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Merged
ggerganov merged 5 commits into from
May 21, 2026
+113 −42
Merged

metal : optimize concat kernel and fix set kernel threads #23411

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9c572d7
metal : fix GGML_OP_SET kernel threads
ggerganov May 20, 2026
8e65c88
tests : extend test_cpy to support different src/dst shapes
ggerganov May 20, 2026
dd2bb47
metal : optimize concat kernel with row batching for small widths
ggerganov May 20, 2026
654df98
tests : clean-up
ggerganov May 21, 2026
2776651
tests : refactor CPY shape tests to use dimension permutations
ggerganov May 21, 2026
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19 changes: 15 additions & 4 deletions ggml/src/ggml-metal/ggml-metal-ops.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -564,9 +564,20 @@ int ggml_metal_op_concat(ggml_metal_op_t ctx, int idx) {
ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op->src[1]), 2);
ggml_metal_encoder_set_buffer (enc, ggml_metal_get_buffer_id(op), 3);

const int nth = std::min(1024, ne0);
int nth = std::min(256, ne0);

ggml_metal_encoder_dispatch_threadgroups(enc, ne1, ne2, ne3, nth, 1, 1);
// when rows are small, we can batch them together in a single threadgroup
int nrptg = 1;
if (nth < 256) {
nrptg = std::min((256 + nth - 1) / nth, ne1);
if (nrptg * nth > 256) {
nrptg = 256 / nth;
}
}

const int nw0 = (ne1 + nrptg - 1) / nrptg;

ggml_metal_encoder_dispatch_threadgroups(enc, nw0, ne2, ne3, nth, nrptg, 1);

return 1;
}
Expand Down Expand Up @@ -1786,7 +1797,7 @@ int ggml_metal_op_set(ggml_metal_op_t ctx, int idx) {
nk0 = ne10/ggml_blck_size(op->type);
}

int nth = std::min<int>(nk0, ggml_metal_pipeline_max_theads_per_threadgroup(pipeline));
int nth = std::min<int>(nk0*ne11, 256);

// when rows are small, we can batch them together in a single threadgroup
int nrptg = 1;
Expand All @@ -1797,7 +1808,7 @@ int ggml_metal_op_set(ggml_metal_op_t ctx, int idx) {
nrptg = (nth + nk0 - 1)/nk0;
nth = nk0;

if (nrptg*nth > ggml_metal_pipeline_max_theads_per_threadgroup(pipeline)) {
if (nrptg*nth > 256) {
nrptg--;
}
}
Expand Down
6 changes: 5 additions & 1 deletion ggml/src/ggml-metal/ggml-metal.metal
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Expand Up @@ -7486,7 +7486,11 @@ kernel void kernel_concat(

const int i3 = tgpig.z;
const int i2 = tgpig.y;
const int i1 = tgpig.x;
const int i1 = ntg.y == 1 ? tgpig.x : tgpig.x*ntg.y + tpitg.y;

if (i1 >= args.ne1) {
return;
}

int o[4] = {0, 0, 0, 0};
o[args.dim] = args.dim == 0 ? args.ne00 : (args.dim == 1 ? args.ne01 : (args.dim == 2 ? args.ne02 : args.ne03));
Expand Down
130 changes: 93 additions & 37 deletions tests/test-backend-ops.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -2866,15 +2866,24 @@ struct test_set : public test_case {
struct test_cpy : public test_case {
const ggml_type type_src;
const ggml_type type_dst;
const std::array<int64_t, 4> ne;
const std::array<int64_t, 4> ne_src;
const std::array<int64_t, 4> ne_dst;
const std::array<int64_t, 4> permute_src;
const std::array<int64_t, 4> permute_dst;
bool _src_use_permute;
bool _dst_use_permute;
bool _src_transpose;
bool _use_dst_shape;

std::string vars() override {
return VARS_TO_STR6(type_src, type_dst, ne, permute_src, permute_dst, _src_transpose);
if (_use_dst_shape) {
return VARS_TO_STR7(type_src, type_dst, ne_src, ne_dst, permute_src, permute_dst, _src_transpose);
}
return VARS_TO_STR6(type_src, type_dst, ne_src, permute_src, permute_dst, _src_transpose);
}

int64_t total_elements() const {
return ne_src[0] * ne_src[1] * ne_src[2] * ne_src[3];
}

