01, row0 + (b + 1) * 34, sizeof(s01));
            memcpy(&s10, row1 + b * 34, sizeof(s10));
            memcpy(&s11, row1 + (b + 1) * 34, sizeof(s11));

            const int8_t *xq0 = xq + b * 32;
            const int8_t *xq1 = xq + (b + 1) * 32;
            const int8x16_t xv00 = vld1q_s8(xq0);
            const int8x16_t xv01 = vld1q_s8(xq0 + 16);
            const int8x16_t xv10 = vld1q_s8(xq1);
            const int8x16_t xv11 = vld1q_s8(xq1 + 16);

            const int8_t *q00 = (const int8_t *)(row0 + b * 34 + 2);
            const int8_t *q01 = (const int8_t *)(row0 + (b + 1) * 34 + 2);
            const int8_t *q10 = (const int8_t *)(row1 + b * 34 + 2);
            const int8_t *q11 = (const int8_t *)(row1 + (b + 1) * 34 + 2);

            int32x4_t d00 = vdupq_n_s32(0);
            d00 = vdotq_s32(d00, vld1q_s8(q00),      xv00);
            d00 = vdotq_s32(d00, vld1q_s8(q00 + 16), xv01);
            int32x4_t d01 = vdupq_n_s32(0);
            d01 = vdotq_s32(d01, vld1q_s8(q01),      xv10);
            d01 = vdotq_s32(d01, vld1q_s8(q01 + 16), xv11);
            int32x4_t d10 = vdupq_n_s32(0);
            d10 = vdotq_s32(d10, vld1q_s8(q10),      xv00);
            d10 = vdotq_s32(d10, vld1q_s8(q10 + 16), xv01);
            int32x4_t d11 = vdupq_n_s32(0);
            d11 = vdotq_s32(d11, vld1q_s8(q11),      xv10);
            d11 = vdotq_s32(d11, vld1q_s8(q11 + 16), xv11);
```

<｜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
_f32(scale_bits);
            acc00 = vfmaq_n_f32(acc00, vcvtq_f32_s32(d0), s0 * xscale0[b]);
            acc10 = vfmaq_n_f32(acc10, vcvtq_f32_s32(d1), s0 * xscale1[b]);
        }

        *out0 = vaddvq_f32(vaddq_f32(acc00, acc01));
        *out1 = vaddvq_f32(vaddq_f32(acc10, acc11));
        return;
    }
#endif

    *out0 = dot_q8_0_row(row, xq0, xscale0, in_dim, blocks);
    *out1 = dot_q8_0_row(row, xq1, xscale1, in_dim, blocks);
}

static inline DS4_MAYBE_UNUSED void dot_q8_0_row_pair(
        const uint8_t *row0,
        const uint8_t *row1,
        const int8_t  *xq,
        const float   *xscale,
        uint64_t       in_dim,
        uint64_t       blocks,
        float         *out0,
        float         *out1) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if ((in_dim & 31u) == 0) {
        float32x4_t acc00 = vdupq_n_f32(0.0f);
        float32x4_t acc01 = vdupq_n_f32(0.0f);
        float32x4_t acc10 = vdupq_n_f32(0.0f);
        float32x4_t acc11 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t s00, s01, s10, s11;
            memcpy(&s00, row0 + b * 34, sizeof(s00));
            memcpy(&s01, row0 + (b + 1) * 34, sizeof(s01));
            memcpy(&s10, row1 + b * 34, sizeof(s10));
            memcpy(&s11, row1 + (b + 1) * 34, sizeof(s11));

            const int8_t *xq0 = xq + b * 32;
            const int8_t *xq1 = xq + (b + 1) * 32;
            const int8x16_t xv00 = vld1q_s8(xq0);
            const int8x16_t xv01 = vld1q_s8(xq0 + 16);
            const int8x16_t xv10 = vld1q_s8(xq1);
            const int8x16_t xv11 = vld1q_s8(xq1 + 16);

            const int8_t *q00 = (const int8_t *)(row0 + b * 34 + 2);
            const int8_t *q01 = (const int8_t *)(row0 + (b + 1) * 34 + 2);
            const int8_t *q10 = (const int8_t *)(row1 + b * 34 + 2);
            const int8_t *q11 = (const int8_t *)(row1 + (b + 1) * 34 + 2);

            int32x4_t d00 = vdupq_n_s32(0);
            d00 = vdotq_s32(d00, vld1q_s8(q00),      xv00);
            d00 = vdotq_s32(d00, vld1q_s8(q00 + 16), xv01);
            int32x4_t d01 = vdupq_n_s32(0);
            d01 = vdotq_s32(d01, vld1q_s8(q01),      xv10);
            d01 = vdotq_s32(d01, vld1q_s8(q01 + 16), xv11);
            int32x4_t d10 = vdupq_n_s32(0);
            d10 = vdotq_s32(d10, vld1q_s8(q10),      xv00);
            d10 = vdotq_s32(d10, vld1q_s8(q10 + 16), xv01);
            int32x4_t d11 = vdupq_n_s32(0);
            d11 = vdotq_s32(d11, vld1q_s8(q11),      xv10);
            d11 = vdotq_s32(d11, vld1q_s8(q11 + 16), xv11);
```<｜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
_f32(scale_bits);
            acc00 = vfmaq_n_f32(acc00, vcvtq_f32_s32(d0), s0 * xscale0[b]);
            acc10 = vfmaq_n_f32(acc10, vcvtq_f32_s32(d1), s0 * xscale1[b]);
        }

