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CUDA: skip fusion for repeating adds in bias (#17080)

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This commit is contained in:
Aman Gupta
2025-11-08 16:58:05 +08:00
committed by GitHub
parent b8a5cfd11a
commit c1b187688d
3 changed files with 18 additions and 6 deletions
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10
tests/test-backend-ops.cpp
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@@ -4984,8 +4984,10 @@ struct test_mul_mat_vec_fusion : public test_case {
ggml_tensor * build_graph(ggml_context * ctx) override {
if (!use_id) {
std::array<int64_t, 4> ne = {k, m, 1, 1};
std::array<int64_t, 4> ne0 = {k, n, 1, 1};
const int channels = 4;
const int samples = 2;
std::array<int64_t, 4> ne = { k, m, channels, samples };
std::array<int64_t, 4> ne0 = { k, n, channels, samples };
ggml_tensor * cur = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, ne.data());
ggml_tensor * gate = with_gate ? ggml_new_tensor(ctx, type, 4, ne0.data()) : nullptr;
@@ -4993,14 +4995,14 @@ struct test_mul_mat_vec_fusion : public test_case {
ggml_tensor * ffn_up = ggml_mul_mat(ctx, up, cur);
if (with_bias) {
std::array<int64_t, 4> bias_ne = {ffn_up->ne[0], 1, 1, 1};
std::array<int64_t, 4> bias_ne = { ffn_up->ne[0], 1, channels, samples };
ggml_tensor * up_bias = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, bias_ne.data());
ffn_up = ggml_add(ctx, ffn_up, up_bias);
}
ggml_tensor * ffn_gate = with_gate ? ggml_mul_mat(ctx, gate, cur) : nullptr;
if (with_bias && with_gate) {
std::array<int64_t, 4> bias_ne = {ffn_gate->ne[0], 1, 1, 1};
std::array<int64_t, 4> bias_ne = { ffn_gate->ne[0], 1, channels, samples };
ggml_tensor * gate_bias = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, bias_ne.data());
ffn_gate = ggml_add(ctx, ffn_gate, gate_bias);
}