double max_nmse_err() override {
Expand All @@ -2899,7 +2908,7 @@ struct test_cpy : public test_case {
err_estimate /= 8.0f;
}
err_estimate *= err_estimate;
err_estimate /= (150.0f*150.0f*0.25f)*float(ne[0] * ne[1] * ne[2] * ne[3]);
err_estimate /= (150.0f*150.0f*0.25f)*float(total_elements());
return err_estimate;
}
return 1e-6;
Expand All @@ -2910,17 +2919,19 @@ struct test_cpy : public test_case {
}

test_cpy(ggml_type type_src = GGML_TYPE_F32, ggml_type type_dst = GGML_TYPE_F32,
std::array<int64_t, 4> ne = {10, 10, 10, 1},
std::array<int64_t, 4> ne_src = {10, 10, 10, 1},
std::array<int64_t, 4> ne_dst = {-1, -1, -1, -1},
std::array<int64_t, 4> permute_src = {0, 0, 0, 0},
std::array<int64_t, 4> permute_dst = {0, 0, 0, 0},
bool transpose_src = false)
: type_src(type_src), type_dst(type_dst), ne(ne), permute_src(permute_src), permute_dst(permute_dst),
: type_src(type_src), type_dst(type_dst), ne_src(ne_src), ne_dst(ne_dst), permute_src(permute_src), permute_dst(permute_dst),
_src_use_permute(permute_src[0] + permute_src[1] + permute_src[2] + permute_src[3] > 0),
_dst_use_permute(permute_dst[0] + permute_dst[1] + permute_dst[2] + permute_dst[3] > 0),
_src_transpose(transpose_src){}
_src_transpose(transpose_src),
_use_dst_shape(ne_dst[0] >= 0 && ne_dst[1] >= 0 && ne_dst[2] >= 0 && ne_dst[3] >= 0){}

ggml_tensor * build_graph(ggml_context * ctx) override {
ggml_tensor * src = ggml_new_tensor(ctx, type_src, 4, ne.data());
ggml_tensor * src = ggml_new_tensor(ctx, type_src, 4, ne_src.data());
ggml_set_param(src);
ggml_set_name(src, "src");

Expand All @@ -2934,7 +2945,8 @@ struct test_cpy : public test_case {
ggml_set_name(src, "src_transposed");
}

ggml_tensor * dst = ggml_new_tensor(ctx, type_dst, 4, src->ne);
std::array<int64_t, 4> dst_ne = _use_dst_shape ? ne_dst : std::array<int64_t, 4>{src->ne[0], src->ne[1], src->ne[2], src->ne[3]};
ggml_tensor * dst = ggml_new_tensor(ctx, type_dst, 4, dst_ne.data());
ggml_set_name(dst, "dst");

if (_dst_use_permute) {
Expand Down Expand Up @@ -8040,42 +8052,72 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {

for (int k = 1; k < 4; ++k) {
test_cases.emplace_back(new test_cpy(type, type, {k*nk, 2, 3, 4}));
test_cases.emplace_back(new test_cpy(type, type, {k*nk, 2, 3, 4}, {0, 2, 1, 3}));
test_cases.emplace_back(new test_cpy(type, type, {k*nk, 2, 3, 4}, {0, 3, 1, 2}, {0, 2, 1, 3}));
test_cases.emplace_back(new test_cpy(type, type, {k*nk, 2, 3, 4}, {-1,-1,-1,-1}, {0, 2, 1, 3}));
test_cases.emplace_back(new test_cpy(type, type, {k*nk, 2, 3, 4}, {-1,-1,-1,-1}, {0, 3, 1, 2}, {0, 2, 1, 3}));
}
}

