[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: metal/set_rows.metal

```metal
// DS4 Metal set-rows kernel used for KV writes.

struct ds4_metal_args_set_rows {
    int32_t  nk0;
    int32_t  ne01;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int32_t  ne11;
    int32_t  ne12;
    uint64_t nb10;
    uint64_t nb11;
    uint64_t nb12;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
};

// Scatters rows into the KV cache by token position. DS4 uses this after Q/K/V
// preparation so decode and later prefill chunks can attend to previous tokens.
template<typename T, typename TI>
kernel void kernel_set_rows_f(
        constant ds4_metal_args_set_rows & args,
        device const char  * src0,
        device const char  * src1,
        device       float * dst,
        uint3                tgpig[[threadgroup_position_in_grid]],
        uint                 tiitg[[thread_index_in_threadgroup]],
        uint3                tptg [[threads_per_threadgroup]]) {
    const int32_t i03 = tgpig.z;
    const int32_t i02 = tgpig.y;

    const int32_t i12 = i03%args.ne12;
    const int32_t i11 = i02%args.ne11;

    const int32_t i01 = tgpig.x*tptg.y + tiitg/tptg.x;
    if (i01 >= args.ne01) {
        return;
    }

    const int32_t i10 = i01;
    const TI      i1  = ((const device TI *) (src1 + i10*args.nb10 + i11*args.nb11 + i12*args.nb12))[0];

          device T     * dst_row = (      device T     *) ((device char *) dst  + i1*args.nb1   + i02*args.nb2  + i03*args.nb3);
    const device float * src_row = (const device float *) (                src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);

    for (int ind = tiitg%tptg.x; ind < args.nk0; ind += tptg.x) {
        dst_row[ind] = (T) src_row[ind];
    }
}

typedef decltype(kernel_set_rows_f<float, int64_t>) set_rows_f_t;

// Host-visible F32/I32 scatter variant used by KV-cache writes.
template [[host_name("kernel_set_rows_f32_i32")]] kernel set_rows_f_t kernel_set_rows_f<float, int32_t>;
```

<｜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: metal/set_rows.metal

```metal
// DS4 Metal set-rows kernel used for KV writes.

struct ds4_metal_args_set_rows {
    int32_t  nk0;
    int32_t  ne01;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int32_t  ne11;
    int32_t  ne12;
    uint64_t nb10;
    uint64_t nb11;
    uint64_t nb12;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
};

// Scatters rows into the KV cache by token position. DS4 uses this after Q/K/V
// preparation so decode and later prefill chunks can attend to previous tokens.
template<typename T, typename TI>
kernel void kernel_set_rows_f(
        constant ds4_metal_args_set_rows & args,
        device const char  * src0,
        device const char  * src1,
        device       float * dst,
        uint3                tgpig[[threadgroup_position_in_grid]],
        uint                 tiitg[[thread_index_in_threadgroup]],
        uint3                tptg [[threads_per_threadgroup]]) {
    const int32_t i03 = tgpig.z;
    const int32_t i02 = tgpig.y;

    const int32_t i12 = i03%args.ne12;
    const int32_t i11 = i02%args.ne11;

    const int32_t i01 = tgpig.x*tptg.y + tiitg/tptg.x;
    if (i01 >= args.ne01) {
        return;
    }

    const int32_t i10 = i01;
    const TI      i1  = ((const device TI *) (src1 + i10*args.nb10 + i11*args.nb11 + i12*args.nb12))[0];

          device T     * dst_row = (      device T     *) ((device char *) dst  + i1*args.nb1   + i02*args.nb2  + i03*args.nb3);
    const device float * src_row = (const device float *) (                src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);

    for (int ind = tiitg%tptg.x; ind < args.nk0; ind += tptg.x) {
        dst_row[ind] = (T) src_row[ind];
    }
}

typedef decltype(kernel_set_rows_f<float, int64_t>) set_rows_f_t;

// Host-visible F32/I32 scatter variant used by KV-cache writes.
template [[host_name("kernel_set_rows_f32_i32")]] kernel set_rows_f_t kernel_set_rows_f<float, int32_t>;
```<｜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: metal/set_rows.metal

```metal
// DS4 Metal set-rows kernel used for KV writes.

struct ds4_metal_args_set_rows {
    int32_t  nk0;
    int32_t  ne01;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int32_t  ne11;
    int32_t  ne12;
    uint64_t nb10;
    uint64_t nb11;
    uint64_t nb12;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
};

// Scatters rows into the KV cache by token position. DS4 uses this after Q/K/V
// preparation so decode and later prefill chunks can attend to previous tokens.
template<typename T, typename TI>
kernel void kernel_set_rows_f(
        constant ds4_metal_args_set_rows & args,
        device const char  * src0,
        device const char  * src1,
        device       float * dst,
        uint3                tgpig[[threadgroup_position_in_grid]],
        uint                 tiitg[[thread_index_in_threadgroup]],
        uint3                tptg [[threads_per_threadgroup]]) {
    const int32_t i03 = tgpig.z;
    const int32_t i02 = tgpig.y;

    const int32_t i12 = i03%args.ne12;
    const int32_t i11 = i02%args.ne11;

    const int32_t i01 = tgpig.x*tptg.y + tiitg/tptg.x;
    if (i01 >= args.ne01) {
        return;
    }

    const int32_t i10 = i01;
    const TI      i1  = ((const device TI *) (src1 + i10*args.nb10 + i11*args.nb11 + i12*args.nb12))[0];

          device T     * dst_row = (      device T     *) ((device char *) dst  + i1*args.nb1   + i02*args.nb2  + i03*args.nb3);
    const device float * src_row = (const device float *) (                src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);

    for (int ind = tiitg%tptg.x; ind < args.nk0; ind += tptg.x) {
        dst_row[ind] = (T) src_row[ind];
    }
}

typedef decltype(kernel_set_rows_f<float, int64_t>) set_rows_f_t;

// Host-visible F32/I32 scatter variant used by KV-cache writes.
template [[host_name("kernel_set_rows_f32_i32")]] kernel set_rows_f_t kernel_set_rows_f<float, int32_t>;
```

<｜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: metal/set_rows.metal

```metal
// DS4 Metal set-rows kernel used for KV writes.

struct ds4_metal_args_set_rows {
    int32_t  nk0;
    int32_t  ne01;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int32_t  ne11;
    int32_t  ne12;
    uint64_t nb10;
    uint64_t nb11;
    uint64_t nb12;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
};

// Scatters rows into the KV cache by token position. DS4 uses this after Q/K/V
// preparation so decode and later prefill chunks can attend to previous tokens.
template<typename T, typename TI>
kernel void kernel_set_rows_f(
        constant ds4_metal_args_set_rows & args,
        device const char  * src0,
        device const char  * src1,
        device       float * dst,
        uint3                tgpig[[threadgroup_position_in_grid]],
        uint                 tiitg[[thread_index_in_threadgroup]],
        uint3                tptg [[threads_per_threadgroup]]) {
    const int32_t i03 = tgpig.z;
    const int32_t i02 = tgpig.y;

    const int32_t i12 = i03%args.ne12;
    const int32_t i11 = i02%args.ne11;

    const int32_t i01 = tgpig.x*tptg.y + tiitg/tptg.x;
    if (i01 >= args.ne01) {
        return;
    }

    const int32_t i10 = i01;
    const TI      i1  = ((const device TI *) (src1 + i10*args.nb10 + i11*args.nb11 + i12*args.nb12))[0];

          device T     * dst_row = (      device T     *) ((device char *) dst  + i1*args.nb1   + i02*args.nb2  + i03*args.nb3);
    const device float * src_row = (const device float *) (                src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);

    for (int ind = tiitg%tptg.x; ind < args.nk0; ind += tptg.x) {
        dst_row[ind] = (T) src_row[ind];
    }
}

typedef decltype(kernel_set_rows_f<float, int64_t>) set_rows_f_t;

// Host-visible F32/I32 scatter variant used by KV-cache writes.
template [[host_name("kernel_set_rows_f32_i32")]] kernel set_rows_f_t kernel_set_rows_f<float, int32_t>;
```<｜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: metal/softmax.metal

```metal
// DS4 Metal softmax kernel used by the compressor pooling compatibility path.
// The single-compressed-row path is intentionally left as soft_max -> mul ->
// sum_rows instead of using the fused dsv4_softmax_pool kernel.

struct ds4_metal_args_soft_max {
    int32_t  ne00;
    int32_t  ne01;
    int32_t  ne02;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int32_t  ne11;
    int32_t  ne12;
    int32_t  ne13;
    uint64_t nb11;
    uint64_t nb12;
    uint64_t nb13;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
    float    scale;
    float    max_bias;
    float    m0;
    float    m1;
    int32_t  n_head_log2;
};

// Row softmax for score matrices. DS4 uses it in the literal one-compressor-row
// path where preserving the original graph operation boundary avoids drift.
template<typename T>
kernel void kernel_soft_max(
        constant ds4_metal_args_soft_max & args,
        device const  char * src0,
        device const  char * src1,
        device const  char * src2,
        device        char * dst,
        threadgroup  float * buf [[threadgroup(0)]],
        uint3 tgpig[[threadgroup_position_in_grid]],
        uint3 tpitg[[thread_position_in_threadgroup]],
        uint  sgitg[[simdgroup_index_in_threadgroup]],
        uint  tiisg[[thread_index_in_simdgroup]],
        uint3  tptg[[threads_per_threadgroup]]) {
    const int32_t i03 = tgpig.z;
    const int32_t i02 = tgpig.y;
    const int32_t i01 = tgpig.x;

    const int32_t i13 = i03%args.ne13;
    const int32_t i12 = i02%args.ne12;
    const int32_t i11 = i01;

    device const float * psrc0 =                (device const float *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
    device const     T * pmask = src1 != src0 ? (device const T *    ) (src1 + i11*args.nb11 + i12*args.nb12 + i13*args.nb13) : nullptr;
    device const float * psrc2 = src2 != src0 ? (device const float *) (src2)                                                 : nullptr;
    device       float * pdst  =                (device       float *) (dst  + i01*args.nb1  + i02*args.nb2  + i03*args.nb3);

    float slope = 1.0f;

    if (args.max_bias > 0.0f) {
        const int32_t h = i02;

        const float base = h < args.n_head_log2 ? args.m0 : args.m1;
        const int   exp  = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;

        slope = pow(base, exp);
    }

    float lmax = psrc2 ? psrc2[i02] : -INFINITY;

    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        lmax = MAX(lmax, psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f));
    }
```

