ggml-cuda : support ssm_conv kernel size 7 (#30873)

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Tarek Dakhran authored and GitHub committed 2026-10-20 17:47:44 +02:00
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commit 39da130fcd
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@@ -10659,7 +10659,7 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
// ne[2] > 65535 exceeds the CUDA gridDim.y limit (#27901)
test_cases.emplace_back(new test_rms_norm_mul_rope({4, 1, 65536, 1}, 1e-6f, false, false, false, GGML_ROPE_TYPE_NORMAL));
test_cases.emplace_back(new test_rms_norm_mul_rope({4, 1, 65536, 1}, 1e-6f, false, true, false, GGML_ROPE_TYPE_NEOX));
for (int64_t d_conv : {3, 4, 9}) {
for (int64_t d_conv : {3, 4, 7, 9}) {
for (int64_t d_inner: {1024, 1536, 2048}) {
test_cases.emplace_back(new test_ssm_conv(GGML_TYPE_F32, {d_conv, d_inner, 1, 1}, {d_conv, d_inner, 1, 1}));
test_cases.emplace_back(new test_ssm_conv(GGML_TYPE_F32, {2 * d_conv, d_inner, 1, 1}, {d_conv, d_inner, 1, 1}));
@@ -10672,7 +10672,7 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
// fused ssm_conv + (optional) bias_add + silu. The bias-only graph (no silu) is intentionally
// not tested since there's no fusion for that pattern in ggml_cuda_can_fuse.
for (int64_t d_conv : {3, 4, 9}) {
for (int64_t d_conv : {3, 4, 7, 9}) {
for (int64_t d_inner : {1024, 1536, 2048}) {
for (bool fuse_bias : {false, true}) {
// short token path (n_t <= 32)