[GPU] Added tests for LoRA with empty adapters and handling of incorr…

…ect fusings

src/plugins/intel_gpu/src/graph/graph_optimizer/prepare_primitive_fusing.cpp

@@ -1048,17 +1048,25 @@ void prepare_primitive_fusing::fuse_simple_primitives(program &p) {
                 std::swap(fused_idx, peer_idx);
             }
 
+            auto fused_node = parents[fused_idx].first;
+            auto peer_node = parents[peer_idx].first;
+
             // Avoid fusing with GEMM from the LoRA pattern, that can be optimized in case of empty adapters
-            if (parents[fused_idx].first->is_type<gemm>()) {
-                if (parents[peer_idx].first->is_type<fully_connected>() ||
-                    (parents[peer_idx].first->is_type<crop>() &&
-                     parents[peer_idx].first->get_dependency(0).is_type<fully_connected>())) {
-                    std::swap(fused_idx, peer_idx);
+            if (fused_node->is_type<gemm>()) {
+                bool is_fc_lora = peer_node->is_type<fully_connected>() ||
+                                  (peer_node->is_type<crop>() &&
+                                   peer_node->get_dependency(0).is_type<fully_connected>());
+
+                bool is_conv_lora = peer_node->is_type<convolution>();
+
+                bool is_gemm_lora = peer_node->is_type<gemm>() &&
+                                    fused_node->get_input_pshape().rbegin()->is_dynamic();
+
+                if (is_fc_lora || is_conv_lora || is_gemm_lora) {
+                    std::swap(peer_node, fused_node);
                 }
             }
 
-            auto fused_node = parents[fused_idx].first;
-            auto peer_node = parents[peer_idx].first;
             if (lo.get_optimization_attributes().use_onednn_impls && lo.is_primitive_implemented_for_onednn(*fused_node)) {
                 auto eltw_in_size = peer_node->get_output_layout();
                 if (eltw_in_size.is_dynamic()

src/plugins/intel_gpu/src/graph/input_layout.cpp

@@ -37,7 +37,11 @@ input_layout_inst::typed_primitive_inst(network& network, input_layout_node cons
 event::ptr input_layout_inst::set_data(memory::ptr mem) {
     auto ol = get_node_output_layout();
 
-    check_memory_to_set(*mem, ol);
+    bool empty_mem = mem->size() == 0 && (ol.is_dynamic() || ol.count() == 0);
+    if (!empty_mem) {
+        check_memory_to_set(*mem, ol);
+    }
+
     event::ptr ev = nullptr;
     auto& engine = get_network().get_engine();
     auto& stream = get_network().get_stream();

src/plugins/intel_gpu/src/graph/primitive_inst.cpp

@@ -1553,8 +1553,13 @@ event::ptr primitive_inst::execute(const std::vector<event::ptr>& events) {
                     auto allocated_mem = d.first->output_memory_ptr();
                     auto actual_input_layout = d.first->get_output_layout();
                     auto& engine = _network.get_engine();
+                    cldnn::memory_ptr actual_mem = nullptr;
                     // Need to use actual layout, not the fake aligned memory layout
-                    auto actual_mem = engine.reinterpret_buffer(*allocated_mem, actual_input_layout);
+                    if (actual_input_layout.count() != 0) {
+                        actual_mem = engine.reinterpret_buffer(*allocated_mem, actual_input_layout);
+                    } else {
+                        actual_mem = engine.allocate_memory(actual_input_layout);
+                    }
                     subgraph->set_input_data(d.first->id(), std::move(actual_mem));
                 }
             }
@@ -2324,6 +2329,13 @@ bool primitive_inst::is_valid_fusion() const {
     if (fused_eltwise_prims.empty())
         return true;
 
+    if (_node->is_type<fully_connected>() || _node->is_type<gemm>() || _node->is_type<convolution>()) {
+        if (_impl_params->input_layouts[0].count() == 0 ||
+            _impl_params->input_layouts[1].count() == 0) {
+            return false;
+        }
+    }
+
     if (_node->is_type<fully_connected>() && _node->get_preferred_impl_type() == impl_types::ocl) {
         // TODO: Only fc_bf_tiled_kernel & ref kernel are verified for fused eltwise. To support more fc kernels for eltwise fusion
         if (!_node->get_selected_impl())

src/plugins/intel_gpu/tests/functional/shared_tests_instances/subgraph_tests/lora_pattern.cpp

@@ -0,0 +1,21 @@
+// Copyright (C) 2024 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "subgraph_tests/lora_pattern.hpp"
+
+using namespace ov::test;
+
+namespace {
+
+INSTANTIATE_TEST_SUITE_P(smoke,
+                         LoraPatternConvolution,
+                         ::testing::Values(ov::test::utils::DEVICE_GPU),
+                         LoraPatternBase::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke,
+                         LoraPatternMatmul,
+                         ::testing::Values(ov::test::utils::DEVICE_GPU),
+                         LoraPatternBase::getTestCaseName);
+
+}  // namespace