<｜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: metal/softmax.metal

```metal
// DS4 Metal softmax kernel used by the compressor pooling compatibility path.
// The single-compressed-row path is intentionally left as soft_max -> mul ->
// sum_rows instead of using the fused dsv4_softmax_pool kernel.

struct ds4_metal_args_soft_max {
    int32_t  ne00;
    int32_t  ne01;
    int32_t  ne02;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int32_t  ne11;
    int32_t  ne12;
    int32_t  ne13;
    uint64_t nb11;
    uint64_t nb12;
    uint64_t nb13;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
    float    scale;
    float    max_bias;
    float    m0;
    float    m1;
    int32_t  n_head_log2;
};

// Row softmax for score matrices. DS4 uses it in the literal one-compressor-row
// path where preserving the original graph operation boundary avoids drift.
template<typename T>
kernel void kernel_soft_max(
        constant ds4_metal_args_soft_max & args,
        device const  char * src0,
        device const  char * src1,
        device const  char * src2,
        device        char * dst,
        threadgroup  float * buf [[threadgroup(0)]],
        uint3 tgpig[[threadgroup_position_in_grid]],
        uint3 tpitg[[thread_position_in_threadgroup]],
        uint  sgitg[[simdgroup_index_in_threadgroup]],
        uint  tiisg[[thread_index_in_simdgroup]],
        uint3  tptg[[threads_per_threadgroup]]) {
    const int32_t i03 = tgpig.z;
    const int32_t i02 = tgpig.y;
    const int32_t i01 = tgpig.x;

    const int32_t i13 = i03%args.ne13;
    const int32_t i12 = i02%args.ne12;
    const int32_t i11 = i01;

    device const float * psrc0 =                (device const float *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
    device const     T * pmask = src1 != src0 ? (device const T *    ) (src1 + i11*args.nb11 + i12*args.nb12 + i13*args.nb13) : nullptr;
    device const float * psrc2 = src2 != src0 ? (device const float *) (src2)                                                 : nullptr;
    device       float * pdst  =                (device       float *) (dst  + i01*args.nb1  + i02*args.nb2  + i03*args.nb3);

    float slope = 1.0f;

    if (args.max_bias > 0.0f) {
        const int32_t h = i02;

        const float base = h < args.n_head_log2 ? args.m0 : args.m1;
        const int   exp  = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;

        slope = pow(base, exp);
    }

    float lmax = psrc2 ? psrc2[i02] : -INFINITY;

    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        lmax = MAX(lmax, psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f));
    }
```<｜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: metal/softmax.metal

```metal
// DS4 Metal softmax kernel used by the compressor pooling compatibility path.
// The single-compressed-row path is intentionally left as soft_max -> mul ->
// sum_rows instead of using the fused dsv4_softmax_pool kernel.

struct ds4_metal_args_soft_max {
    int32_t  ne00;
    int32_t  ne01;
    int32_t  ne02;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int32_t  ne11;
    int32_t  ne12;
    int32_t  ne13;
    uint64_t nb11;
    uint64_t nb12;
    uint64_t nb13;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
    float    scale;
    float    max_bias;
    float    m0;
    float    m1;
    int32_t  n_head_log2;
};

// Row softmax for score matrices. DS4 uses it in the literal one-compressor-row
// path where preserving the original graph operation boundary avoids drift.
template<typename T>
kernel void kernel_soft_max(
        constant ds4_metal_args_soft_max & args,
        device const  char * src0,
        device const  char * src1,
        device const  char * src2,
        device        char * dst,
        threadgroup  float * buf [[threadgroup(0)]],
        uint3 tgpig[[threadgroup_position_in_grid]],
        uint3 tpitg[[thread_position_in_threadgroup]],
        uint  sgitg[[simdgroup_index_in_threadgroup]],
        uint  tiisg[[thread_index_in_simdgroup]],
        uint3  tptg[[threads_per_threadgroup]]) {
    const int32_t i03 = tgpig.z;
    const int32_t i02 = tgpig.y;
    const int32_t i01 = tgpig.x;

    const int32_t i13 = i03%args.ne13;
    const int32_t i12 = i02%args.ne12;
    const int32_t i11 = i01;

    device const float * psrc0 =                (device const float *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
    device const     T * pmask = src1 != src0 ? (device const T *    ) (src1 + i11*args.nb11 + i12*args.nb12 + i13*args.nb13) : nullptr;
    device const float * psrc2 = src2 != src0 ? (device const float *) (src2)                                                 : nullptr;
    device       float * pdst  =                (device       float *) (dst  + i01*args.nb1  + i02*args.nb2  + i03*args.nb3);

    float slope = 1.0f;

    if (args.max_bias > 0.0f) {
        const int32_t h = i02;

        const float base = h < args.n_head_log2 ? args.m0 : args.m1;
        const int   exp  = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;

        slope = pow(base, exp);
    }

    float lmax = psrc2 ? psrc2[i02] : -INFINITY;

    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        lmax = MAX(lmax, psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f));
    }
```

<｜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: metal/softmax.metal

```metal
// DS4 Metal softmax kernel used by the compressor pooling compatibility path.
// The single-compressed-row path is intentionally left as soft_max -> mul ->
// sum_rows instead of using the fused dsv4_softmax_pool kernel.

struct ds4_metal_args_soft_max {
    int32_t  ne00;
    int32_t  ne01;
    int32_t  ne02;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int32_t  ne11;
    int32_t  ne12;
    int32_t  ne13;
    uint64_t nb11;
    uint64_t nb12;
    uint64_t nb13;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
    float    scale;
    float    max_bias;
    float    m0;
    float    m1;
    int32_t  n_head_log2;
};

// Row softmax for score matrices. DS4 uses it in the literal one-compressor-row
// path where preserving the original graph operation boundary avoids drift.
template<typename T>
kernel void kernel_soft_max(
        constant ds4_metal_args_soft_max & args,
        device const  char * src0,
        device const  char * src1,
        device const  char * src2,
        device        char * dst,
        threadgroup  float * buf [[threadgroup(0)]],
        uint3 tgpig[[threadgroup_position_in_grid]],
        uint3 tpitg[[thread_position_in_threadgroup]],
        uint  sgitg[[simdgroup_index_in_threadgroup]],
        uint  tiisg[[thread_index_in_simdgroup]],
        uint3  tptg[[threads_per_threadgroup]]) {
    const int32_t i03 = tgpig.z;
    const int32_t i02 = tgpig.y;
    const int32_t i01 = tgpig.x;

    const int32_t i13 = i03%args.ne13;
    const int32_t i12 = i02%args.ne12;
    const int32_t i11 = i01;

    device const float * psrc0 =                (device const float *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
    device const     T * pmask = src1 != src0 ? (device const T *    ) (src1 + i11*args.nb11 + i12*args.nb12 + i13*args.nb13) : nullptr;
    device const float * psrc2 = src2 != src0 ? (device const float *) (src2)                                                 : nullptr;
    device       float * pdst  =                (device       float *) (dst  + i01*args.nb1  + i02*args.nb2  + i03*args.nb3);

    float slope = 1.0f;

    if (args.max_bias > 0.0f) {
        const int32_t h = i02;

        const float base = h < args.n_head_log2 ? args.m0 : args.m1;
        const int   exp  = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;

        slope = pow(base, exp);
    }

    float lmax = psrc2 ? psrc2[i02] : -INFINITY;

    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        lmax = MAX(lmax, psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f));
    }
```<｜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: metal/softmax.metal

```metal
? psrc2[i02] : -INFINITY;

    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        lmax = MAX(lmax, psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f));
    }

    float max_val = simd_max(lmax);
    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = -INFINITY;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = max_val;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        max_val = buf[tiisg];
        max_val = simd_max(max_val);
    }

    float lsum = 0.0f;
    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        const float exp_psrc0 = exp((psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f)) - max_val);
        lsum += exp_psrc0;
        pdst[i00] = exp_psrc0;
    }

    threadgroup_barrier(mem_flags::mem_none);

    float sum = simd_sum(lsum);

    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = 0.0f;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = sum;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        sum = buf[tiisg];
        sum = simd_sum(sum);
    }

    if (psrc2) {
        sum += exp(psrc2[i02] - max_val);
    }

    const float inv_sum = 1.0f/sum;

    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        pdst[i00] *= inv_sum;
    }
}

// Vectorized float4 row softmax for contiguous score rows whose length is a
// multiple of four; used by the same DS4 compressor/indexer graph path.
template<typename T>
kernel void kernel_soft_max_4(
        constant ds4_metal_args_soft_max & args,
        device const  char * src0,
        device const  char * src1,
        device const  char * src2,
        device        char * dst,
        threadgroup  float * buf [[threadgroup(0)]],
        uint3 tgpig[[threadgroup_position_in_grid]],
        uint3 tpitg[[thread_position_in_threadgroup]],
        uint  sgitg[[simdgroup_index_in_threadgroup]],
        uint  tiisg[[thread_index_in_simdgroup]],
        uint3  tptg[[threads_per_threadgroup]]) {
    const int32_t i03 = tgpig.z;
    const int32_t i02 = tgpig.y;
    const int32_t i01 = tgpig.x;

    const int32_t i13 = i03%args.ne13;
    const int32_t i12 = i02%args.ne12;
    const int32_t i11 = i01;

    device const float4 * psrc4 =                (device const float4 *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
```

<｜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: metal/softmax.metal

```metal
? psrc2[i02] : -INFINITY;

    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        lmax = MAX(lmax, psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f));
    }

    float max_val = simd_max(lmax);
    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = -INFINITY;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = max_val;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        max_val = buf[tiisg];
        max_val = simd_max(max_val);
    }

    float lsum = 0.0f;
    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        const float exp_psrc0 = exp((psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f)) - max_val);
        lsum += exp_psrc0;
        pdst[i00] = exp_psrc0;
    }

    threadgroup_barrier(mem_flags::mem_none);

    float sum = simd_sum(lsum);

    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = 0.0f;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = sum;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        sum = buf[tiisg];
        sum = simd_sum(sum);
    }

    if (psrc2) {
        sum += exp(psrc2[i02] - max_val);
    }

    const float inv_sum = 1.0f/sum;

    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        pdst[i00] *= inv_sum;
    }
}

// Vectorized float4 row softmax for contiguous score rows whose length is a
// multiple of four; used by the same DS4 compressor/indexer graph path.
template<typename T>
kernel void kernel_soft_max_4(
        constant ds4_metal_args_soft_max & args,
        device const  char * src0,
        device const  char * src1,
        device const  char * src2,
        device        char * dst,
        threadgroup  float * buf [[threadgroup(0)]],
        uint3 tgpig[[threadgroup_position_in_grid]],
        uint3 tpitg[[thread_position_in_threadgroup]],
        uint  sgitg[[simdgroup_index_in_threadgroup]],
        uint  tiisg[[thread_index_in_simdgroup]],
        uint3  tptg[[threads_per_threadgroup]]) {
    const int32_t i03 = tgpig.z;
    const int32_t i02 = tgpig.y;
    const int32_t i01 = tgpig.x;

    const int32_t i13 = i03%args.ne13;
    const int32_t i12 = i02%args.ne12;
    const int32_t i11 = i01;

    device const float4 * psrc4 =                (device const float4 *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
```<｜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: metal/softmax.metal

```metal
? psrc2[i02] : -INFINITY;

    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        lmax = MAX(lmax, psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f));
    }

    float max_val = simd_max(lmax);
    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = -INFINITY;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = max_val;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        max_val = buf[tiisg];
        max_val = simd_max(max_val);
    }

    float lsum = 0.0f;
    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        const float exp_psrc0 = exp((psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f)) - max_val);
        lsum += exp_psrc0;
        pdst[i00] = exp_psrc0;
    }

    threadgroup_barrier(mem_flags::mem_none);

    float sum = simd_sum(lsum);

    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = 0.0f;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = sum;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        sum = buf[tiisg];
        sum = simd_sum(sum);
    }

    if (psrc2) {
        sum += exp(psrc2[i02] - max_val);
    }

    const float inv_sum = 1.0f/sum;

    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        pdst[i00] *= inv_sum;
    }
}

// Vectorized float4 row softmax for contiguous score rows whose length is a
// multiple of four; used by the same DS4 compressor/indexer graph path.
template<typename T>
kernel void kernel_soft_max_4(
        constant ds4_metal_args_soft_max & args,
        device const  char * src0,
        device const  char * src1,
        device const  char * src2,
        device        char * dst,
        threadgroup  float * buf [[threadgroup(0)]],
        uint3 tgpig[[threadgroup_position_in_grid]],
        uint3 tpitg[[thread_position_in_threadgroup]],
        uint  sgitg[[simdgroup_index_in_threadgroup]],
        uint  tiisg[[thread_index_in_simdgroup]],
        uint3  tptg[[threads_per_threadgroup]]) {
    const int32_t i03 = tgpig.z;
    const int32_t i02 = tgpig.y;
    const int32_t i01 = tgpig.x;

    const int32_t i13 = i03%args.ne13;
    const int32_t i12 = i02%args.ne12;
    const int32_t i11 = i01;

    device const float4 * psrc4 =                (device const float4 *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
```