        *out0 = vaddvq_f32(vaddq_f32(acc00, acc01));
        *out1 = vaddvq_f32(vaddq_f32(acc10, acc11));
        return;
    }
#endif

    *out0 = dot_q8_0_row(row, xq0, xscale0, in_dim, blocks);
    *out1 = dot_q8_0_row(row, xq1, xscale1, in_dim, blocks);
}

static inline DS4_MAYBE_UNUSED void dot_q8_0_row_pair(
        const uint8_t *row0,
        const uint8_t *row1,
        const int8_t  *xq,
        const float   *xscale,
        uint64_t       in_dim,
        uint64_t       blocks,
        float         *out0,
        float         *out1) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if ((in_dim & 31u) == 0) {
        float32x4_t acc00 = vdupq_n_f32(0.0f);
        float32x4_t acc01 = vdupq_n_f32(0.0f);
        float32x4_t acc10 = vdupq_n_f32(0.0f);
        float32x4_t acc11 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t s00, s01, s10, s11;
            memcpy(&s00, row0 + b * 34, sizeof(s00));
            memcpy(&s01, row0 + (b + 1) * 34, sizeof(s01));
            memcpy(&s10, row1 + b * 34, sizeof(s10));
            memcpy(&s11, row1 + (b + 1) * 34, sizeof(s11));

            const int8_t *xq0 = xq + b * 32;
            const int8_t *xq1 = xq + (b + 1) * 32;
            const int8x16_t xv00 = vld1q_s8(xq0);
            const int8x16_t xv01 = vld1q_s8(xq0 + 16);
            const int8x16_t xv10 = vld1q_s8(xq1);
            const int8x16_t xv11 = vld1q_s8(xq1 + 16);

            const int8_t *q00 = (const int8_t *)(row0 + b * 34 + 2);
            const int8_t *q01 = (const int8_t *)(row0 + (b + 1) * 34 + 2);
            const int8_t *q10 = (const int8_t *)(row1 + b * 34 + 2);
            const int8_t *q11 = (const int8_t *)(row1 + (b + 1) * 34 + 2);

