ggml: add SWIGLU_CLAMP (#27930)
* ggml: add SWIGLU_CLAMP * add vulkan shader
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@@ -211,6 +211,50 @@ void ggml_cann_swiglu(ggml_backend_cann_context & ctx, ggml_tensor * dst) {
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GGML_CANN_CALL_ACLNN_OP(ctx, SwiGlu, acl_src.get(), (int64_t)2, acl_dst.get());
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}
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void ggml_cann_swiglu_clamp(ggml_backend_cann_context & ctx, ggml_tensor * dst) {
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ggml_tensor * src0 = dst->src[0];
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ggml_tensor * src1 = dst->src[1];
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GGML_ASSERT(ggml_is_contiguous_1(src0));
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GGML_ASSERT(ggml_is_contiguous_1(dst));
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const int32_t swapped = ggml_get_op_params_i32(dst, 1);
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acl_tensor_ptr acl_gate;
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acl_tensor_ptr acl_up;
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if (src1) {
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GGML_ASSERT(ggml_is_contiguous_1(src1));
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GGML_ASSERT(src0->type == src1->type);
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acl_gate = ggml_cann_create_tensor(src0);
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acl_up = ggml_cann_create_tensor(src1);
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} else {
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int64_t ne[] = { src0->ne[0] / 2, src0->ne[1], src0->ne[2], src0->ne[3] };
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size_t nb[] = { src0->nb[0], src0->nb[1], src0->nb[2], src0->nb[3] };
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acl_gate = ggml_cann_create_tensor(src0, ne, nb, GGML_MAX_DIMS, ACL_FORMAT_ND, 0);
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acl_up = ggml_cann_create_tensor(src0, ne, nb, GGML_MAX_DIMS, ACL_FORMAT_ND, ne[0] * ggml_element_size(src0));
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if (swapped) {
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std::swap(acl_gate, acl_up);
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}
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}
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ggml_cann_pool_alloc temp_alloc(ctx.pool(), ggml_nbytes(dst));
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acl_tensor_ptr acl_temp = ggml_cann_create_tensor(temp_alloc.get(), ggml_cann_type_mapping(dst->type),
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ggml_element_size(dst), dst->ne, dst->nb, GGML_MAX_DIMS);
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acl_tensor_ptr acl_dst = ggml_cann_create_tensor(dst);
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const float limit = ggml_get_op_params_f32(dst, 3);
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float min_gate = -INFINITY;
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float min_up = -limit;
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float max_value = limit;
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acl_scalar_ptr acl_min_gate = ggml_cann_create_scalar(&min_gate, ACL_FLOAT);
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acl_scalar_ptr acl_min_up = ggml_cann_create_scalar(&min_up, ACL_FLOAT);
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acl_scalar_ptr acl_limit = ggml_cann_create_scalar(&max_value, ACL_FLOAT);
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GGML_CANN_CALL_ACLNN_OP(ctx, Clamp, acl_gate.get(), acl_min_gate.get(), acl_limit.get(), acl_temp.get());
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GGML_CANN_CALL_ACLNN_OP(ctx, Silu, acl_temp.get(), acl_dst.get());
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GGML_CANN_CALL_ACLNN_OP(ctx, Clamp, acl_up.get(), acl_min_up.get(), acl_limit.get(), acl_temp.get());
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GGML_CANN_CALL_ACLNN_OP(ctx, InplaceMul, acl_dst.get(), acl_temp.get());
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}
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// Fused GeGLU using aclnnGeGluV3: splits input along ne[0] (CANN last dim),
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// activates the LEFT half with GELU, multiplies by right half.
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// approximate: 0=tanh, 1=none(erf). activateLeft=true matches GGML convention.
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@@ -4433,4 +4477,3 @@ void ggml_cann_gated_linear_attn(ggml_backend_cann_context & ctx, ggml_tensor *
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}
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}
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}
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@@ -76,6 +76,7 @@
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void ggml_cann_repeat(ggml_backend_cann_context & ctx, ggml_tensor * dst);
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void ggml_cann_swiglu(ggml_backend_cann_context & ctx, ggml_tensor * dst);
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void ggml_cann_swiglu_clamp(ggml_backend_cann_context & ctx, ggml_tensor * dst);
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void ggml_cann_geglu(ggml_backend_cann_context & ctx, ggml_tensor * dst, int64_t approximate);
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/**
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@@ -1872,6 +1872,9 @@ static bool ggml_cann_compute_forward(ggml_backend_cann_context & ctx, struct gg
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case GGML_GLU_OP_SWIGLU:
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ggml_cann_swiglu(ctx, dst);
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break;
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case GGML_GLU_OP_SWIGLU_CLAMP:
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ggml_cann_swiglu_clamp(ctx, dst);
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break;
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case GGML_GLU_OP_GEGLU_QUICK:
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ggml_cann_geglu_quick(ctx, dst);
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break;
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@@ -2428,6 +2431,7 @@ static bool ggml_backend_cann_supports_op(ggml_backend_dev_t dev, const ggml_ten
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case GGML_GLU_OP_SWIGLU:
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case GGML_GLU_OP_GEGLU_ERF:
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case GGML_GLU_OP_GEGLU_QUICK:
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case GGML_GLU_OP_SWIGLU_CLAMP:
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return true;
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default:
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return false;
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