<｜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: metal/softmax.metal

```metal
? psrc2[i02] : -INFINITY;

    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        lmax = MAX(lmax, psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f));
    }

    float max_val = simd_max(lmax);
    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = -INFINITY;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = max_val;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        max_val = buf[tiisg];
        max_val = simd_max(max_val);
    }

    float lsum = 0.0f;
    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        const float exp_psrc0 = exp((psrc0[i00]*args.scale + (pmask ? slope*pmask[i00] : 0.0f)) - max_val);
        lsum += exp_psrc0;
        pdst[i00] = exp_psrc0;
    }

    threadgroup_barrier(mem_flags::mem_none);

    float sum = simd_sum(lsum);

    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = 0.0f;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = sum;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        sum = buf[tiisg];
        sum = simd_sum(sum);
    }

    if (psrc2) {
        sum += exp(psrc2[i02] - max_val);
    }

    const float inv_sum = 1.0f/sum;

    for (int i00 = tpitg.x; i00 < args.ne00; i00 += tptg.x) {
        pdst[i00] *= inv_sum;
    }
}

// Vectorized float4 row softmax for contiguous score rows whose length is a
// multiple of four; used by the same DS4 compressor/indexer graph path.
template<typename T>
kernel void kernel_soft_max_4(
        constant ds4_metal_args_soft_max & args,
        device const  char * src0,
        device const  char * src1,
        device const  char * src2,
        device        char * dst,
        threadgroup  float * buf [[threadgroup(0)]],
        uint3 tgpig[[threadgroup_position_in_grid]],
        uint3 tpitg[[thread_position_in_threadgroup]],
        uint  sgitg[[simdgroup_index_in_threadgroup]],
        uint  tiisg[[thread_index_in_simdgroup]],
        uint3  tptg[[threads_per_threadgroup]]) {
    const int32_t i03 = tgpig.z;
    const int32_t i02 = tgpig.y;
    const int32_t i01 = tgpig.x;

    const int32_t i13 = i03%args.ne13;
    const int32_t i12 = i02%args.ne12;
    const int32_t i11 = i01;

    device const float4 * psrc4 =                (device const float4 *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
```<｜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: metal/softmax.metal

```metal
i12 = i02%args.ne12;
    const int32_t i11 = i01;

    device const float4 * psrc4 =                (device const float4 *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
    device const      T * pmask = src1 != src0 ? (device const T *     ) (src1 + i11*args.nb11 + i12*args.nb12 + i13*args.nb13) : nullptr;
    device const float *  psrc2 = src2 != src0 ? (device const float * ) (src2)                                                 : nullptr;
    device       float4 * pdst4 =                (device       float4 *) (dst  + i01*args.nb1  + i02*args.nb2  + i03*args.nb3);

    float slope = 1.0f;

    if (args.max_bias > 0.0f) {
        const int32_t h = i02;

        const float base = h < args.n_head_log2 ? args.m0 : args.m1;
        const int   exp  = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;

        slope = pow(base, exp);
    }

    float4 lmax4 = psrc2 ? psrc2[i02] : -INFINITY;

    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        lmax4 = fmax(lmax4, psrc4[i00]*args.scale + (float4)((pmask ? slope*pmask[i00] : 0.0f)));
    }

    const float lmax = MAX(MAX(lmax4[0], lmax4[1]), MAX(lmax4[2], lmax4[3]));

    float max_val = simd_max(lmax);
    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = -INFINITY;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = max_val;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        max_val = buf[tiisg];
        max_val = simd_max(max_val);
    }

    float4 lsum4 = 0.0f;
    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        const float4 exp_psrc4 = exp((psrc4[i00]*args.scale + (float4)((pmask ? slope*pmask[i00] : 0.0f))) - max_val);
        lsum4 += exp_psrc4;
        pdst4[i00] = exp_psrc4;
    }

    const float lsum = lsum4[0] + lsum4[1] + lsum4[2] + lsum4[3];

    threadgroup_barrier(mem_flags::mem_none);

    float sum = simd_sum(lsum);

    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = 0.0f;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = sum;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        sum = buf[tiisg];
        sum = simd_sum(sum);
    }

    if (psrc2) {
        sum += exp(psrc2[i02] - max_val);
    }

    const float inv_sum = 1.0f/sum;

    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        pdst4[i00] *= inv_sum;
    }
}
```

<｜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: metal/softmax.metal

```metal
i12 = i02%args.ne12;
    const int32_t i11 = i01;

    device const float4 * psrc4 =                (device const float4 *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
    device const      T * pmask = src1 != src0 ? (device const T *     ) (src1 + i11*args.nb11 + i12*args.nb12 + i13*args.nb13) : nullptr;
    device const float *  psrc2 = src2 != src0 ? (device const float * ) (src2)                                                 : nullptr;
    device       float4 * pdst4 =                (device       float4 *) (dst  + i01*args.nb1  + i02*args.nb2  + i03*args.nb3);

    float slope = 1.0f;

    if (args.max_bias > 0.0f) {
        const int32_t h = i02;

        const float base = h < args.n_head_log2 ? args.m0 : args.m1;
        const int   exp  = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;

        slope = pow(base, exp);
    }

    float4 lmax4 = psrc2 ? psrc2[i02] : -INFINITY;

    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        lmax4 = fmax(lmax4, psrc4[i00]*args.scale + (float4)((pmask ? slope*pmask[i00] : 0.0f)));
    }

    const float lmax = MAX(MAX(lmax4[0], lmax4[1]), MAX(lmax4[2], lmax4[3]));

    float max_val = simd_max(lmax);
    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = -INFINITY;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = max_val;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        max_val = buf[tiisg];
        max_val = simd_max(max_val);
    }

    float4 lsum4 = 0.0f;
    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        const float4 exp_psrc4 = exp((psrc4[i00]*args.scale + (float4)((pmask ? slope*pmask[i00] : 0.0f))) - max_val);
        lsum4 += exp_psrc4;
        pdst4[i00] = exp_psrc4;
    }

    const float lsum = lsum4[0] + lsum4[1] + lsum4[2] + lsum4[3];

    threadgroup_barrier(mem_flags::mem_none);

    float sum = simd_sum(lsum);

    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = 0.0f;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = sum;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        sum = buf[tiisg];
        sum = simd_sum(sum);
    }

    if (psrc2) {
        sum += exp(psrc2[i02] - max_val);
    }

    const float inv_sum = 1.0f/sum;

    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        pdst4[i00] *= inv_sum;
    }
}
```<｜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: metal/softmax.metal

```metal
i12 = i02%args.ne12;
    const int32_t i11 = i01;

    device const float4 * psrc4 =                (device const float4 *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
    device const      T * pmask = src1 != src0 ? (device const T *     ) (src1 + i11*args.nb11 + i12*args.nb12 + i13*args.nb13) : nullptr;
    device const float *  psrc2 = src2 != src0 ? (device const float * ) (src2)                                                 : nullptr;
    device       float4 * pdst4 =                (device       float4 *) (dst  + i01*args.nb1  + i02*args.nb2  + i03*args.nb3);

    float slope = 1.0f;

    if (args.max_bias > 0.0f) {
        const int32_t h = i02;

        const float base = h < args.n_head_log2 ? args.m0 : args.m1;
        const int   exp  = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;

        slope = pow(base, exp);
    }

    float4 lmax4 = psrc2 ? psrc2[i02] : -INFINITY;

    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        lmax4 = fmax(lmax4, psrc4[i00]*args.scale + (float4)((pmask ? slope*pmask[i00] : 0.0f)));
    }

    const float lmax = MAX(MAX(lmax4[0], lmax4[1]), MAX(lmax4[2], lmax4[3]));

    float max_val = simd_max(lmax);
    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = -INFINITY;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = max_val;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        max_val = buf[tiisg];
        max_val = simd_max(max_val);
    }

    float4 lsum4 = 0.0f;
    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        const float4 exp_psrc4 = exp((psrc4[i00]*args.scale + (float4)((pmask ? slope*pmask[i00] : 0.0f))) - max_val);
        lsum4 += exp_psrc4;
        pdst4[i00] = exp_psrc4;
    }

    const float lsum = lsum4[0] + lsum4[1] + lsum4[2] + lsum4[3];

    threadgroup_barrier(mem_flags::mem_none);

    float sum = simd_sum(lsum);

    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = 0.0f;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = sum;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        sum = buf[tiisg];
        sum = simd_sum(sum);
    }

    if (psrc2) {
        sum += exp(psrc2[i02] - max_val);
    }

    const float inv_sum = 1.0f/sum;

    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        pdst4[i00] *= inv_sum;
    }
}
```

<｜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: metal/softmax.metal

```metal
i12 = i02%args.ne12;
    const int32_t i11 = i01;

    device const float4 * psrc4 =                (device const float4 *) (src0 + i01*args.nb01 + i02*args.nb02 + i03*args.nb03);
    device const      T * pmask = src1 != src0 ? (device const T *     ) (src1 + i11*args.nb11 + i12*args.nb12 + i13*args.nb13) : nullptr;
    device const float *  psrc2 = src2 != src0 ? (device const float * ) (src2)                                                 : nullptr;
    device       float4 * pdst4 =                (device       float4 *) (dst  + i01*args.nb1  + i02*args.nb2  + i03*args.nb3);

    float slope = 1.0f;

    if (args.max_bias > 0.0f) {
        const int32_t h = i02;

        const float base = h < args.n_head_log2 ? args.m0 : args.m1;
        const int   exp  = h < args.n_head_log2 ? h + 1 : 2*(h - args.n_head_log2) + 1;

        slope = pow(base, exp);
    }

    float4 lmax4 = psrc2 ? psrc2[i02] : -INFINITY;

    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        lmax4 = fmax(lmax4, psrc4[i00]*args.scale + (float4)((pmask ? slope*pmask[i00] : 0.0f)));
    }

    const float lmax = MAX(MAX(lmax4[0], lmax4[1]), MAX(lmax4[2], lmax4[3]));

    float max_val = simd_max(lmax);
    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = -INFINITY;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = max_val;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        max_val = buf[tiisg];
        max_val = simd_max(max_val);
    }

    float4 lsum4 = 0.0f;
    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        const float4 exp_psrc4 = exp((psrc4[i00]*args.scale + (float4)((pmask ? slope*pmask[i00] : 0.0f))) - max_val);
        lsum4 += exp_psrc4;
        pdst4[i00] = exp_psrc4;
    }

    const float lsum = lsum4[0] + lsum4[1] + lsum4[2] + lsum4[3];

    threadgroup_barrier(mem_flags::mem_none);

    float sum = simd_sum(lsum);

    if (tptg.x > N_SIMDWIDTH) {
        if (sgitg == 0) {
            buf[tiisg] = 0.0f;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        if (tiisg == 0) {
            buf[sgitg] = sum;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        sum = buf[tiisg];
        sum = simd_sum(sum);
    }

    if (psrc2) {
        sum += exp(psrc2[i02] - max_val);
    }

    const float inv_sum = 1.0f/sum;

    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        pdst4[i00] *= inv_sum;
    }
}
```<｜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: metal/softmax.metal

```metal
um += exp(psrc2[i02] - max_val);
    }

    const float inv_sum = 1.0f/sum;

    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        pdst4[i00] *= inv_sum;
    }
}

typedef decltype(kernel_soft_max<float>)    kernel_soft_max_t;
typedef decltype(kernel_soft_max_4<float4>) kernel_soft_max_4_t;

// Host-visible F32 softmax variants used by compressor pooling.
template [[host_name("kernel_soft_max_f32")]]   kernel kernel_soft_max_t   kernel_soft_max<float>;
template [[host_name("kernel_soft_max_f32_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4<float4>;
```