            int32x4_t d00 = vdupq_n_s32(0);
            d00 = vdotq_s32(d00, vld1q_s8(q00),      xv00);
            d00 = vdotq_s32(d00, vld1q_s8(q00 + 16), xv01);
            int32x4_t d01 = vdupq_n_s32(0);
            d01 = vdotq_s32(d01, vld1q_s8(q01),      xv10);
            d01 = vdotq_s32(d01, vld1q_s8(q01 + 16), xv11);
            int32x4_t d10 = vdupq_n_s32(0);
            d10 = vdotq_s32(d10, vld1q_s8(q10),      xv00);
            d10 = vdotq_s32(d10, vld1q_s8(q10 + 16), xv01);
            int32x4_t d11 = vdupq_n_s32(0);
            d11 = vdotq_s32(d11, vld1q_s8(q11),      xv10);
            d11 = vdotq_s32(d11, vld1q_s8(q11 + 16), xv11);
```

<｜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
_f32(scale_bits);
            acc00 = vfmaq_n_f32(acc00, vcvtq_f32_s32(d0), s0 * xscale0[b]);
            acc10 = vfmaq_n_f32(acc10, vcvtq_f32_s32(d1), s0 * xscale1[b]);
        }

        *out0 = vaddvq_f32(vaddq_f32(acc00, acc01));
        *out1 = vaddvq_f32(vaddq_f32(acc10, acc11));
        return;
    }
#endif

    *out0 = dot_q8_0_row(row, xq0, xscale0, in_dim, blocks);
    *out1 = dot_q8_0_row(row, xq1, xscale1, in_dim, blocks);
}

static inline DS4_MAYBE_UNUSED void dot_q8_0_row_pair(
        const uint8_t *row0,
        const uint8_t *row1,
        const int8_t  *xq,
        const float   *xscale,
        uint64_t       in_dim,
        uint64_t       blocks,
        float         *out0,
        float         *out1) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    if ((in_dim & 31u) == 0) {
        float32x4_t acc00 = vdupq_n_f32(0.0f);
        float32x4_t acc01 = vdupq_n_f32(0.0f);
        float32x4_t acc10 = vdupq_n_f32(0.0f);
        float32x4_t acc11 = vdupq_n_f32(0.0f);

        uint64_t b = 0;
        for (; b + 1 < blocks; b += 2) {
            uint16_t s00, s01, s10, s11;
            memcpy(&s00, row0 + b * 34, sizeof(s00));
            memcpy(&s01, row0 + (b + 1) * 34, sizeof(s01));
            memcpy(&s10, row1 + b * 34, sizeof(s10));
            memcpy(&s11, row1 + (b + 1) * 34, sizeof(s11));

            const int8_t *xq0 = xq + b * 32;
            const int8_t *xq1 = xq + (b + 1) * 32;
            const int8x16_t xv00 = vld1q_s8(xq0);
            const int8x16_t xv01 = vld1q_s8(xq0 + 16);
            const int8x16_t xv10 = vld1q_s8(xq1);
            const int8x16_t xv11 = vld1q_s8(xq1 + 16);

            const int8_t *q00 = (const int8_t *)(row0 + b * 34 + 2);
            const int8_t *q01 = (const int8_t *)(row0 + (b + 1) * 34 + 2);
            const int8_t *q10 = (const int8_t *)(row1 + b * 34 + 2);
            const int8_t *q11 = (const int8_t *)(row1 + (b + 1) * 34 + 2);

            int32x4_t d00 = vdupq_n_s32(0);
            d00 = vdotq_s32(d00, vld1q_s8(q00),      xv00);
            d00 = vdotq_s32(d00, vld1q_s8(q00 + 16), xv01);
            int32x4_t d01 = vdupq_n_s32(0);
            d01 = vdotq_s32(d01, vld1q_s8(q01),      xv10);
            d01 = vdotq_s32(d01, vld1q_s8(q01 + 16), xv11);
            int32x4_t d10 = vdupq_n_s32(0);
            d10 = vdotq_s32(d10, vld1q_s8(q10),      xv00);
            d10 = vdotq_s32(d10, vld1q_s8(q10 + 16), xv01);
            int32x4_t d11 = vdupq_n_s32(0);
            d11 = vdotq_s32(d11, vld1q_s8(q11),      xv10);
            d11 = vdotq_s32(d11, vld1q_s8(q11 + 16), xv11);
```<｜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
81908081908,
    0x2b08081908192b08, 0x2b08081919080808, 0x2b08082b08190819, 0x2b08190808080819,
    0x2b08190808081908, 0x2b08190808190808, 0x2b08190808191919, 0x2b08190819080808,
    0x2b081908192b0808, 0x2b08191908080808, 0x2b0819191908192b, 0x2b0819192b191908,
    0x2b08192b08082b19, 0x2b08192b19080808, 0x2b08192b192b0808, 0x2b082b080808082b,
    0x2b082b1908081908, 0x2b082b2b08190819, 0x2b19080808081908, 0x2b19080808190808,
    0x2b190808082b1908, 0x2b19080819080808, 0x2b1908082b2b0819, 0x2b1908190819192b,
    0x2b1908192b080808, 0x2b19082b19081919, 0x2b19190808080808, 0x2b191908082b082b,
    0x2b19190819081908, 0x2b19191919190819, 0x2b192b082b080819, 0x2b192b19082b0808,
    0x2b2b08080808082b, 0x2b2b080819190808, 0x2b2b08082b081919, 0x2b2b081908082b19,
    0x2b2b082b08080808, 0x2b2b190808192b08, 0x2b2b2b0819190808, 0x2b2b2b1908081908,
};

