Revert "CUDA: add expert reduce kernel (#16857)" (#17100)

Author: am17an

ggml/src/ggml-cuda/ggml-cuda.cu

@@ -27,7 +27,6 @@
 #include "ggml-cuda/mmq.cuh"
 #include "ggml-cuda/mmvf.cuh"
 #include "ggml-cuda/mmvq.cuh"
-#include "ggml-cuda/moe-expert-reduce.cuh"
 #include "ggml-cuda/norm.cuh"
 #include "ggml-cuda/opt-step-adamw.cuh"
 #include "ggml-cuda/opt-step-sgd.cuh"
@@ -3197,31 +3196,6 @@ static void evaluate_and_capture_cuda_graph(ggml_backend_cuda_context * cuda_ctx
                         continue;
                     }
 
-                    if (node->op == GGML_OP_MUL) {
-                        int current_node = i + 1;
-                        int num_views    = 0;
-                        int num_adds     = 0;
-                        while (current_node < cgraph->n_nodes && cgraph->nodes[current_node]->op == GGML_OP_VIEW) {
-                            num_views++;
-                            current_node++;
-                        }
-
-                        while (current_node < cgraph->n_nodes && cgraph->nodes[current_node]->op == GGML_OP_ADD &&
-                                num_adds < num_views - 1) {
-                            num_adds++;
-                            current_node++;
-                        }
-
-                        if (num_adds == num_views - 1 && num_views > 0) {
-                            ggml_tensor * dst_node = cgraph->nodes[current_node - 1];
-                            if (ggml_cuda_should_use_moe_expert_reduce(cgraph, i, current_node)) {
-                                ggml_cuda_op_moe_expert_reduce(*cuda_ctx, node->src[0], node->src[1], dst_node);
-                                i += num_views + num_adds;
-                                continue;
-                            }
-                        }
-                    }
-
                     if (node->op == GGML_OP_ADD) {
                         int n_fuse = 0;
                         ggml_op ops[8];

ggml/src/ggml-cuda/moe-expert-reduce.cu

@@ -4882,60 +4882,6 @@ struct test_topk_moe: public test_case {
     }
 };
 
-struct test_moe_expert_reduce : public test_case {
-    const int64_t n_embd;
-    const int64_t n_tokens;
-    const int64_t n_expert_used;
-
-    test_moe_expert_reduce(int64_t n_embd = 64, int64_t n_tokens = 5, int64_t n_expert_used = 4)
-        : n_embd(n_embd), n_tokens(n_tokens), n_expert_used(n_expert_used) {
-        GGML_ASSERT(n_expert_used > 1);
-    }
-
-    std::string vars() override {
-        return VARS_TO_STR3(n_embd, n_tokens, n_expert_used);
-    }
-
-    std::string op_desc(ggml_tensor * t) override {
-        GGML_UNUSED(t);
-        return "MOE_EXPERT_REDUCE";
-    }
-
-    bool run_whole_graph() override { return true; }
-
-    ggml_tensor * build_graph(ggml_context * ctx) override {
-        ggml_tensor * experts = ggml_new_tensor_3d(ctx, GGML_TYPE_F32, n_embd, n_expert_used, n_tokens);
-        ggml_set_name(experts, "experts");
-
-        ggml_tensor * weights = ggml_new_tensor_3d(ctx, GGML_TYPE_F32, 1, n_expert_used, n_tokens);
-        ggml_set_name(weights, "weights");
-
-        ggml_tensor * weighted = ggml_mul(ctx, experts, weights);
-        ggml_set_name(weighted, "weighted_experts");
-
-        std::vector<ggml_tensor *> expert_views(n_expert_used);
-        for (int64_t i = 0; i < n_expert_used; ++i) {
-            expert_views[i] = ggml_view_2d(ctx, weighted, n_embd, n_tokens, weighted->nb[2], i * weighted->nb[1]);
-
-            std::string name = "expert_view_" + std::to_string(i);
-            ggml_set_name(expert_views[i], name.c_str());
-            ggml_build_forward_expand(gf, expert_views[i]);
-        }
-
-        ggml_tensor * moe_out = expert_views[0];
-        for (int64_t i = 1; i < n_expert_used; ++i) {
-            moe_out = ggml_add(ctx, moe_out, expert_views[i]);
-
-            std::string name = "expert_add_" + std::to_string(i - 1);
-            ggml_set_name(moe_out, name.c_str());
-        }
-
-        ggml_set_name(moe_out, "moe_out");
-
-        return moe_out;
-    }
-};
-
 struct test_mul_mat_vec_fusion : public test_case {
     const ggml_type type;
     const ggml_glu_op glu_op;
@@ -7415,10 +7361,6 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
     test_cases.emplace_back(new test_topk_moe({ 8, 22, 1, 1 }, 4, /*with_norm*/ false, /*delayed_softmax*/ true));
     test_cases.emplace_back(new test_topk_moe({ 32, 22, 1, 1 }, 8, /*with_norm*/ false, /*delayed_softmax*/ true));
 
-    test_cases.emplace_back(new test_moe_expert_reduce(1024, 5, 4));
-    test_cases.emplace_back(new test_moe_expert_reduce(80, 3, 6));
-    test_cases.emplace_back(new test_moe_expert_reduce(80, 3, 7));
-
 #if 0
     // these tests are disabled to save execution time, sbut they can be handy for debugging
     test_cases.emplace_back(new test_llama(2, true));