cl_kernel kernel_gelu_quick, kernel_gelu_quick_4;
cl_kernel kernel_relu;
cl_kernel kernel_sigmoid_f32, kernel_sigmoid_f16;
+ cl_kernel kernel_fill;
cl_kernel kernel_clamp;
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;
GGML_LOG_CONT(".");
}
+ // fill
+ {
+#ifdef GGML_OPENCL_EMBED_KERNELS
+ const std::string kernel_src {
+ #include "fill.cl.h"
+ };
+#else
+ const std::string kernel_src = read_file("fill.cl");
+#endif
+ cl_program prog =
+ build_program_from_source(backend_ctx->context, backend_ctx->device, kernel_src.c_str(), compile_opts);
+
+ CL_CHECK((backend_ctx->kernel_fill = clCreateKernel(prog, "kernel_fill_f32", &err), err));
+ GGML_LOG_CONT(".");
+
+ CL_CHECK(clReleaseProgram(prog));
+ }
+
// clamp
{
#ifdef GGML_OPENCL_EMBED_KERNELS
default:
return false;
}
+ case GGML_OP_FILL:
+ return op->type == GGML_TYPE_F32 && ggml_is_contiguous(op);
case GGML_OP_CLAMP:
return op->src[0]->type == GGML_TYPE_F32;
case GGML_OP_SOFT_MAX:
backend_ctx->enqueue_ndrange_kernel(kernel, 3, global_work_size, local_work_size_ptr, dst);
}
+static void ggml_cl_fill(ggml_backend_t backend, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
+ GGML_ASSERT(dst);
+ GGML_ASSERT(dst->extra);
+
+ UNUSED(src0);
+ UNUSED(src1);
+
+ ggml_backend_opencl_context *backend_ctx = (ggml_backend_opencl_context *)backend->context;
+
+ ggml_tensor_extra_cl * extrad = (ggml_tensor_extra_cl *)dst->extra;
+ cl_ulong offsetd = extrad->offset + dst->view_offs;
+
+ float v = 0.0f;
+ memcpy(&v, ((int32_t *) dst->op_params), sizeof(float));
+
+ const int64_t n = ggml_nelements(dst);
+
+ cl_kernel kernel = backend_ctx->kernel_fill;
+
+ CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &extrad->data_device));
+ CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_ulong), &offsetd));
+ CL_CHECK(clSetKernelArg(kernel, 2, sizeof(float), &v));
+ CL_CHECK(clSetKernelArg(kernel, 3, sizeof(float), &n));
+
+ size_t local_work_size[1] = { 256 };
+ size_t global_work_size[1] = { ((size_t)n + local_work_size[0] - 1) / local_work_size[0] * local_work_size[0] };
+
+ backend_ctx->enqueue_ndrange_kernel(kernel, 1, global_work_size, local_work_size, dst);
+}
+
static void ggml_cl_clamp(ggml_backend_t backend, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
GGML_ASSERT(src0);
GGML_ASSERT(src0->extra);
}
func = ggml_cl_glu;
break;
+ case GGML_OP_FILL:
+ if (!any_on_device) {
+ return false;
+ }
+ func = ggml_cl_fill;
+ break;
case GGML_OP_CLAMP:
if (!any_on_device) {
return false;