<｜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: metal/softmax.metal

```metal
um += exp(psrc2[i02] - max_val);
    }

    const float inv_sum = 1.0f/sum;

    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        pdst4[i00] *= inv_sum;
    }
}

typedef decltype(kernel_soft_max<float>)    kernel_soft_max_t;
typedef decltype(kernel_soft_max_4<float4>) kernel_soft_max_4_t;

// Host-visible F32 softmax variants used by compressor pooling.
template [[host_name("kernel_soft_max_f32")]]   kernel kernel_soft_max_t   kernel_soft_max<float>;
template [[host_name("kernel_soft_max_f32_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4<float4>;
```<｜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: metal/softmax.metal

```metal
um += exp(psrc2[i02] - max_val);
    }

    const float inv_sum = 1.0f/sum;

    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        pdst4[i00] *= inv_sum;
    }
}

typedef decltype(kernel_soft_max<float>)    kernel_soft_max_t;
typedef decltype(kernel_soft_max_4<float4>) kernel_soft_max_4_t;

// Host-visible F32 softmax variants used by compressor pooling.
template [[host_name("kernel_soft_max_f32")]]   kernel kernel_soft_max_t   kernel_soft_max<float>;
template [[host_name("kernel_soft_max_f32_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4<float4>;
```

<｜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: metal/softmax.metal

```metal
um += exp(psrc2[i02] - max_val);
    }

    const float inv_sum = 1.0f/sum;

    for (int i00 = tpitg.x; i00 < args.ne00/4; i00 += tptg.x) {
        pdst4[i00] *= inv_sum;
    }
}

typedef decltype(kernel_soft_max<float>)    kernel_soft_max_t;
typedef decltype(kernel_soft_max_4<float4>) kernel_soft_max_4_t;

// Host-visible F32 softmax variants used by compressor pooling.
template [[host_name("kernel_soft_max_f32")]]   kernel kernel_soft_max_t   kernel_soft_max<float>;
template [[host_name("kernel_soft_max_f32_4")]] kernel kernel_soft_max_4_t kernel_soft_max_4<float4>;
```<｜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: metal/sum_rows.metal

```metal
// DS4 Metal row-sum kernel.

#define FC_SUM_ROWS 1400

#define OP_SUM_ROWS_NUM_SUM_ROWS 10
#define OP_SUM_ROWS_NUM_MEAN     11

struct ds4_metal_args_sum_rows {
    int64_t  ne00;
    int64_t  ne01;
    int64_t  ne02;
    int64_t  ne03;
    uint64_t nb00;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int64_t  ne0;
    int64_t  ne1;
    int64_t  ne2;
    int64_t  ne3;
    uint64_t nb0;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
};

static inline float sum(float x) {
    return x;
}

static inline float sum(float4 x) {
    return x[0] + x[1] + x[2] + x[3];
}

constant short FC_sum_rows_op [[function_constant(FC_SUM_ROWS + 0)]];

// Reduces each row to a sum or mean. DS4 mainly uses the sum form to preserve
// the compressor-pooling graph boundary in the single-compressor-row case.
template <typename T0, typename T>
kernel void kernel_sum_rows_impl(
        constant ds4_metal_args_sum_rows & args,
        device const char * src0,
        device       char * dst,
        threadgroup  char * shmem [[threadgroup(0)]],
        uint3   tgpig[[threadgroup_position_in_grid]],
        ushort3 tpitg[[thread_position_in_threadgroup]],
        ushort  sgitg[[simdgroup_index_in_threadgroup]],
        ushort  tiisg[[thread_index_in_simdgroup]],
        ushort3   ntg[[threads_per_threadgroup]]) {
#define FC_OP  FC_sum_rows_op

    const int i3 = tgpig.z;
    const int i2 = tgpig.y;
    const int i1 = tgpig.x;

    threadgroup T0 * shmem_t = (threadgroup T0 *) shmem;

    if (sgitg == 0) {
        shmem_t[tiisg] = 0.0f;
    }

    device const T0 * src_row = (device const T0 *) (src0 + i1*args.nb01 + i2*args.nb02 + i3*args.nb03);
    device       T  * dst_row = (device       T  *) (dst  + i1*args.nb1  + i2*args.nb2  + i3*args.nb3);

    T0 sumf = T0(0.0f);

    for (int64_t i0 = tpitg.x; i0 < args.ne00; i0 += ntg.x) {
        sumf += src_row[i0];
    }

    sumf = simd_sum(sumf);

    threadgroup_barrier(mem_flags::mem_threadgroup);

    if (tiisg == 0) {
        shmem_t[sgitg] = sumf;
    }

    threadgroup_barrier(mem_flags::mem_threadgroup);

    sumf = shmem_t[tiisg];
    sumf = simd_sum(sumf);

    if (tpitg.x == 0) {
        if (FC_OP == OP_SUM_ROWS_NUM_MEAN) {
            if (is_same<float4, T0>::value) {
                dst_row[0] = sum(sumf) / (4*args.ne00);
            } else {
                dst_row[0] = sum(sumf) / args.ne00;
            }
        } else {
            dst_row[0] = sum(sumf);
        }
    }

#undef FC_OP
}

typedef decltype(kernel_sum_rows_impl<float, float>) kernel_sum_rows_t;
```

<｜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: metal/sum_rows.metal

```metal
// DS4 Metal row-sum kernel.

#define FC_SUM_ROWS 1400

#define OP_SUM_ROWS_NUM_SUM_ROWS 10
#define OP_SUM_ROWS_NUM_MEAN     11

struct ds4_metal_args_sum_rows {
    int64_t  ne00;
    int64_t  ne01;
    int64_t  ne02;
    int64_t  ne03;
    uint64_t nb00;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int64_t  ne0;
    int64_t  ne1;
    int64_t  ne2;
    int64_t  ne3;
    uint64_t nb0;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
};

static inline float sum(float x) {
    return x;
}

static inline float sum(float4 x) {
    return x[0] + x[1] + x[2] + x[3];
}

constant short FC_sum_rows_op [[function_constant(FC_SUM_ROWS + 0)]];

// Reduces each row to a sum or mean. DS4 mainly uses the sum form to preserve
// the compressor-pooling graph boundary in the single-compressor-row case.
template <typename T0, typename T>
kernel void kernel_sum_rows_impl(
        constant ds4_metal_args_sum_rows & args,
        device const char * src0,
        device       char * dst,
        threadgroup  char * shmem [[threadgroup(0)]],
        uint3   tgpig[[threadgroup_position_in_grid]],
        ushort3 tpitg[[thread_position_in_threadgroup]],
        ushort  sgitg[[simdgroup_index_in_threadgroup]],
        ushort  tiisg[[thread_index_in_simdgroup]],
        ushort3   ntg[[threads_per_threadgroup]]) {
#define FC_OP  FC_sum_rows_op

    const int i3 = tgpig.z;
    const int i2 = tgpig.y;
    const int i1 = tgpig.x;

    threadgroup T0 * shmem_t = (threadgroup T0 *) shmem;

    if (sgitg == 0) {
        shmem_t[tiisg] = 0.0f;
    }

    device const T0 * src_row = (device const T0 *) (src0 + i1*args.nb01 + i2*args.nb02 + i3*args.nb03);
    device       T  * dst_row = (device       T  *) (dst  + i1*args.nb1  + i2*args.nb2  + i3*args.nb3);

    T0 sumf = T0(0.0f);

    for (int64_t i0 = tpitg.x; i0 < args.ne00; i0 += ntg.x) {
        sumf += src_row[i0];
    }

    sumf = simd_sum(sumf);

    threadgroup_barrier(mem_flags::mem_threadgroup);

    if (tiisg == 0) {
        shmem_t[sgitg] = sumf;
    }

    threadgroup_barrier(mem_flags::mem_threadgroup);

    sumf = shmem_t[tiisg];
    sumf = simd_sum(sumf);

    if (tpitg.x == 0) {
        if (FC_OP == OP_SUM_ROWS_NUM_MEAN) {
            if (is_same<float4, T0>::value) {
                dst_row[0] = sum(sumf) / (4*args.ne00);
            } else {
                dst_row[0] = sum(sumf) / args.ne00;
            }
        } else {
            dst_row[0] = sum(sumf);
        }
    }

#undef FC_OP
}

typedef decltype(kernel_sum_rows_impl<float, float>) kernel_sum_rows_t;
```<｜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: metal/sum_rows.metal

```metal
// DS4 Metal row-sum kernel.

#define FC_SUM_ROWS 1400

#define OP_SUM_ROWS_NUM_SUM_ROWS 10
#define OP_SUM_ROWS_NUM_MEAN     11

struct ds4_metal_args_sum_rows {
    int64_t  ne00;
    int64_t  ne01;
    int64_t  ne02;
    int64_t  ne03;
    uint64_t nb00;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int64_t  ne0;
    int64_t  ne1;
    int64_t  ne2;
    int64_t  ne3;
    uint64_t nb0;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
};

static inline float sum(float x) {
    return x;
}

static inline float sum(float4 x) {
    return x[0] + x[1] + x[2] + x[3];
}

constant short FC_sum_rows_op [[function_constant(FC_SUM_ROWS + 0)]];

// Reduces each row to a sum or mean. DS4 mainly uses the sum form to preserve
// the compressor-pooling graph boundary in the single-compressor-row case.
template <typename T0, typename T>
kernel void kernel_sum_rows_impl(
        constant ds4_metal_args_sum_rows & args,
        device const char * src0,
        device       char * dst,
        threadgroup  char * shmem [[threadgroup(0)]],
        uint3   tgpig[[threadgroup_position_in_grid]],
        ushort3 tpitg[[thread_position_in_threadgroup]],
        ushort  sgitg[[simdgroup_index_in_threadgroup]],
        ushort  tiisg[[thread_index_in_simdgroup]],
        ushort3   ntg[[threads_per_threadgroup]]) {
#define FC_OP  FC_sum_rows_op

    const int i3 = tgpig.z;
    const int i2 = tgpig.y;
    const int i1 = tgpig.x;

    threadgroup T0 * shmem_t = (threadgroup T0 *) shmem;

    if (sgitg == 0) {
        shmem_t[tiisg] = 0.0f;
    }

    device const T0 * src_row = (device const T0 *) (src0 + i1*args.nb01 + i2*args.nb02 + i3*args.nb03);
    device       T  * dst_row = (device       T  *) (dst  + i1*args.nb1  + i2*args.nb2  + i3*args.nb3);

    T0 sumf = T0(0.0f);

    for (int64_t i0 = tpitg.x; i0 < args.ne00; i0 += ntg.x) {
        sumf += src_row[i0];
    }

    sumf = simd_sum(sumf);

    threadgroup_barrier(mem_flags::mem_threadgroup);

    if (tiisg == 0) {
        shmem_t[sgitg] = sumf;
    }

    threadgroup_barrier(mem_flags::mem_threadgroup);

    sumf = shmem_t[tiisg];
    sumf = simd_sum(sumf);

    if (tpitg.x == 0) {
        if (FC_OP == OP_SUM_ROWS_NUM_MEAN) {
            if (is_same<float4, T0>::value) {
                dst_row[0] = sum(sumf) / (4*args.ne00);
            } else {
                dst_row[0] = sum(sumf) / args.ne00;
            }
        } else {
            dst_row[0] = sum(sumf);
        }
    }

#undef FC_OP
}

typedef decltype(kernel_sum_rows_impl<float, float>) kernel_sum_rows_t;
```