for (ggml_type type_src : {GGML_TYPE_F16, GGML_TYPE_BF16, GGML_TYPE_F32}) {
for (ggml_type type_dst : all_types) {
test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 4, 4, 4}));
test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 2, 3, 4}, {0, 2, 1, 3})); // cpy by rows
test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 2, 3, 4}, {-1,-1,-1,-1}, {0, 2, 1, 3})); // cpy by rows
}
}
for (ggml_type type_src : all_types) {
for (ggml_type type_dst : {GGML_TYPE_F32}) {
test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 4, 4, 4}));
test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 2, 3, 4}, {0, 2, 1, 3})); // cpy by rows
test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 2, 3, 4}, {-1,-1,-1,-1}, {0, 2, 1, 3})); // cpy by rows
}
}
for (ggml_type type_src : {GGML_TYPE_F16, GGML_TYPE_F32}) {
for (ggml_type type_dst : {GGML_TYPE_F16, GGML_TYPE_F32}) {
test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 2, 3, 4}, {1, 0, 2, 3})); // cpy not-contiguous
test_cases.emplace_back(new test_cpy(type_src, type_dst, {256, 2, 3, 4}, {-1,-1,-1,-1}, {1, 0, 2, 3})); // cpy not-contiguous
}
}
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_I32, {256, 2, 3, 4}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_I32, {256, 2, 3, 4}, {1, 0, 2, 3}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_I32, {256, 2, 3, 4}, {-1,-1,-1,-1}, {1, 0, 2, 3}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_I32, GGML_TYPE_F32, {256, 2, 3, 4}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_I32, GGML_TYPE_F32, {256, 2, 3, 4}, {1, 0, 2, 3}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F16, GGML_TYPE_F16, {256, 4, 3, 1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {256, 4, 3, 1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {256, 4, 3, 3}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_BF16, GGML_TYPE_BF16, {256, 4, 3, 1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F16, GGML_TYPE_F16, {256, 4, 1, 1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {256, 4, 1, 1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_BF16, GGML_TYPE_BF16, {256, 4, 1, 1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_I32, GGML_TYPE_I32, {256, 4, 1, 1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_I32, GGML_TYPE_I32, {256, 1, 4, 1}, {1, 2, 0, 3}, {0, 0, 0, 0}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {256, 1, 4, 1}, {1, 2, 0, 3}, {0, 0, 0, 0}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_I32, GGML_TYPE_F32, {256, 2, 3, 4}, {-1,-1,-1,-1}, {1, 0, 2, 3}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F16, GGML_TYPE_F16, {256, 4, 3, 1}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {256, 4, 3, 1}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {256, 4, 3, 3}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_BF16, GGML_TYPE_BF16, {256, 4, 3, 1}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F16, GGML_TYPE_F16, {256, 4, 1, 1}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {256, 4, 1, 1}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_BF16, GGML_TYPE_BF16, {256, 4, 1, 1}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_I32, GGML_TYPE_I32, {256, 4, 1, 1}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_I32, GGML_TYPE_I32, {256, 1, 4, 1}, {-1,-1,-1,-1}, {1, 2, 0, 3}, {0, 0, 0, 0}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {256, 1, 4, 1}, {-1,-1,-1,-1}, {1, 2, 0, 3}, {0, 0, 0, 0}));

// CPY - different src/dst shapes (reshaping via CPY)
// Use permutations of {3, 5, 7, 32}. Total elements: 3*5*7*32 = 3360.
// Each src permutation is tested against canonical sorted and reverse dst (skip self).
{
std::array<int64_t, 4> dims = {3, 5, 7, 32};
std::sort(dims.begin(), dims.end());
std::array<int64_t, 4> canonical = dims;
std::array<int64_t, 4> reversed = {32, 7, 5, 3};
for (ggml_type type : {GGML_TYPE_F32, GGML_TYPE_F16}) {
std::array<int64_t, 4> cur = dims;
do {
if (cur != canonical) {
test_cases.emplace_back(new test_cpy(type, type, cur, canonical));
}
if (cur != reversed) {
test_cases.emplace_back(new test_cpy(type, type, cur, reversed));
}
if (cur[0] == 32 && type == GGML_TYPE_F32) {
if (canonical[0] == 32) {
test_cases.emplace_back(new test_cpy(GGML_TYPE_Q4_0, GGML_TYPE_Q4_0, cur, canonical));
}
if (reversed[0] == 32) {
test_cases.emplace_back(new test_cpy(GGML_TYPE_Q4_0, GGML_TYPE_Q4_0, cur, reversed));
}
}
std::next_permutation(cur.begin(), cur.end());
} while (cur != canonical);
}
}

for (ggml_type type_dst : { GGML_TYPE_F32, GGML_TYPE_I32, GGML_TYPE_F16, GGML_TYPE_BF16 }) {
for (bool use_view_slice : { true, false }) {
Expand Down Expand Up @@ -8830,9 +8872,24 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
test_cases.emplace_back(new test_acc(GGML_TYPE_F32, {256, 17, 2, 3}, {256, 16, 2, 3}, 1));
test_cases.emplace_back(new test_acc(GGML_TYPE_F32, {256, 17, 2, 3}, {128, 16, 2, 3}, 2));
test_cases.emplace_back(new test_acc(GGML_TYPE_F32, {256, 17, 2, 3}, {64, 16, 2, 3}, 3));

