[GPU] Moved RMSFusion higher in pipeline and added output type fuse

src/common/transformations/include/ov_ops/rms.hpp

@@ -43,6 +43,12 @@ class TRANSFORMATIONS_API RMS : public ov::op::Op {
         m_epsilon = epsilon;
     }
 
+    void set_output_type(const element::Type& output_type) {
+        m_output_type = output_type;
+    }
+    // Overload collision with method on Node
+    using Node::set_output_type;
+
 private:
     double m_epsilon{0};
     ov::element::Type m_output_type;

src/common/transformations/src/transformations/convert_precision.cpp

@@ -12,6 +12,7 @@
 #include "openvino/pass/constant_folding.hpp"
 #include "openvino/pass/manager.hpp"
 #include "openvino/reference/convert.hpp"
+#include "ov_ops/rms.hpp"
 #include "ov_ops/type_relaxed.hpp"
 #include "transformations/fp16_compression/align_mixed_fp32_fp16_types.hpp"
 #include "transformations/fp16_compression/mark_decompression_convert_constant_folding.hpp"
@@ -59,6 +60,7 @@ bool fuse_type_to_maxpool(const std::shared_ptr<ov::Node>& node, const precision
 bool fuse_type_to_nonzero(const std::shared_ptr<ov::Node>& node, const precisions_map& precisions);
 bool fuse_type_to_bucketize(const std::shared_ptr<ov::Node>& node, const precisions_map& precisions);
 bool fuse_type_to_ctc_greedy_decoder_seq_len(const std::shared_ptr<ov::Node>& node, const precisions_map& precisions);
+bool fuse_type_to_rms(const std::shared_ptr<ov::Node>& node, const precisions_map& precisions);
 
 bool fuse_type_to_random_uniform_v8(const std::shared_ptr<ov::Node>& node, const precisions_map& precisions);
 
@@ -465,7 +467,8 @@ bool ov::pass::ConvertPrecision::run_on_model(const std::shared_ptr<ov::Model>&
         {ov::op::v0::PriorBox::get_type_info_static(), fuse_type_to_prior_box<ov::op::v0::PriorBox>},
         {ov::op::v8::PriorBox::get_type_info_static(), fuse_type_to_prior_box<ov::op::v8::PriorBox>},
         {ov::op::v0::PriorBoxClustered::get_type_info_static(), fuse_type_to_prior_box<ov::op::v0::PriorBoxClustered>},
-        {ov::op::v15::SearchSorted::get_type_info_static(), fuse_type_to_search_sorted_v15}};
+        {ov::op::v15::SearchSorted::get_type_info_static(), fuse_type_to_search_sorted_v15},
+        {ov::op::internal::RMS::get_type_info_static(), fuse_type_to_rms}};
 
     for (const auto& it : m_additional_type_to_fuse_map) {
         type_to_fuse[it.first] = it.second;
@@ -858,6 +861,20 @@ bool fuse_type_to_nms_rotated(const std::shared_ptr<ov::Node>& node, const preci
     return res;
 }
 
+bool fuse_type_to_rms(const std::shared_ptr<ov::Node>& node, const precisions_map& precisions) {
+    auto it = precisions.find(node->get_output_element_type(0));
+    if (it == precisions.end())
+        return false;
+    const auto& to = it->second;
+    if (auto rms = ov::as_type_ptr<ov::op::internal::RMS>(node)) {
+        if (to.is_real()) {
+            rms->set_output_type(to);
+            return true;
+        }
+    }
+    return false;
+}
+
 namespace {
 
 bool update_type(size_t idx,

src/plugins/intel_gpu/src/plugin/transformations_pipeline.cpp

@@ -107,6 +107,7 @@
 #include "transformations/op_conversions/convert_broadcast3.hpp"
 #include "transformations/op_conversions/convert_deformable_conv_v8_to_v1.hpp"
 #include "transformations/op_conversions/convert_depth_to_space.hpp"
+#include "transformations/op_conversions/convert_divide.hpp"
 #include "transformations/op_conversions/convert_gather_0d.hpp"
 #include "transformations/op_conversions/convert_gather_downgrade.hpp"
 #include "transformations/op_conversions/convert_gelu.hpp"
@@ -338,6 +339,19 @@ void TransformationsPipeline::apply(std::shared_ptr<ov::Model> func) {
             });
         }
 
+        manager.register_pass<ov::pass::ConvertDivideWithConstant>();
+        manager.register_pass<ov::pass::ConvertDivide>();
+
+        pass_config->set_callback<ov::pass::RMSFusion>([=](const_node_ptr& root) -> bool {
+            if (!root->get_input_partial_shape(0).is_static()) {
+                return false;
+            }
+            const auto& gamma_shape = root->get_input_partial_shape(0).to_shape();
+            const int32_t vec_size = 8;
+            return static_cast<int32_t>((gamma_shape.back() / vec_size)) > static_cast<int32_t>(device_info.max_work_group_size);
+        });
+        manager.register_pass<ov::pass::RMSFusion>(false);
+
         const bool keep_precision_sensitive_in_fp32_1 = true;
         const bool convert_input_output_precision = false;
         const bool store_original_precision_as_rt_attribute = true;
@@ -855,16 +869,6 @@ void TransformationsPipeline::apply(std::shared_ptr<ov::Model> func) {
 
         manager.register_pass<ov::pass::ConvertGatherToGatherCompressed>();
         auto pass_config = manager.get_pass_config();
-        pass_config->set_callback<ov::pass::RMSFusion>([=](const_node_ptr& root) -> bool {
-            if (!root->get_input_node_ptr(0)->get_input_partial_shape(0).is_static()) {
-                return false;
-            }
-            const auto& gamma_shape = root->get_input_node_ptr(0)->get_input_partial_shape(0).to_shape();
-            const int32_t vec_size = 8;
-            return static_cast<int32_t>((gamma_shape.back() / vec_size)) > static_cast<int32_t>(device_info.max_work_group_size);
-        });
-
-        manager.register_pass<ov::pass::RMSFusion>();
         manager.register_pass<ov::intel_gpu::KVCacheFusion>();
         manager.register_pass<ov::intel_gpu::FullyConnectedConvertFusion>();
         manager.register_pass<ov::intel_gpu::TransposeFusion>(device_info.supports_immad);
@@ -930,7 +934,6 @@ void TransformationsPipeline::apply(std::shared_ptr<ov::Model> func) {
         GPU_DEBUG_IF(cldnn::debug_configuration::get_instance()->verbose >= 1) {
             manager.register_pass<ov::intel_gpu::PrintModelStatistics>();
         }
-
         manager.run_passes(func);
     }
 }