<｜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: metal/sum_rows.metal

```metal
// DS4 Metal row-sum kernel.

#define FC_SUM_ROWS 1400

#define OP_SUM_ROWS_NUM_SUM_ROWS 10
#define OP_SUM_ROWS_NUM_MEAN     11

struct ds4_metal_args_sum_rows {
    int64_t  ne00;
    int64_t  ne01;
    int64_t  ne02;
    int64_t  ne03;
    uint64_t nb00;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int64_t  ne0;
    int64_t  ne1;
    int64_t  ne2;
    int64_t  ne3;
    uint64_t nb0;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
};

static inline float sum(float x) {
    return x;
}

static inline float sum(float4 x) {
    return x[0] + x[1] + x[2] + x[3];
}

constant short FC_sum_rows_op [[function_constant(FC_SUM_ROWS + 0)]];

// Reduces each row to a sum or mean. DS4 mainly uses the sum form to preserve
// the compressor-pooling graph boundary in the single-compressor-row case.
template <typename T0, typename T>
kernel void kernel_sum_rows_impl(
        constant ds4_metal_args_sum_rows & args,
        device const char * src0,
        device       char * dst,
        threadgroup  char * shmem [[threadgroup(0)]],
        uint3   tgpig[[threadgroup_position_in_grid]],
        ushort3 tpitg[[thread_position_in_threadgroup]],
        ushort  sgitg[[simdgroup_index_in_threadgroup]],
        ushort  tiisg[[thread_index_in_simdgroup]],
        ushort3   ntg[[threads_per_threadgroup]]) {
#define FC_OP  FC_sum_rows_op

    const int i3 = tgpig.z;
    const int i2 = tgpig.y;
    const int i1 = tgpig.x;

    threadgroup T0 * shmem_t = (threadgroup T0 *) shmem;

    if (sgitg == 0) {
        shmem_t[tiisg] = 0.0f;
    }

    device const T0 * src_row = (device const T0 *) (src0 + i1*args.nb01 + i2*args.nb02 + i3*args.nb03);
    device       T  * dst_row = (device       T  *) (dst  + i1*args.nb1  + i2*args.nb2  + i3*args.nb3);

    T0 sumf = T0(0.0f);

    for (int64_t i0 = tpitg.x; i0 < args.ne00; i0 += ntg.x) {
        sumf += src_row[i0];
    }

    sumf = simd_sum(sumf);

    threadgroup_barrier(mem_flags::mem_threadgroup);

    if (tiisg == 0) {
        shmem_t[sgitg] = sumf;
    }

    threadgroup_barrier(mem_flags::mem_threadgroup);

    sumf = shmem_t[tiisg];
    sumf = simd_sum(sumf);

    if (tpitg.x == 0) {
        if (FC_OP == OP_SUM_ROWS_NUM_MEAN) {
            if (is_same<float4, T0>::value) {
                dst_row[0] = sum(sumf) / (4*args.ne00);
            } else {
                dst_row[0] = sum(sumf) / args.ne00;
            }
        } else {
            dst_row[0] = sum(sumf);
        }
    }

#undef FC_OP
}

typedef decltype(kernel_sum_rows_impl<float, float>) kernel_sum_rows_t;
```<｜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: metal/sum_rows.metal

```metal
s.ne00;
            }
        } else {
            dst_row[0] = sum(sumf);
        }
    }

#undef FC_OP
}

typedef decltype(kernel_sum_rows_impl<float, float>) kernel_sum_rows_t;

// Host-visible F32 row reduction used by compressor pooling.
template [[host_name("kernel_sum_rows_f32_f32")]] kernel kernel_sum_rows_t kernel_sum_rows_impl<float, float>;
```

<｜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: metal/sum_rows.metal

```metal
s.ne00;
            }
        } else {
            dst_row[0] = sum(sumf);
        }
    }

#undef FC_OP
}

typedef decltype(kernel_sum_rows_impl<float, float>) kernel_sum_rows_t;

// Host-visible F32 row reduction used by compressor pooling.
template [[host_name("kernel_sum_rows_f32_f32")]] kernel kernel_sum_rows_t kernel_sum_rows_impl<float, float>;
```<｜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: metal/sum_rows.metal

```metal
s.ne00;
            }
        } else {
            dst_row[0] = sum(sumf);
        }
    }

#undef FC_OP
}

typedef decltype(kernel_sum_rows_impl<float, float>) kernel_sum_rows_t;

// Host-visible F32 row reduction used by compressor pooling.
template [[host_name("kernel_sum_rows_f32_f32")]] kernel kernel_sum_rows_t kernel_sum_rows_impl<float, float>;
```

<｜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: metal/sum_rows.metal

```metal
s.ne00;
            }
        } else {
            dst_row[0] = sum(sumf);
        }
    }

#undef FC_OP
}

typedef decltype(kernel_sum_rows_impl<float, float>) kernel_sum_rows_t;

// Host-visible F32 row reduction used by compressor pooling.
template [[host_name("kernel_sum_rows_f32_f32")]] kernel kernel_sum_rows_t kernel_sum_rows_impl<float, float>;
```<｜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: metal/unary.metal

```metal
#define FC_UNARY 1200

#define OP_UNARY_NUM_SCALE      10
#define OP_UNARY_NUM_FILL       11
#define OP_UNARY_NUM_CLAMP      12
#define OP_UNARY_NUM_SQR        13
#define OP_UNARY_NUM_SQRT       14
#define OP_UNARY_NUM_SIN        15
#define OP_UNARY_NUM_COS        16
#define OP_UNARY_NUM_LOG        17
#define OP_UNARY_NUM_LEAKY_RELU 18

#define OP_UNARY_NUM_TANH        100
#define OP_UNARY_NUM_RELU        101
#define OP_UNARY_NUM_SIGMOID     102
#define OP_UNARY_NUM_GELU        103
#define OP_UNARY_NUM_GELU_ERF    104
#define OP_UNARY_NUM_GELU_QUICK  105
#define OP_UNARY_NUM_SILU        106
#define OP_UNARY_NUM_ELU         107
#define OP_UNARY_NUM_NEG         108
#define OP_UNARY_NUM_ABS         109
#define OP_UNARY_NUM_SGN         110
#define OP_UNARY_NUM_STEP        111
#define OP_UNARY_NUM_HARDSWISH   112
#define OP_UNARY_NUM_HARDSIGMOID 113
#define OP_UNARY_NUM_EXP         114
#define OP_UNARY_NUM_SOFTPLUS    115
#define OP_UNARY_NUM_EXPM1       116
#define OP_UNARY_NUM_FLOOR       117
#define OP_UNARY_NUM_CEIL        118
#define OP_UNARY_NUM_ROUND       119
#define OP_UNARY_NUM_TRUNC       120
#define OP_UNARY_NUM_XIELU       121

struct ds4_metal_args_unary {
    int32_t  ne00;
    int32_t  ne01;
    int32_t  ne02;
    int32_t  ne03;
    uint64_t nb00;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int32_t  ne0;
    int32_t  ne1;
    int32_t  ne2;
    int32_t  ne3;
    uint64_t nb0;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
    float    slope;
    float    scale;
    float    bias;
    float    val;
    float    min;
    float    max;
};

constant float GELU_COEF_A     = 0.044715f;
constant float GELU_QUICK_COEF = -1.702f;
constant float SQRT_2_OVER_PI  = 0.79788456080286535587989211986876f;
constant float SQRT_2_INV      = 0.70710678118654752440084436210484f;

// based on Abramowitz and Stegun formula 7.1.26 or similar Hastings' approximation
// ref: https://www.johndcook.com/blog/python_erf/
constant float p_erf  = 0.3275911f;
constant float a1_erf = 0.254829592f;
constant float a2_erf = -0.284496736f;
constant float a3_erf = 1.421413741f;
constant float a4_erf = -1.453152027f;
constant float a5_erf = 1.061405429f;

template<typename T>
inline T erf_approx(T x) {
    T sign_x = sign(x);
    x = fabs(x);
    T t = 1.0f / (1.0f + p_erf * x);
    T y = 1.0f - (((((a5_erf * t + a4_erf) * t) + a3_erf) * t + a2_erf) * t + a1_erf) * t * exp(-x * x);
    return sign_x * y;
}

template<typename T> T elu_approx(T x);

template<> inline float elu_approx<float>(float x) {
    return (x > 0.f) ? x : (exp(x) - 1);
}
```

