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Ggml/cuda snake fusion hardening (#22912)

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* cuda: tighten snake fusion type checks for all operands (defensive, sync vulkan)

* cuda: reject snake fusion when ne[2] or ne[3] > 1 (mirror vulkan PR review)

* cuda: merge type_ok and types_ok into a single types_ok (address am17an review)

* cuda: filter ADD/SUB/MUL/DIV in supports_op to F32/F16

bin_bcast only dispatches F32/F16 type triplets, mirror the
vulkan filter so unsupported types fall back through cpy
instead of aborting.

* test-backend-ops: extend snake_fuse to rank-4 with ne[2]/ne[3] > 1 cases
This commit is contained in:
Pascal
2026-05-11 18:42:08 +02:00
committed by GitHub
parent ef22b3e4ac
commit e936660760
2 changed files with 39 additions and 17 deletions
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tests/test-backend-ops.cpp
+15 -11
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@@ -3561,7 +3561,7 @@ struct test_relu_sqr : public test_case {
// and dispatches a single fused kernel.
struct test_snake_fuse : public test_case {
const ggml_type type;
const std::array<int64_t, 2> ne; // [T, C]
const std::array<int64_t, 4> ne; // [T, C, D2, D3]
std::string op_desc(ggml_tensor * t) override {
GGML_UNUSED(t);
@@ -3586,11 +3586,11 @@ struct test_snake_fuse : public test_case {
}
test_snake_fuse(ggml_type type = GGML_TYPE_F32,
std::array<int64_t, 2> ne = {256, 192})
std::array<int64_t, 4> ne = {256, 192, 1, 1})
: type(type), ne(ne) {}
ggml_tensor * build_graph(ggml_context * ctx) override {
ggml_tensor * x = ggml_new_tensor_2d(ctx, type, ne[0], ne[1]);
ggml_tensor * x = ggml_new_tensor_4d(ctx, type, ne[0], ne[1], ne[2], ne[3]);
ggml_set_name(x, "x");
ggml_tensor * a = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 1, ne[1]);
@@ -7558,11 +7558,15 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
// SNAKE activation fusion: x + sin(a*x)^2 * inv_b
for (ggml_type type : { GGML_TYPE_F32, GGML_TYPE_F16, GGML_TYPE_BF16 }) {
test_cases.emplace_back(new test_snake_fuse(type, { 5, 7})); // primes sub-block
test_cases.emplace_back(new test_snake_fuse(type, { 33, 32})); // boundary
test_cases.emplace_back(new test_snake_fuse(type, {1025, 13})); // large prime, grid-stride
test_cases.emplace_back(new test_snake_fuse(type, { 128, 16})); // power-of-two
test_cases.emplace_back(new test_snake_fuse(type, { 256, 192})); // BigVGAN-ish
test_cases.emplace_back(new test_snake_fuse(type, { 5, 7, 1, 1})); // primes sub-block
test_cases.emplace_back(new test_snake_fuse(type, { 33, 32, 1, 1})); // boundary
test_cases.emplace_back(new test_snake_fuse(type, {1025, 13, 1, 1})); // large prime, grid-stride
test_cases.emplace_back(new test_snake_fuse(type, { 128, 16, 1, 1})); // power-of-two
test_cases.emplace_back(new test_snake_fuse(type, { 256, 192, 1, 1})); // BigVGAN-ish
// higher-rank shapes: matcher must reject fusion, fallback to naive chain
test_cases.emplace_back(new test_snake_fuse(type, { 64, 32, 2, 1})); // ne[2] > 1
test_cases.emplace_back(new test_snake_fuse(type, { 64, 32, 1, 2})); // ne[3] > 1
test_cases.emplace_back(new test_snake_fuse(type, { 64, 32, 2, 3})); // ne[2] > 1 and ne[3] > 1
}
// glu ops
@@ -9093,9 +9097,9 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_perf() {
test_cases.emplace_back(new test_pad_reflect_1d(GGML_TYPE_F32, {3000, 384, 4, 1}));
// SNAKE activation fusion at BigVGAN scale (T=7680 = 24 kHz x 320 ms, C=192)
test_cases.emplace_back(new test_snake_fuse(GGML_TYPE_F32, {7680, 192}));
test_cases.emplace_back(new test_snake_fuse(GGML_TYPE_F16, {7680, 192}));
test_cases.emplace_back(new test_snake_fuse(GGML_TYPE_BF16, {7680, 192}));
test_cases.emplace_back(new test_snake_fuse(GGML_TYPE_F32, {7680, 192, 1, 1}));
test_cases.emplace_back(new test_snake_fuse(GGML_TYPE_F16, {7680, 192, 1, 1}));
test_cases.emplace_back(new test_snake_fuse(GGML_TYPE_BF16, {7680, 192, 1, 1}));
test_cases.emplace_back(new test_mul_mat(GGML_TYPE_F16, GGML_TYPE_F32, 16416, 1, 128, {8, 1}, {4, 1}, {0, 2, 1, 3}));
test_cases.emplace_back(new test_mul_mat(GGML_TYPE_F16, GGML_TYPE_F32, 128, 1, 16416, {8, 1}, {4, 1}, {0, 1, 2, 3}, 2*16416));