ggml : add ggml_top_k (#17365)
* ggml : add ggml_top_k * cont : add ggml_argsort_top_k * metal : add top_k support * ggml : cleanup * tests : add virtual err() function for test_case * ggml : add comments
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@@ -7794,7 +7794,7 @@ void ggml_compute_forward_timestep_embedding(
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// ggml_compute_forward_argsort
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template<enum ggml_sort_order order>
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struct argsort_cmp {
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struct cmp_argsort {
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const float * data;
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bool operator()(int32_t a, int32_t b) const {
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if constexpr (order == GGML_SORT_ORDER_ASC) {
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@@ -7833,11 +7833,11 @@ static void ggml_compute_forward_argsort_f32(
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switch (order) {
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case GGML_SORT_ORDER_ASC:
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std::sort(dst_data, dst_data + ne0, argsort_cmp<GGML_SORT_ORDER_ASC>{src_data});
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std::sort(dst_data, dst_data + ne0, cmp_argsort<GGML_SORT_ORDER_ASC>{src_data});
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break;
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case GGML_SORT_ORDER_DESC:
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std::sort(dst_data, dst_data + ne0, argsort_cmp<GGML_SORT_ORDER_DESC>{src_data});
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std::sort(dst_data, dst_data + ne0, cmp_argsort<GGML_SORT_ORDER_DESC>{src_data});
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break;
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default:
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@@ -7864,6 +7864,72 @@ void ggml_compute_forward_argsort(
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}
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}
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// ggml_compute_forward_top_k
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struct cmp_top_k {
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const float * data;
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bool operator()(int32_t a, int32_t b) const {
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return data[a] > data[b];
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}
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};
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static void ggml_compute_forward_top_k_f32(
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const ggml_compute_params * params,
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ggml_tensor * dst) {
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const ggml_tensor * src0 = dst->src[0];
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GGML_TENSOR_UNARY_OP_LOCALS
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GGML_ASSERT(nb0 == sizeof(float));
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const int ith = params->ith;
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const int nth = params->nth;
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const int64_t nr = ggml_nrows(src0);
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const int top_k = ne0;
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int32_t * tmp = (int32_t *) params->wdata + (ne00 + CACHE_LINE_SIZE_F32) * ith;
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for (int64_t i = ith; i < nr; i += nth) {
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const float * src_data = (float *)((char *) src0->data + i*nb01);
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for (int64_t j = 0; j < ne00; j++) {
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tmp[j] = j;
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}
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std::partial_sort(tmp, tmp + top_k, tmp + ne00, cmp_top_k{src_data});
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int32_t * dst_data = (int32_t *)((char *) dst->data + i*nb1);
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std::copy(tmp, tmp + top_k, dst_data);
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// emphasize that the order is not important
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if (top_k > 1) {
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std::swap(dst_data[0], dst_data[1]);
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}
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}
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}
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void ggml_compute_forward_top_k(
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const ggml_compute_params * params,
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ggml_tensor * dst) {
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const ggml_tensor * src0 = dst->src[0];
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switch (src0->type) {
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case GGML_TYPE_F32:
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{
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ggml_compute_forward_top_k_f32(params, dst);
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} break;
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default:
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{
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GGML_ABORT("fatal error");
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}
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}
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}
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// ggml_compute_forward_flash_attn_ext
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static void ggml_compute_forward_flash_attn_ext_f16_one_chunk(
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