cl_command_queue queue;
cl_program program_add;
+ cl_program program_add_id;
cl_program program_clamp;
cl_program program_cpy;
cl_program program_cvt;
cl_kernel kernel_mul, kernel_mul_row, kernel_mul_f16, kernel_mul_row_f16;
cl_kernel kernel_div, kernel_div_row, kernel_div_f16, kernel_div_row_f16;
cl_kernel kernel_sub, kernel_sub_row, kernel_sub_f16, kernel_sub_row_f16;
+ cl_kernel kernel_add_id;
cl_kernel kernel_scale;
cl_kernel kernel_silu, kernel_silu_4;
cl_kernel kernel_gelu, kernel_gelu_4;
cl_kernel kernel_relu;
cl_kernel kernel_sigmoid_f32, kernel_sigmoid_f16;
cl_kernel kernel_clamp;
- cl_kernel kernel_geglu, kernel_reglu, kernel_swiglu, kernel_geglu_erf, kernel_geglu_quick,
+ cl_kernel kernel_geglu, kernel_reglu, kernel_swiglu, kernel_swiglu_oai, kernel_geglu_erf, kernel_geglu_quick,
kernel_geglu_f16, kernel_reglu_f16, kernel_swiglu_f16, kernel_geglu_erf_f16, kernel_geglu_quick_f16;
cl_kernel kernel_norm;
cl_kernel kernel_rms_norm, kernel_rms_norm_mul;
GGML_LOG_CONT(".");
}
+ // add_id
+ {
+#ifdef GGML_OPENCL_EMBED_KERNELS
+ const std::string kernel_src {
+ #include "add_id.cl.h"
+ };
+#else
+ const std::string kernel_src = read_file("add_id.cl");
+#endif
+ backend_ctx->program_add_id =
+ build_program_from_source(backend_ctx->context, backend_ctx->device, kernel_src.c_str(), compile_opts);
+
+ CL_CHECK((backend_ctx->kernel_add_id = clCreateKernel(backend_ctx->program_add_id, "kernel_add_id", &err), err));
+ GGML_LOG_CONT(".");
+ }
+
// clamp
{
#ifdef GGML_OPENCL_EMBED_KERNELS
CL_CHECK((backend_ctx->kernel_geglu = clCreateKernel(backend_ctx->program_glu, "kernel_geglu", &err), err));
CL_CHECK((backend_ctx->kernel_reglu = clCreateKernel(backend_ctx->program_glu, "kernel_reglu", &err), err));
CL_CHECK((backend_ctx->kernel_swiglu = clCreateKernel(backend_ctx->program_glu, "kernel_swiglu", &err), err));
+ CL_CHECK((backend_ctx->kernel_swiglu_oai = clCreateKernel(backend_ctx->program_glu, "kernel_swiglu_oai", &err), err));
CL_CHECK((backend_ctx->kernel_geglu_erf = clCreateKernel(backend_ctx->program_glu, "kernel_geglu_erf", &err), err));
CL_CHECK((backend_ctx->kernel_geglu_quick = clCreateKernel(backend_ctx->program_glu, "kernel_geglu_quick", &err), err));
CL_CHECK((backend_ctx->kernel_geglu_f16 = clCreateKernel(backend_ctx->program_glu, "kernel_geglu_f16", &err), err));
return (op->src[0]->type == op->src[1]->type) &&
(op->src[0]->type == op->type) &&
(op->src[0]->type == GGML_TYPE_F32 || op->src[0]->type == GGML_TYPE_F16);
+ case GGML_OP_ADD_ID:
+ return op->src[0]->type == GGML_TYPE_F32;
case GGML_OP_UNARY:
switch (ggml_get_unary_op(op)) {
case GGML_UNARY_OP_GELU:
case GGML_GLU_OP_GEGLU:
case GGML_GLU_OP_REGLU:
case GGML_GLU_OP_SWIGLU:
+ case GGML_GLU_OP_SWIGLU_OAI:
case GGML_GLU_OP_GEGLU_ERF:
case GGML_GLU_OP_GEGLU_QUICK:
return ggml_is_contiguous_1(op->src[0]) && (op->type == GGML_TYPE_F32 || op->type == GGML_TYPE_F16);
}
}
+static void ggml_cl_add_id(ggml_backend_t backend, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
+ GGML_ASSERT(src0);
+ GGML_ASSERT(src0->extra);
+ GGML_ASSERT(src1);
+ GGML_ASSERT(src1->extra);
+ GGML_ASSERT(dst);
+ GGML_ASSERT(dst->extra);
+
+ const ggml_tensor * src2 = dst->src[2];
+ GGML_ASSERT(src2);
+ GGML_ASSERT(src2->extra);
+
+ GGML_ASSERT(src0->type == GGML_TYPE_F32);
+ GGML_ASSERT(src1->type == GGML_TYPE_F32);
+ GGML_ASSERT(src2->type == GGML_TYPE_I32);
+ GGML_ASSERT(dst->type == GGML_TYPE_F32);
+
+ GGML_ASSERT(ggml_is_contiguous_rows(src0));
+
+ const int ne00 = src0->ne[0];
+ const int ne01 = src0->ne[1];