static int8_t iq2xxs_signed_grid[256][128][8];
static int8_t iq2xxs_signs[128][8];
static pthread_once_t iq2xxs_signed_grid_once = PTHREAD_ONCE_INIT;

static void iq2xxs_signed_grid_init(void) {
    for (uint32_t s = 0; s < 128; s++) {
        const uint8_t signs = ksigns_iq2xs[s];
        for (uint32_t j = 0; j < 8; j++) {
            iq2xxs_signs[s][j] = (int8_t)((signs & kmask_iq2xs[j]) ? -1 : 1);
        }
    }

    for (uint32_t g = 0; g < 256; g++) {
        const uint8_t *grid = (const uint8_t *)(iq2xxs_grid + g);
        for (uint32_t s = 0; s < 128; s++) {
            const uint8_t signs = ksigns_iq2xs[s];
            for (uint32_t j = 0; j < 8; j++) {
                const int v = (int)grid[j];
                iq2xxs_signed_grid[g][s][j] = (int8_t)((signs & kmask_iq2xs[j]) ? -v : v);
            }
        }
    }
}

static inline DS4_MAYBE_UNUSED int32_t dot_iq2_pair_16(const int8_t *grid0, const int8_t *grid1, const int8_t *q8) {
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
    const int8x16_t gv = vcombine_s8(vld1_s8(grid0), vld1_s8(grid1));
    const int32x4_t acc = vdotq_s32(vdupq_n_s32(0), gv, vld1q_s8(q8));
    return vaddvq_s32(acc);
#elif defined(__ARM_NEON)
    const int8x16_t gv = vcombine_s8(vld1_s8(grid0), vld1_s8(grid1));
    const int8x16_t qv = vld1q_s8(q8);
    const int16x8_t p0 = vmull_s8(vget_low_s8(gv), vget_low_s8(qv));
    const int16x8_t p1 = vmull_s8(vget_high_s8(gv), vget_high_s8(qv));
    return vaddvq_s32(vaddq_s32(vpaddlq_s16(p0), vpaddlq_s16(p1)));
#else
    int32_t sum = 0;
    for (uint32_t i = 0; i < 8; i++) sum += (int32_t)grid0[i] * (int32_t)q8[i];
    for (uint32_t i = 0; i < 8; i++) sum += (int32_t)grid1[i] * (int32_t)q8[8 + i];
    return sum;
#endif
}
```