Revert "cuda : add softcap fusion (ggml-org#14907)"

Author: Nexesenex

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

@@ -35,7 +35,6 @@ bool g_mul_mat_q = true;
 #include "ggml-cuda/rope.cuh"
 #include "ggml-cuda/roll.cuh"
 #include "ggml-cuda/scale.cuh"
-#include "ggml-cuda/softcap.cuh"
 #include "ggml-cuda/softmax.cuh"
 #include "ggml-cuda/ssm-conv.cuh"
 #include "ggml-cuda/ssm-scan.cuh"
@@ -2776,12 +2775,7 @@ static void update_cuda_graph_executable(ggml_backend_cuda_context * cuda_ctx) {
 }
 #endif
 
-static bool ggml_cuda_can_fuse(const struct ggml_cgraph * cgraph, int node_idx, std::initializer_list<enum ggml_op> ops, std::initializer_list<enum ggml_unary_op> unary_ops) {
-#ifndef NDEBUG
-    const size_t num_unary = std::count(ops.begin(), ops.end(), GGML_OP_UNARY);
-    GGML_ASSERT(unary_ops.size() == num_unary);
-#endif
-
+static bool ggml_cuda_can_fuse(const struct ggml_cgraph * cgraph, int node_idx, std::initializer_list<enum ggml_op> ops) {
     if (!ggml_can_fuse(cgraph, node_idx, ops)) {
         return false;
     }
@@ -2809,32 +2803,9 @@ static bool ggml_cuda_can_fuse(const struct ggml_cgraph * cgraph, int node_idx,
         if (!ggml_is_contiguous_rows(mul->src[0]) || !ggml_is_contiguous_rows(mul->src[1])) {
             return false;
         }
-
-        return true;
-    }
-
-    if (ops.size() == 3 && ops.begin()[0] == GGML_OP_SCALE && ops.begin()[1] == GGML_OP_UNARY && ops.begin()[2] == GGML_OP_SCALE
-     && unary_ops.size() == 1 && unary_ops.begin()[0] == GGML_UNARY_OP_TANH) {
-        const ggml_tensor *scale  = cgraph->nodes[node_idx];
-        const ggml_tensor *tanh   = cgraph->nodes[node_idx+1];
-        const ggml_tensor *scale2 = cgraph->nodes[node_idx+2];
-
-        GGML_ASSERT(scale->src[0]->type == GGML_TYPE_F32);
-        GGML_ASSERT(scale->type == GGML_TYPE_F32);
-
-        if (ggml_get_unary_op(tanh) != GGML_UNARY_OP_TANH) {
-            return false;
-        }
-
-        // Check for bias
-        if (ggml_get_op_params_f32(scale, 1) != 0.0f || ggml_get_op_params_f32(scale2, 1) != 0.0f) {
-            return false;
-        }
-
-        return true;
     }
 
-    return false;
+    return true;
 }
 
 static void evaluate_and_capture_cuda_graph(ggml_backend_cuda_context * cuda_ctx, ggml_cgraph * cgraph,
@@ -2855,18 +2826,10 @@ static void evaluate_and_capture_cuda_graph(ggml_backend_cuda_context * cuda_ctx
                 }
 
                 static bool disable_fusion = (getenv("GGML_CUDA_DISABLE_FUSION") != nullptr);
-                if (!disable_fusion) {
-                    if (ggml_cuda_can_fuse(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL }, {})) {
-                        ggml_cuda_op_rms_norm_fused(*cuda_ctx, node, cgraph->nodes[i+1]);
-                        i++;
-                        continue;
-                    }
-
-                    if (ggml_cuda_can_fuse(cgraph, i, { GGML_OP_SCALE, GGML_OP_UNARY, GGML_OP_SCALE }, { GGML_UNARY_OP_TANH })) {
-                        i += 2;
-                        ggml_cuda_op_softcap(*cuda_ctx, cgraph->nodes[i], node);
-                        continue;
-                    }
+                if (!disable_fusion && ggml_cuda_can_fuse(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL })) {
+                    ggml_cuda_op_rms_norm_fused(*cuda_ctx, node, cgraph->nodes[i+1]);
+                    i++;
+                    continue;
                 }
 #ifndef NDEBUG
                 assert(node->buffer->buft == ggml_backend_cuda_buffer_type(cuda_ctx->device));