+ const int ne02 = src0->ne[2];
+
+ const cl_ulong nb01 = src0->nb[1];
+ const cl_ulong nb02 = src0->nb[2];
+
+ const cl_ulong nb11 = src1->nb[1];
+
+ const cl_ulong nb21 = src2->nb[1];
+
+ const int ne0 = dst->ne[0];
+ const int ne1 = dst->ne[1];
+
+ ggml_backend_opencl_context *backend_ctx = (ggml_backend_opencl_context *)backend->context;
+
+ ggml_tensor_extra_cl * extra0 = (ggml_tensor_extra_cl *)src0->extra;
+ ggml_tensor_extra_cl * extra1 = (ggml_tensor_extra_cl *)src1->extra;
+ ggml_tensor_extra_cl * extra2 = (ggml_tensor_extra_cl *)src2->extra;
+ ggml_tensor_extra_cl * extrad = (ggml_tensor_extra_cl *)dst->extra;
+
+ cl_ulong offset0 = extra0->offset + src0->view_offs;
+ cl_ulong offset1 = extra1->offset + src1->view_offs;
+ cl_ulong offset2 = extra2->offset + src2->view_offs;
+ cl_ulong offsetd = extrad->offset + dst->view_offs;
+
+ cl_kernel kernel = backend_ctx->kernel_add_id;
+
+ CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &extra0->data_device));
+ CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_ulong), &offset0));
+ CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &extra1->data_device));
+ CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_ulong), &offset1));
+ CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_mem), &extra2->data_device));
+ CL_CHECK(clSetKernelArg(kernel, 5, sizeof(cl_ulong), &offset2));
+ CL_CHECK(clSetKernelArg(kernel, 6, sizeof(cl_mem), &extrad->data_device));
+ CL_CHECK(clSetKernelArg(kernel, 7, sizeof(cl_ulong), &offsetd));
+ CL_CHECK(clSetKernelArg(kernel, 8, sizeof(cl_ulong), &nb01));
+ CL_CHECK(clSetKernelArg(kernel, 9, sizeof(cl_ulong), &nb02));
+ CL_CHECK(clSetKernelArg(kernel, 10, sizeof(cl_ulong), &nb11));
+ CL_CHECK(clSetKernelArg(kernel, 11, sizeof(cl_ulong), &nb21));
+ CL_CHECK(clSetKernelArg(kernel, 12, sizeof(int), &ne0));
+ CL_CHECK(clSetKernelArg(kernel, 13, sizeof(int), &ne1));
+
+ int nth = MIN(ne00, (int) backend_ctx->get_kernel_workgroup_size(kernel));
+ size_t global_work_size[] = { (size_t)ne01*nth, (size_t)ne02, 1 };
+ size_t local_work_size[] = { (size_t)nth, 1, 1 };
+
+ backend_ctx->enqueue_ndrange_kernel(kernel, 3, global_work_size, local_work_size, dst);
+}
+
static void ggml_cl_mul(ggml_backend_t backend, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
GGML_ASSERT(src0);
GGML_ASSERT(src0->extra);
kernel = backend_ctx->kernel_swiglu_f16;
}
break;
+ case GGML_GLU_OP_SWIGLU_OAI:
+ kernel = backend_ctx->kernel_swiglu_oai;
+ break;
case GGML_GLU_OP_GEGLU_ERF:
if (dst->type == GGML_TYPE_F32) {
kernel = backend_ctx->kernel_geglu_erf;
const cl_ulong nb1 = dst->nb[1];
- const int swp = ((const int32_t *) dst->op_params)[1];
+ const int swp = ggml_get_op_params_i32(dst, 1);
+ const float alpha = ggml_get_op_params_f32(dst, 2);
+ const float limit = ggml_get_op_params_f32(dst, 3);
+
const int ne00_off = src1 ? 0 : (swp ? ne0 : 0);
const int ne10_off = src1 ? 0 : (swp ? 0 : ne0);
CL_CHECK(clSetKernelArg(kernel, 10, sizeof(int), &ne00_off));
CL_CHECK(clSetKernelArg(kernel, 11, sizeof(int), &ne10_off));
+ if (ggml_get_glu_op(dst) == GGML_GLU_OP_SWIGLU_OAI) {
+ CL_CHECK(clSetKernelArg(kernel, 12, sizeof(float), &limit));
+ CL_CHECK(clSetKernelArg(kernel, 13, sizeof(float), &alpha));
+ }
+
const size_t nrows = ggml_nrows(src0);
size_t nth = 512;
size_t global_work_size[] = {nrows*nth, 1, 1};
}
func = ggml_cl_add;
break;
+ case GGML_OP_ADD_ID:
+ if (!any_on_device) {
+ return false;
+ }
+ func = ggml_cl_add_id;
+ break;
case GGML_OP_MUL:
if (!any_on_device) {
return false;