<｜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: metal/unary.metal

```metal
#define FC_UNARY 1200

#define OP_UNARY_NUM_SCALE      10
#define OP_UNARY_NUM_FILL       11
#define OP_UNARY_NUM_CLAMP      12
#define OP_UNARY_NUM_SQR        13
#define OP_UNARY_NUM_SQRT       14
#define OP_UNARY_NUM_SIN        15
#define OP_UNARY_NUM_COS        16
#define OP_UNARY_NUM_LOG        17
#define OP_UNARY_NUM_LEAKY_RELU 18

#define OP_UNARY_NUM_TANH        100
#define OP_UNARY_NUM_RELU        101
#define OP_UNARY_NUM_SIGMOID     102
#define OP_UNARY_NUM_GELU        103
#define OP_UNARY_NUM_GELU_ERF    104
#define OP_UNARY_NUM_GELU_QUICK  105
#define OP_UNARY_NUM_SILU        106
#define OP_UNARY_NUM_ELU         107
#define OP_UNARY_NUM_NEG         108
#define OP_UNARY_NUM_ABS         109
#define OP_UNARY_NUM_SGN         110
#define OP_UNARY_NUM_STEP        111
#define OP_UNARY_NUM_HARDSWISH   112
#define OP_UNARY_NUM_HARDSIGMOID 113
#define OP_UNARY_NUM_EXP         114
#define OP_UNARY_NUM_SOFTPLUS    115
#define OP_UNARY_NUM_EXPM1       116
#define OP_UNARY_NUM_FLOOR       117
#define OP_UNARY_NUM_CEIL        118
#define OP_UNARY_NUM_ROUND       119
#define OP_UNARY_NUM_TRUNC       120
#define OP_UNARY_NUM_XIELU       121

struct ds4_metal_args_unary {
    int32_t  ne00;
    int32_t  ne01;
    int32_t  ne02;
    int32_t  ne03;
    uint64_t nb00;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int32_t  ne0;
    int32_t  ne1;
    int32_t  ne2;
    int32_t  ne3;
    uint64_t nb0;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
    float    slope;
    float    scale;
    float    bias;
    float    val;
    float    min;
    float    max;
};

constant float GELU_COEF_A     = 0.044715f;
constant float GELU_QUICK_COEF = -1.702f;
constant float SQRT_2_OVER_PI  = 0.79788456080286535587989211986876f;
constant float SQRT_2_INV      = 0.70710678118654752440084436210484f;

// based on Abramowitz and Stegun formula 7.1.26 or similar Hastings' approximation
// ref: https://www.johndcook.com/blog/python_erf/
constant float p_erf  = 0.3275911f;
constant float a1_erf = 0.254829592f;
constant float a2_erf = -0.284496736f;
constant float a3_erf = 1.421413741f;
constant float a4_erf = -1.453152027f;
constant float a5_erf = 1.061405429f;

template<typename T>
inline T erf_approx(T x) {
    T sign_x = sign(x);
    x = fabs(x);
    T t = 1.0f / (1.0f + p_erf * x);
    T y = 1.0f - (((((a5_erf * t + a4_erf) * t) + a3_erf) * t + a2_erf) * t + a1_erf) * t * exp(-x * x);
    return sign_x * y;
}

template<typename T> T elu_approx(T x);

template<> inline float elu_approx<float>(float x) {
    return (x > 0.f) ? x : (exp(x) - 1);
}
```<｜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: metal/unary.metal

```metal
#define FC_UNARY 1200

#define OP_UNARY_NUM_SCALE      10
#define OP_UNARY_NUM_FILL       11
#define OP_UNARY_NUM_CLAMP      12
#define OP_UNARY_NUM_SQR        13
#define OP_UNARY_NUM_SQRT       14
#define OP_UNARY_NUM_SIN        15
#define OP_UNARY_NUM_COS        16
#define OP_UNARY_NUM_LOG        17
#define OP_UNARY_NUM_LEAKY_RELU 18

#define OP_UNARY_NUM_TANH        100
#define OP_UNARY_NUM_RELU        101
#define OP_UNARY_NUM_SIGMOID     102
#define OP_UNARY_NUM_GELU        103
#define OP_UNARY_NUM_GELU_ERF    104
#define OP_UNARY_NUM_GELU_QUICK  105
#define OP_UNARY_NUM_SILU        106
#define OP_UNARY_NUM_ELU         107
#define OP_UNARY_NUM_NEG         108
#define OP_UNARY_NUM_ABS         109
#define OP_UNARY_NUM_SGN         110
#define OP_UNARY_NUM_STEP        111
#define OP_UNARY_NUM_HARDSWISH   112
#define OP_UNARY_NUM_HARDSIGMOID 113
#define OP_UNARY_NUM_EXP         114
#define OP_UNARY_NUM_SOFTPLUS    115
#define OP_UNARY_NUM_EXPM1       116
#define OP_UNARY_NUM_FLOOR       117
#define OP_UNARY_NUM_CEIL        118
#define OP_UNARY_NUM_ROUND       119
#define OP_UNARY_NUM_TRUNC       120
#define OP_UNARY_NUM_XIELU       121

struct ds4_metal_args_unary {
    int32_t  ne00;
    int32_t  ne01;
    int32_t  ne02;
    int32_t  ne03;
    uint64_t nb00;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int32_t  ne0;
    int32_t  ne1;
    int32_t  ne2;
    int32_t  ne3;
    uint64_t nb0;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
    float    slope;
    float    scale;
    float    bias;
    float    val;
    float    min;
    float    max;
};

constant float GELU_COEF_A     = 0.044715f;
constant float GELU_QUICK_COEF = -1.702f;
constant float SQRT_2_OVER_PI  = 0.79788456080286535587989211986876f;
constant float SQRT_2_INV      = 0.70710678118654752440084436210484f;

// based on Abramowitz and Stegun formula 7.1.26 or similar Hastings' approximation
// ref: https://www.johndcook.com/blog/python_erf/
constant float p_erf  = 0.3275911f;
constant float a1_erf = 0.254829592f;
constant float a2_erf = -0.284496736f;
constant float a3_erf = 1.421413741f;
constant float a4_erf = -1.453152027f;
constant float a5_erf = 1.061405429f;

template<typename T>
inline T erf_approx(T x) {
    T sign_x = sign(x);
    x = fabs(x);
    T t = 1.0f / (1.0f + p_erf * x);
    T y = 1.0f - (((((a5_erf * t + a4_erf) * t) + a3_erf) * t + a2_erf) * t + a1_erf) * t * exp(-x * x);
    return sign_x * y;
}

template<typename T> T elu_approx(T x);

template<> inline float elu_approx<float>(float x) {
    return (x > 0.f) ? x : (exp(x) - 1);
}
```

<｜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: metal/unary.metal

```metal
#define FC_UNARY 1200

#define OP_UNARY_NUM_SCALE      10
#define OP_UNARY_NUM_FILL       11
#define OP_UNARY_NUM_CLAMP      12
#define OP_UNARY_NUM_SQR        13
#define OP_UNARY_NUM_SQRT       14
#define OP_UNARY_NUM_SIN        15
#define OP_UNARY_NUM_COS        16
#define OP_UNARY_NUM_LOG        17
#define OP_UNARY_NUM_LEAKY_RELU 18

#define OP_UNARY_NUM_TANH        100
#define OP_UNARY_NUM_RELU        101
#define OP_UNARY_NUM_SIGMOID     102
#define OP_UNARY_NUM_GELU        103
#define OP_UNARY_NUM_GELU_ERF    104
#define OP_UNARY_NUM_GELU_QUICK  105
#define OP_UNARY_NUM_SILU        106
#define OP_UNARY_NUM_ELU         107
#define OP_UNARY_NUM_NEG         108
#define OP_UNARY_NUM_ABS         109
#define OP_UNARY_NUM_SGN         110
#define OP_UNARY_NUM_STEP        111
#define OP_UNARY_NUM_HARDSWISH   112
#define OP_UNARY_NUM_HARDSIGMOID 113
#define OP_UNARY_NUM_EXP         114
#define OP_UNARY_NUM_SOFTPLUS    115
#define OP_UNARY_NUM_EXPM1       116
#define OP_UNARY_NUM_FLOOR       117
#define OP_UNARY_NUM_CEIL        118
#define OP_UNARY_NUM_ROUND       119
#define OP_UNARY_NUM_TRUNC       120
#define OP_UNARY_NUM_XIELU       121

struct ds4_metal_args_unary {
    int32_t  ne00;
    int32_t  ne01;
    int32_t  ne02;
    int32_t  ne03;
    uint64_t nb00;
    uint64_t nb01;
    uint64_t nb02;
    uint64_t nb03;
    int32_t  ne0;
    int32_t  ne1;
    int32_t  ne2;
    int32_t  ne3;
    uint64_t nb0;
    uint64_t nb1;
    uint64_t nb2;
    uint64_t nb3;
    float    slope;
    float    scale;
    float    bias;
    float    val;
    float    min;
    float    max;
};

constant float GELU_COEF_A     = 0.044715f;
constant float GELU_QUICK_COEF = -1.702f;
constant float SQRT_2_OVER_PI  = 0.79788456080286535587989211986876f;
constant float SQRT_2_INV      = 0.70710678118654752440084436210484f;

// based on Abramowitz and Stegun formula 7.1.26 or similar Hastings' approximation
// ref: https://www.johndcook.com/blog/python_erf/
constant float p_erf  = 0.3275911f;
constant float a1_erf = 0.254829592f;
constant float a2_erf = -0.284496736f;
constant float a3_erf = 1.421413741f;
constant float a4_erf = -1.453152027f;
constant float a5_erf = 1.061405429f;

template<typename T>
inline T erf_approx(T x) {
    T sign_x = sign(x);
    x = fabs(x);
    T t = 1.0f / (1.0f + p_erf * x);
    T y = 1.0f - (((((a5_erf * t + a4_erf) * t) + a3_erf) * t + a2_erf) * t + a1_erf) * t * exp(-x * x);
    return sign_x * y;
}

template<typename T> T elu_approx(T x);

template<> inline float elu_approx<float>(float x) {
    return (x > 0.f) ? x : (exp(x) - 1);
}
```<｜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: metal/unary.metal

```metal
t * exp(-x * x);
    return sign_x * y;
}

template<typename T> T elu_approx(T x);

template<> inline float elu_approx<float>(float x) {
    return (x > 0.f) ? x : (exp(x) - 1);
}

template<> inline float4 elu_approx<float4>(float4 x) {
    float4 res;

    res[0] = (x[0] > 0.0f) ? x[0] : (exp(x[0]) - 1.0f);
    res[1] = (x[1] > 0.0f) ? x[1] : (exp(x[1]) - 1.0f);
    res[2] = (x[2] > 0.0f) ? x[2] : (exp(x[2]) - 1.0f);
    res[3] = (x[3] > 0.0f) ? x[3] : (exp(x[3]) - 1.0f);

    return res;
}

constant short FC_unary_op [[function_constant(FC_UNARY + 0)]];
constant bool  FC_unary_cnt[[function_constant(FC_UNARY + 1)]];

// Generic unary elementwise op selected by function constant. DS4 only uses a
// small subset in inference, mainly sigmoid, SiLU, softplus, sqrt, clamp,
// scale, and fill.
template <typename T0, typename T, typename TC>
kernel void kernel_unary_impl(
        constant ds4_metal_args_unary & args,
        device const char * src0,
        device       char * dst,
        uint3   tgpig[[threadgroup_position_in_grid]],
        ushort3 tpitg[[thread_position_in_threadgroup]],
        ushort3   ntg[[threads_per_threadgroup]]) {
#define FC_OP  FC_unary_op
#define FC_CNT FC_unary_cnt

    device const T0 * src0_ptr;
    device       T  * dst_ptr;

    int i0;

    if (FC_CNT) {
        i0 = tgpig.x;

        src0_ptr = (device const T0 *) (src0);
        dst_ptr  = (device       T  *) (dst);
    } else {
        const int i03 = tgpig.z;
        const int i02 = tgpig.y;
        const int k0  = tgpig.x/args.ne01;
        const int i01 = tgpig.x - k0*args.ne01;

        i0 = k0*ntg.x + tpitg.x;

        src0_ptr = (device const T0 *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
        dst_ptr  = (device       T  *) (dst  + i03*args.nb3  + i02*args.nb2  + i01*args.nb1 );
    }

    {
        if (!FC_CNT) {
            if (i0 >= args.ne0) {
                return;
            }
        }

        const TC x = (TC) src0_ptr[i0];

        if (FC_OP == OP_UNARY_NUM_SCALE) {
            dst_ptr[i0] = (T) (args.scale * x + args.bias);
        }

        if (FC_OP == OP_UNARY_NUM_FILL) {
            dst_ptr[i0] = (T) args.val;
        }

        if (FC_OP == OP_UNARY_NUM_CLAMP) {
            dst_ptr[i0] = (T) clamp(x, args.min, args.max);
        }

        if (FC_OP == OP_UNARY_NUM_SQR) {
            dst_ptr[i0] = (T) (x * x);
        }

        if (FC_OP == OP_UNARY_NUM_SQRT) {
            dst_ptr[i0] = (T) sqrt(x);
        }

        if (FC_OP == OP_UNARY_NUM_SIN) {
            dst_ptr[i0] = (T) sin(x);
        }
```