test_cases.emplace_back(new test_pad());
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {33, 17, 2, 1}, 4, 3, true)); // circular
test_cases.emplace_back(new test_pad_ext());
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {1024, 1, 1, 1}, 1, 0, false));
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {1024, 2, 1, 1}, 1, 0, false));
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {1024, 16, 1, 1}, 0, 1, false));
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {1023, 1, 1, 1}, 1, 0, false));
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {1023, 8, 1, 1}, 1, 0, false));
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {1025, 1, 1, 1}, 1, 0, false));
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {1025, 8, 1, 1}, 1, 0, false));
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {2048, 1, 1, 1}, 1, 0, false));
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {2048, 4, 1, 1}, 1, 0, false));
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {2049, 1, 1, 1}, 1, 0, false));
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {100, 1, 1, 1}, 100, 0, false));
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {100, 1, 1, 1}, 0, 100, false));
test_cases.emplace_back(new test_pad(GGML_TYPE_F32, {100, 100, 1, 1}, 50, 50, false));

test_cases.emplace_back(new test_pad_reflect_1d());
test_cases.emplace_back(new test_pad_reflect_1d(GGML_TYPE_F32, {3000, 384, 4, 1}));
test_cases.emplace_back(new test_roll());
Expand Down Expand Up @@ -9132,22 +9189,21 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_perf() {
test_cases.emplace_back(new test_bin_bcast(ggml_add, GGML_TYPE_F32, {4096, 1, 1, 1}, {1, 512, 1, 1}));

test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F16, {512, 3072, 1, 1}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {8192, 512, 2, 1}, {0, 2, 1, 3}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {3072, 512, 2, 1}, {0, 2, 1, 3}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {8192, 512, 2, 1}, {-1,-1,-1,-1}, {0, 2, 1, 3}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {3072, 512, 2, 1}, {-1,-1,-1,-1}, {0, 2, 1, 3}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_Q4_0, {8192, 512, 2, 1}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_Q4_0, GGML_TYPE_F32, {8192, 512, 2, 1}));

test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {768*1024, 256, 1, 1}, {1, 0, 2, 3}, {0, 0, 0, 0}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F16, GGML_TYPE_F16, {768*1024, 256, 1, 1}, {1, 0, 2, 3}, {0, 0, 0, 0}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F16, GGML_TYPE_F16, {768, 1024, 256, 1}, {1, 0, 2, 3}, {0, 0, 0, 0}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_BF16, GGML_TYPE_BF16, {768, 1024, 256, 1}, {1, 0, 2, 3}, {0, 0, 0, 0}));

test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {768*1024, 256, 1, 1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {768, 1024, 256, 1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F16, GGML_TYPE_F16, {768*1024, 256, 1, 1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F16, GGML_TYPE_F16, {768, 1024, 256, 1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_BF16, GGML_TYPE_BF16, {768, 1024, 256, 1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {768*1024, 256, 1, 1}, {-1,-1,-1,-1}, {1, 0, 2, 3}, {0, 0, 0, 0}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F16, GGML_TYPE_F16, {768*1024, 256, 1, 1}, {-1,-1,-1,-1}, {1, 0, 2, 3}, {0, 0, 0, 0}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F16, GGML_TYPE_F16, {768, 1024, 256, 1}, {-1,-1,-1,-1}, {1, 0, 2, 3}, {0, 0, 0, 0}));
test_cases.emplace_back(new test_cpy(GGML_TYPE_BF16, GGML_TYPE_BF16, {768, 1024, 256, 1}, {-1,-1,-1,-1}, {1, 0, 2, 3}, {0, 0, 0, 0}));

test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {768*1024, 256, 1, 1}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F32, GGML_TYPE_F32, {768, 1024, 256, 1}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F16, GGML_TYPE_F16, {768*1024, 256, 1, 1}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_F16, GGML_TYPE_F16, {768, 1024, 256, 1}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));
test_cases.emplace_back(new test_cpy(GGML_TYPE_BF16, GGML_TYPE_BF16, {768, 1024, 256, 1}, {-1,-1,-1,-1}, {0, 0, 0, 0}, {0, 0, 0, 0}, true));

test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {4096, 4096, 5, 1}, false, false, GGML_TYPE_F32, {1, 1}, 1.0f, 0.0f));
test_cases.emplace_back(new test_soft_max(GGML_TYPE_F32, {12888, 256, 5, 1}, false, false, GGML_TYPE_F32, {1, 1}, 1.0f, 0.0f));
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