opencl: add FILL op support (#18682)
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5b8844ae53
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568371a726
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@ -57,6 +57,7 @@ set(GGML_OPENCL_KERNELS
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add
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add_id
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argsort
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fill
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clamp
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cpy
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cvt
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@ -489,6 +489,7 @@ struct ggml_backend_opencl_context {
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cl_kernel kernel_gelu_quick, kernel_gelu_quick_4;
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cl_kernel kernel_relu;
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cl_kernel kernel_sigmoid_f32, kernel_sigmoid_f16;
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cl_kernel kernel_fill;
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cl_kernel kernel_clamp;
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cl_kernel kernel_geglu, kernel_reglu, kernel_swiglu, kernel_swiglu_oai, kernel_geglu_erf, kernel_geglu_quick,
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kernel_geglu_f16, kernel_reglu_f16, kernel_swiglu_f16, kernel_geglu_erf_f16, kernel_geglu_quick_f16;
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@ -787,6 +788,24 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx, ggml_cl_ve
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GGML_LOG_CONT(".");
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}
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// fill
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{
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#ifdef GGML_OPENCL_EMBED_KERNELS
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const std::string kernel_src {
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#include "fill.cl.h"
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};
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#else
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const std::string kernel_src = read_file("fill.cl");
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#endif
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cl_program prog =
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build_program_from_source(backend_ctx->context, backend_ctx->device, kernel_src.c_str(), compile_opts);
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CL_CHECK((backend_ctx->kernel_fill = clCreateKernel(prog, "kernel_fill_f32", &err), err));
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GGML_LOG_CONT(".");
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CL_CHECK(clReleaseProgram(prog));
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}
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// clamp
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{
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#ifdef GGML_OPENCL_EMBED_KERNELS
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@ -3104,6 +3123,8 @@ static bool ggml_opencl_supports_op(ggml_backend_dev_t dev, const struct ggml_te
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default:
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return false;
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}
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case GGML_OP_FILL:
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return op->type == GGML_TYPE_F32 && ggml_is_contiguous(op);
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case GGML_OP_CLAMP:
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return op->src[0]->type == GGML_TYPE_F32;
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case GGML_OP_SOFT_MAX:
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@ -5860,6 +5881,36 @@ static void ggml_cl_sigmoid(ggml_backend_t backend, const ggml_tensor * src0, co
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backend_ctx->enqueue_ndrange_kernel(kernel, 3, global_work_size, local_work_size_ptr, dst);
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}
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static void ggml_cl_fill(ggml_backend_t backend, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
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GGML_ASSERT(dst);
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GGML_ASSERT(dst->extra);
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UNUSED(src0);
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UNUSED(src1);
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ggml_backend_opencl_context *backend_ctx = (ggml_backend_opencl_context *)backend->context;
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ggml_tensor_extra_cl * extrad = (ggml_tensor_extra_cl *)dst->extra;
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cl_ulong offsetd = extrad->offset + dst->view_offs;
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float v = 0.0f;
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memcpy(&v, ((int32_t *) dst->op_params), sizeof(float));
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const int64_t n = ggml_nelements(dst);
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cl_kernel kernel = backend_ctx->kernel_fill;
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CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &extrad->data_device));
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CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_ulong), &offsetd));
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CL_CHECK(clSetKernelArg(kernel, 2, sizeof(float), &v));
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CL_CHECK(clSetKernelArg(kernel, 3, sizeof(float), &n));
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size_t local_work_size[1] = { 256 };
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size_t global_work_size[1] = { ((size_t)n + local_work_size[0] - 1) / local_work_size[0] * local_work_size[0] };
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backend_ctx->enqueue_ndrange_kernel(kernel, 1, global_work_size, local_work_size, dst);
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}
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static void ggml_cl_clamp(ggml_backend_t backend, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
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GGML_ASSERT(src0);
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GGML_ASSERT(src0->extra);
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@ -9595,6 +9646,12 @@ bool ggml_cl_compute_forward(ggml_backend_t backend, struct ggml_tensor * tensor
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}
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func = ggml_cl_glu;
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break;
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case GGML_OP_FILL:
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if (!any_on_device) {
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return false;
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}
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func = ggml_cl_fill;
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break;
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case GGML_OP_CLAMP:
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if (!any_on_device) {
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return false;
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@ -0,0 +1,17 @@
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#pragma OPENCL EXTENSION cl_khr_fp16 : enable
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//------------------------------------------------------------------------------
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// fill
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//------------------------------------------------------------------------------
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__kernel void kernel_fill_f32(
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__global float *dst,
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ulong offsetd,
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float v,
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int n
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) {
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dst = (global float*)((global char*)dst + offsetd);
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if(get_global_id(0) < n){
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dst[get_global_id(0)] = v;
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}
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}
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