<｜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: metal/unary.metal

```metal
t * exp(-x * x);
    return sign_x * y;
}

template<typename T> T elu_approx(T x);

template<> inline float elu_approx<float>(float x) {
    return (x > 0.f) ? x : (exp(x) - 1);
}

template<> inline float4 elu_approx<float4>(float4 x) {
    float4 res;

    res[0] = (x[0] > 0.0f) ? x[0] : (exp(x[0]) - 1.0f);
    res[1] = (x[1] > 0.0f) ? x[1] : (exp(x[1]) - 1.0f);
    res[2] = (x[2] > 0.0f) ? x[2] : (exp(x[2]) - 1.0f);
    res[3] = (x[3] > 0.0f) ? x[3] : (exp(x[3]) - 1.0f);

    return res;
}

constant short FC_unary_op [[function_constant(FC_UNARY + 0)]];
constant bool  FC_unary_cnt[[function_constant(FC_UNARY + 1)]];

// Generic unary elementwise op selected by function constant. DS4 only uses a
// small subset in inference, mainly sigmoid, SiLU, softplus, sqrt, clamp,
// scale, and fill.
template <typename T0, typename T, typename TC>
kernel void kernel_unary_impl(
        constant ds4_metal_args_unary & args,
        device const char * src0,
        device       char * dst,
        uint3   tgpig[[threadgroup_position_in_grid]],
        ushort3 tpitg[[thread_position_in_threadgroup]],
        ushort3   ntg[[threads_per_threadgroup]]) {
#define FC_OP  FC_unary_op
#define FC_CNT FC_unary_cnt

    device const T0 * src0_ptr;
    device       T  * dst_ptr;

    int i0;

    if (FC_CNT) {
        i0 = tgpig.x;

        src0_ptr = (device const T0 *) (src0);
        dst_ptr  = (device       T  *) (dst);
    } else {
        const int i03 = tgpig.z;
        const int i02 = tgpig.y;
        const int k0  = tgpig.x/args.ne01;
        const int i01 = tgpig.x - k0*args.ne01;

        i0 = k0*ntg.x + tpitg.x;

        src0_ptr = (device const T0 *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
        dst_ptr  = (device       T  *) (dst  + i03*args.nb3  + i02*args.nb2  + i01*args.nb1 );
    }

    {
        if (!FC_CNT) {
            if (i0 >= args.ne0) {
                return;
            }
        }

        const TC x = (TC) src0_ptr[i0];

        if (FC_OP == OP_UNARY_NUM_SCALE) {
            dst_ptr[i0] = (T) (args.scale * x + args.bias);
        }

        if (FC_OP == OP_UNARY_NUM_FILL) {
            dst_ptr[i0] = (T) args.val;
        }

        if (FC_OP == OP_UNARY_NUM_CLAMP) {
            dst_ptr[i0] = (T) clamp(x, args.min, args.max);
        }

        if (FC_OP == OP_UNARY_NUM_SQR) {
            dst_ptr[i0] = (T) (x * x);
        }

        if (FC_OP == OP_UNARY_NUM_SQRT) {
            dst_ptr[i0] = (T) sqrt(x);
        }

        if (FC_OP == OP_UNARY_NUM_SIN) {
            dst_ptr[i0] = (T) sin(x);
        }
```<｜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: metal/unary.metal

```metal
t * exp(-x * x);
    return sign_x * y;
}

template<typename T> T elu_approx(T x);

template<> inline float elu_approx<float>(float x) {
    return (x > 0.f) ? x : (exp(x) - 1);
}

template<> inline float4 elu_approx<float4>(float4 x) {
    float4 res;

    res[0] = (x[0] > 0.0f) ? x[0] : (exp(x[0]) - 1.0f);
    res[1] = (x[1] > 0.0f) ? x[1] : (exp(x[1]) - 1.0f);
    res[2] = (x[2] > 0.0f) ? x[2] : (exp(x[2]) - 1.0f);
    res[3] = (x[3] > 0.0f) ? x[3] : (exp(x[3]) - 1.0f);

    return res;
}

constant short FC_unary_op [[function_constant(FC_UNARY + 0)]];
constant bool  FC_unary_cnt[[function_constant(FC_UNARY + 1)]];

// Generic unary elementwise op selected by function constant. DS4 only uses a
// small subset in inference, mainly sigmoid, SiLU, softplus, sqrt, clamp,
// scale, and fill.
template <typename T0, typename T, typename TC>
kernel void kernel_unary_impl(
        constant ds4_metal_args_unary & args,
        device const char * src0,
        device       char * dst,
        uint3   tgpig[[threadgroup_position_in_grid]],
        ushort3 tpitg[[thread_position_in_threadgroup]],
        ushort3   ntg[[threads_per_threadgroup]]) {
#define FC_OP  FC_unary_op
#define FC_CNT FC_unary_cnt

    device const T0 * src0_ptr;
    device       T  * dst_ptr;

    int i0;

    if (FC_CNT) {
        i0 = tgpig.x;

        src0_ptr = (device const T0 *) (src0);
        dst_ptr  = (device       T  *) (dst);
    } else {
        const int i03 = tgpig.z;
        const int i02 = tgpig.y;
        const int k0  = tgpig.x/args.ne01;
        const int i01 = tgpig.x - k0*args.ne01;

        i0 = k0*ntg.x + tpitg.x;

        src0_ptr = (device const T0 *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
        dst_ptr  = (device       T  *) (dst  + i03*args.nb3  + i02*args.nb2  + i01*args.nb1 );
    }

    {
        if (!FC_CNT) {
            if (i0 >= args.ne0) {
                return;
            }
        }

        const TC x = (TC) src0_ptr[i0];

        if (FC_OP == OP_UNARY_NUM_SCALE) {
            dst_ptr[i0] = (T) (args.scale * x + args.bias);
        }

        if (FC_OP == OP_UNARY_NUM_FILL) {
            dst_ptr[i0] = (T) args.val;
        }

        if (FC_OP == OP_UNARY_NUM_CLAMP) {
            dst_ptr[i0] = (T) clamp(x, args.min, args.max);
        }

        if (FC_OP == OP_UNARY_NUM_SQR) {
            dst_ptr[i0] = (T) (x * x);
        }

        if (FC_OP == OP_UNARY_NUM_SQRT) {
            dst_ptr[i0] = (T) sqrt(x);
        }

        if (FC_OP == OP_UNARY_NUM_SIN) {
            dst_ptr[i0] = (T) sin(x);
        }
```

<｜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: metal/unary.metal

```metal
t * exp(-x * x);
    return sign_x * y;
}

template<typename T> T elu_approx(T x);

template<> inline float elu_approx<float>(float x) {
    return (x > 0.f) ? x : (exp(x) - 1);
}

template<> inline float4 elu_approx<float4>(float4 x) {
    float4 res;

    res[0] = (x[0] > 0.0f) ? x[0] : (exp(x[0]) - 1.0f);
    res[1] = (x[1] > 0.0f) ? x[1] : (exp(x[1]) - 1.0f);
    res[2] = (x[2] > 0.0f) ? x[2] : (exp(x[2]) - 1.0f);
    res[3] = (x[3] > 0.0f) ? x[3] : (exp(x[3]) - 1.0f);

    return res;
}

constant short FC_unary_op [[function_constant(FC_UNARY + 0)]];
constant bool  FC_unary_cnt[[function_constant(FC_UNARY + 1)]];

// Generic unary elementwise op selected by function constant. DS4 only uses a
// small subset in inference, mainly sigmoid, SiLU, softplus, sqrt, clamp,
// scale, and fill.
template <typename T0, typename T, typename TC>
kernel void kernel_unary_impl(
        constant ds4_metal_args_unary & args,
        device const char * src0,
        device       char * dst,
        uint3   tgpig[[threadgroup_position_in_grid]],
        ushort3 tpitg[[thread_position_in_threadgroup]],
        ushort3   ntg[[threads_per_threadgroup]]) {
#define FC_OP  FC_unary_op
#define FC_CNT FC_unary_cnt

    device const T0 * src0_ptr;
    device       T  * dst_ptr;

    int i0;

    if (FC_CNT) {
        i0 = tgpig.x;

        src0_ptr = (device const T0 *) (src0);
        dst_ptr  = (device       T  *) (dst);
    } else {
        const int i03 = tgpig.z;
        const int i02 = tgpig.y;
        const int k0  = tgpig.x/args.ne01;
        const int i01 = tgpig.x - k0*args.ne01;

        i0 = k0*ntg.x + tpitg.x;

        src0_ptr = (device const T0 *) (src0 + i03*args.nb03 + i02*args.nb02 + i01*args.nb01);
        dst_ptr  = (device       T  *) (dst  + i03*args.nb3  + i02*args.nb2  + i01*args.nb1 );
    }

    {
        if (!FC_CNT) {
            if (i0 >= args.ne0) {
                return;
            }
        }

        const TC x = (TC) src0_ptr[i0];

        if (FC_OP == OP_UNARY_NUM_SCALE) {
            dst_ptr[i0] = (T) (args.scale * x + args.bias);
        }

        if (FC_OP == OP_UNARY_NUM_FILL) {
            dst_ptr[i0] = (T) args.val;
        }

        if (FC_OP == OP_UNARY_NUM_CLAMP) {
            dst_ptr[i0] = (T) clamp(x, args.min, args.max);
        }

        if (FC_OP == OP_UNARY_NUM_SQR) {
            dst_ptr[i0] = (T) (x * x);
        }

        if (FC_OP == OP_UNARY_NUM_SQRT) {
            dst_ptr[i0] = (T) sqrt(x);
        }

        if (FC_OP == OP_UNARY_NUM_SIN) {
            dst_ptr[i0] = (T) sin(x);
        }
```<｜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: metal/unary.metal

```metal
if (FC_OP == OP_UNARY_NUM_SQRT) {
            dst_ptr[i0] = (T) sqrt(x);
        }

        if (FC_OP == OP_UNARY_NUM_SIN) {
            dst_ptr[i0] = (T) sin(x);
        }

        if (FC_OP == OP_UNARY_NUM_COS) {
            dst_ptr[i0] = (T) cos(x);
        }

        if (FC_OP == OP_UNARY_NUM_LOG) {
            dst_ptr[i0] = (T) log(x);
        }

        if (FC_OP == OP_UNARY_NUM_LEAKY_RELU) {
            dst_ptr[i0] = (T) (TC(x > 0)*x + TC(x <= 0)*(x * args.slope));
        }

        if (FC_OP == OP_UNARY_NUM_TANH) {
            dst_ptr[i0] = (T) precise::tanh(x);
        }

        if (FC_OP == OP_UNARY_NUM_RELU) {
            dst_ptr[i0] = (T) fmax(0, x);
        }

        if (FC_OP == OP_UNARY_NUM_SIGMOID) {
            dst_ptr[i0] = (T) (1 / (1 + exp(-x)));
        }

        if (FC_OP == OP_UNARY_NUM_GELU) {
            dst_ptr[i0] = (T) (0.5*x*(1 + precise::tanh(SQRT_2_OVER_PI*x*(1 + GELU_COEF_A*x*x))));
        }

        if (FC_OP == OP_UNARY_NUM_GELU_ERF) {
            dst_ptr[i0] = (T) (0.5*x*(1 + erf_approx(SQRT_2_INV*x)));
        }

        if (FC_OP == OP_UNARY_NUM_GELU_QUICK) {
            dst_ptr[i0] = (T) (x * (1/(1 + exp(GELU_QUICK_COEF*x))));
        }

        if (FC_OP == OP_UNARY_NUM_SILU) {
            dst_ptr[i0] = (T) (x / (1 + exp(-x)));
        }

        if (FC_OP == OP_UNARY_NUM_ELU) {
            dst_ptr[i0] = (T) elu_approx(x);
        }

        if (FC_OP == OP_UNARY_NUM_NEG) {
            dst_ptr[i0] = (T) -x;
        }

        if (FC_OP == OP_UNARY_NUM_ABS) {
            dst_ptr[i0] = (T) fabs(x);
        }

        if (FC_OP == OP_UNARY_NUM_SGN) {
            dst_ptr[i0] = T(x > 0) - T(x < 0);
        }

        if (FC_OP == OP_UNARY_NUM_STEP) {
            dst_ptr[i0] = T(x > 0);
        }

        if (FC_OP == OP_UNARY_NUM_HARDSWISH) {
            dst_ptr[i0] = (T) (x * fmax(0, fmin(1, x/6 + 0.5)));
        }

        if (FC_OP == OP_UNARY_NUM_HARDSIGMOID) {
            dst_ptr[i0] = (T) fmax(0, fmin(1, x/6 + 0.5));
        }

        if (FC_OP == OP_UNARY_NUM_EXP) {
            dst_ptr[i0] = (T) exp(x);
        }

        if (FC_OP == OP_UNARY_NUM_SOFTPLUS) {
            dst_ptr[i0] = (T) select(log(1 + exp(x)), x, x > 20);
        }

        if (FC_OP == OP_UNARY_NUM_EXPM1) {
            // Metal target profiles used here do not all expose expm1(); this
            // generic unary branch is not used by the DS4 inference graph.
            dst_ptr[i0] = (T) (exp(x) - 1);
        }

        if (FC_OP == OP_UNARY_NUM_FLOOR) {
            dst_ptr[i0] = (T) floor(x);
        }
```

<｜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: metal/unary.metal

```metal
if (FC_OP == OP_UNARY_NUM_SQRT) {
            dst_ptr[i0] = (T) sqrt(x);
        }

        if (FC_OP == OP_UNARY_NUM_SIN) {
            dst_ptr[i0] = (T) sin(x);
        }

        if (FC_OP == OP_UNARY_NUM_COS) {
            dst_ptr[i0] = (T) cos(x);
        }

        if (FC_OP == OP_UNARY_NUM_LOG) {
            dst_ptr[i0] = (T) log(x);
        }

        if (FC_OP == OP_UNARY_NUM_LEAKY_RELU) {
            dst_ptr[i0] = (T) (TC(x > 0)*x + TC(x <= 0)*(x * args.slope));
        }

        if (FC_OP == OP_UNARY_NUM_TANH) {
            dst_ptr[i0] = (T) precise::tanh(x);
        }

        if (FC_OP == OP_UNARY_NUM_RELU) {
            dst_ptr[i0] = (T) fmax(0, x);
        }

        if (FC_OP == OP_UNARY_NUM_SIGMOID) {
            dst_ptr[i0] = (T) (1 / (1 + exp(-x)));
        }

        if (FC_OP == OP_UNARY_NUM_GELU) {
            dst_ptr[i0] = (T) (0.5*x*(1 + precise::tanh(SQRT_2_OVER_PI*x*(1 + GELU_COEF_A*x*x))));
        }

        if (FC_OP == OP_UNARY_NUM_GELU_ERF) {
            dst_ptr[i0] = (T) (0.5*x*(1 + erf_approx(SQRT_2_INV*x)));
        }

        if (FC_OP == OP_UNARY_NUM_GELU_QUICK) {
            dst_ptr[i0] = (T) (x * (1/(1 + exp(GELU_QUICK_COEF*x))));
        }

        if (FC_OP == OP_UNARY_NUM_SILU) {
            dst_ptr[i0] = (T) (x / (1 + exp(-x)));
        }

        if (FC_OP == OP_UNARY_NUM_ELU) {
            dst_ptr[i0] = (T) elu_approx(x);
        }

        if (FC_OP == OP_UNARY_NUM_NEG) {
            dst_ptr[i0] = (T) -x;
        }

        if (FC_OP == OP_UNARY_NUM_ABS) {
            dst_ptr[i0] = (T) fabs(x);
        }

        if (FC_OP == OP_UNARY_NUM_SGN) {
            dst_ptr[i0] = T(x > 0) - T(x < 0);
        }

        if (FC_OP == OP_UNARY_NUM_STEP) {
            dst_ptr[i0] = T(x > 0);
        }

        if (FC_OP == OP_UNARY_NUM_HARDSWISH) {
            dst_ptr[i0] = (T) (x * fmax(0, fmin(1, x/6 + 0.5)));
        }

        if (FC_OP == OP_UNARY_NUM_HARDSIGMOID) {
            dst_ptr[i0] = (T) fmax(0, fmin(1, x/6 + 0.5));
        }

        if (FC_OP == OP_UNARY_NUM_EXP) {
            dst_ptr[i0] = (T) exp(x);
        }

        if (FC_OP == OP_UNARY_NUM_SOFTPLUS) {
            dst_ptr[i0] = (T) select(log(1 + exp(x)), x, x > 20);
        }

        if (FC_OP == OP_UNARY_NUM_EXPM1) {
            // Metal target profiles used here do not all expose expm1(); this
            // generic unary branch is not used by the DS4 inference graph.
            dst_ptr[i0] = (T) (exp(x) - 1);
        }

        if (FC_OP == OP_UNARY_NUM_FLOOR) {
            dst_ptr[i0] = (T) floor(x);
        }
```<｜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: metal/unary.metal

```metal
if (FC_OP == OP_UNARY_NUM_SQRT) {
            dst_ptr[i0] = (T) sqrt(x);
        }

        if (FC_OP == OP_UNARY_NUM_SIN) {
            dst_ptr[i0] = (T) sin(x);
        }

        if (FC_OP == OP_UNARY_NUM_COS) {
            dst_ptr[i0] = (T) cos(x);
        }

        if (FC_OP == OP_UNARY_NUM_LOG) {
            dst_ptr[i0] = (T) log(x);
        }

        if (FC_OP == OP_UNARY_NUM_LEAKY_RELU) {
            dst_ptr[i0] = (T) (TC(x > 0)*x + TC(x <= 0)*(x * args.slope));
        }

        if (FC_OP == OP_UNARY_NUM_TANH) {
            dst_ptr[i0] = (T) precise::tanh(x);
        }

        if (FC_OP == OP_UNARY_NUM_RELU) {
            dst_ptr[i0] = (T) fmax(0, x);
        }

        if (FC_OP == OP_UNARY_NUM_SIGMOID) {
            dst_ptr[i0] = (T) (1 / (1 + exp(-x)));
        }

        if (FC_OP == OP_UNARY_NUM_GELU) {
            dst_ptr[i0] = (T) (0.5*x*(1 + precise::tanh(SQRT_2_OVER_PI*x*(1 + GELU_COEF_A*x*x))));
        }

        if (FC_OP == OP_UNARY_NUM_GELU_ERF) {
            dst_ptr[i0] = (T) (0.5*x*(1 + erf_approx(SQRT_2_INV*x)));
        }

        if (FC_OP == OP_UNARY_NUM_GELU_QUICK) {
            dst_ptr[i0] = (T) (x * (1/(1 + exp(GELU_QUICK_COEF*x))));
        }

        if (FC_OP == OP_UNARY_NUM_SILU) {
            dst_ptr[i0] = (T) (x / (1 + exp(-x)));
        }

        if (FC_OP == OP_UNARY_NUM_ELU) {
            dst_ptr[i0] = (T) elu_approx(x);
        }

        if (FC_OP == OP_UNARY_NUM_NEG) {
            dst_ptr[i0] = (T) -x;
        }

        if (FC_OP == OP_UNARY_NUM_ABS) {
            dst_ptr[i0] = (T) fabs(x);
        }

        if (FC_OP == OP_UNARY_NUM_SGN) {
            dst_ptr[i0] = T(x > 0) - T(x < 0);
        }

        if (FC_OP == OP_UNARY_NUM_STEP) {
            dst_ptr[i0] = T(x > 0);
        }

        if (FC_OP == OP_UNARY_NUM_HARDSWISH) {
            dst_ptr[i0] = (T) (x * fmax(0, fmin(1, x/6 + 0.5)));
        }

        if (FC_OP == OP_UNARY_NUM_HARDSIGMOID) {
            dst_ptr[i0] = (T) fmax(0, fmin(1, x/6 + 0.5));
        }

        if (FC_OP == OP_UNARY_NUM_EXP) {
            dst_ptr[i0] = (T) exp(x);
        }

        if (FC_OP == OP_UNARY_NUM_SOFTPLUS) {
            dst_ptr[i0] = (T) select(log(1 + exp(x)), x, x > 20);
        }

        if (FC_OP == OP_UNARY_NUM_EXPM1) {
            // Metal target profiles used here do not all expose expm1(); this
            // generic unary branch is not used by the DS4 inference graph.
            dst_ptr[i0] = (T) (exp(x) - 1);
        }

        if (FC_OP == OP_UNARY_NUM_FLOOR) {
            dst_ptr[i0] = (T) floor(x);
        }
```

<｜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: metal/unary.metal

```metal
if (FC_OP == OP_UNARY_NUM_SQRT) {
            dst_ptr[i0] = (T) sqrt(x);
        }

        if (FC_OP == OP_UNARY_NUM_SIN) {
            dst_ptr[i0] = (T) sin(x);
        }

        if (FC_OP == OP_UNARY_NUM_COS) {
            dst_ptr[i0] = (T) cos(x);
        }

        if (FC_OP == OP_UNARY_NUM_LOG) {
            dst_ptr[i0] = (T) log(x);
        }

        if (FC_OP == OP_UNARY_NUM_LEAKY_RELU) {
            dst_ptr[i0] = (T) (TC(x > 0)*x + TC(x <= 0)*(x * args.slope));
        }

        if (FC_OP == OP_UNARY_NUM_TANH) {
            dst_ptr[i0] = (T) precise::tanh(x);
        }

        if (FC_OP == OP_UNARY_NUM_RELU) {
            dst_ptr[i0] = (T) fmax(0, x);
        }

        if (FC_OP == OP_UNARY_NUM_SIGMOID) {
            dst_ptr[i0] = (T) (1 / (1 + exp(-x)));
        }

        if (FC_OP == OP_UNARY_NUM_GELU) {
            dst_ptr[i0] = (T) (0.5*x*(1 + precise::tanh(SQRT_2_OVER_PI*x*(1 + GELU_COEF_A*x*x))));
        }

        if (FC_OP == OP_UNARY_NUM_GELU_ERF) {
            dst_ptr[i0] = (T) (0.5*x*(1 + erf_approx(SQRT_2_INV*x)));
        }

        if (FC_OP == OP_UNARY_NUM_GELU_QUICK) {
            dst_ptr[i0] = (T) (x * (1/(1 + exp(GELU_QUICK_COEF*x))));
        }

        if (FC_OP == OP_UNARY_NUM_SILU) {
            dst_ptr[i0] = (T) (x / (1 + exp(-x)));
        }

        if (FC_OP == OP_UNARY_NUM_ELU) {
            dst_ptr[i0] = (T) elu_approx(x);
        }

        if (FC_OP == OP_UNARY_NUM_NEG) {
            dst_ptr[i0] = (T) -x;
        }

        if (FC_OP == OP_UNARY_NUM_ABS) {
            dst_ptr[i0] = (T) fabs(x);
        }

        if (FC_OP == OP_UNARY_NUM_SGN) {
            dst_ptr[i0] = T(x > 0) - T(x < 0);
        }

        if (FC_OP == OP_UNARY_NUM_STEP) {
            dst_ptr[i0] = T(x > 0);
        }

        if (FC_OP == OP_UNARY_NUM_HARDSWISH) {
            dst_ptr[i0] = (T) (x * fmax(0, fmin(1, x/6 + 0.5)));
        }

        if (FC_OP == OP_UNARY_NUM_HARDSIGMOID) {
            dst_ptr[i0] = (T) fmax(0, fmin(1, x/6 + 0.5));
        }

        if (FC_OP == OP_UNARY_NUM_EXP) {
            dst_ptr[i0] = (T) exp(x);
        }

        if (FC_OP == OP_UNARY_NUM_SOFTPLUS) {
            dst_ptr[i0] = (T) select(log(1 + exp(x)), x, x > 20);
        }

        if (FC_OP == OP_UNARY_NUM_EXPM1) {
            // Metal target profiles used here do not all expose expm1(); this
            // generic unary branch is not used by the DS4 inference graph.
            dst_ptr[i0] = (T) (exp(x) - 1);
        }

        if (FC_OP == OP_UNARY_NUM_FLOOR) {
            dst_ptr[i0] = (T) floor(x);
        }
```<｜Assistant｜><think>