Merge branch 'master' into as/npuw_parallel_for_improve

src/frontends/tensorflow_common/src/op/expand_dims.cpp

@@ -3,7 +3,13 @@
 //
 
 #include "common_op_table.hpp"
+#include "helper_ops/complex_type_mark.hpp"
+#include "openvino/op/constant.hpp"
+#include "openvino/op/less.hpp"
+#include "openvino/op/select.hpp"
+#include "openvino/op/subtract.hpp"
 #include "openvino/op/unsqueeze.hpp"
+#include "utils.hpp"
 
 using namespace std;
 using namespace ov::op;
@@ -14,9 +20,31 @@ namespace tensorflow {
 namespace op {
 
 OutputVector translate_expand_dims_op(const NodeContext& node) {
-    default_op_checks(node, 2, {"ExpandDims", "EXPAND_DIMS"});
+    default_op_checks(node, 2, {"ExpandDims", "EXPAND_DIMS"}, true);
     auto input = node.get_input(0);
     auto axis = node.get_input(1);
+    auto complex_type_mark = as_type_ptr<ComplexTypeMark>(input.get_node_shared_ptr());
+
+    if (complex_type_mark) {
+        element::Type complex_part_type = complex_type_mark->get_complex_part_type();
+        input = complex_type_mark->input_value(0);
+
+        auto const_zero = create_same_type_const_scalar<int32_t>(axis, 0);
+
+        auto is_axis_neg = make_shared<v1::Less>(axis, const_zero);
+
+        auto const_one = create_same_type_const_scalar<int32_t>(axis, 1);
+        auto axis_min_one = make_shared<v1::Subtract>(axis, const_one);
+
+        auto new_axis = make_shared<v1::Select>(is_axis_neg, axis_min_one, axis);
+
+        auto unsqueeze = make_shared<v0::Unsqueeze>(input, new_axis);
+
+        set_node_name(node.get_name(), unsqueeze);
+        auto complex_result = make_shared<ComplexTypeMark>(unsqueeze, complex_part_type);
+        return {complex_result};
+    }
+
     auto unsqueeze = make_shared<v0::Unsqueeze>(input, axis);
     set_node_name(node.get_name(), unsqueeze);
     return {unsqueeze};

src/plugins/intel_gpu/include/intel_gpu/graph/network.hpp

@@ -4,17 +4,15 @@
 
 #pragma once
 
-#include "openvino/runtime/threading/cpu_streams_executor.hpp"
+#include "openvino/runtime/threading/istreams_executor.hpp"
 
 #include "intel_gpu/graph/topology.hpp"
 #include "intel_gpu/graph/program.hpp"
 #include "intel_gpu/graph/serialization/binary_buffer.hpp"
-#include "intel_gpu/runtime/compounds.hpp"
 #include "intel_gpu/runtime/memory.hpp"
 #include "intel_gpu/runtime/engine.hpp"
 #include "intel_gpu/runtime/event.hpp"
 #include "intel_gpu/runtime/stream.hpp"
-#include "intel_gpu/runtime/lru_cache.hpp"
 #include "intel_gpu/runtime/shape_predictor.hpp"
 #include "intel_gpu/plugin/variable_state.hpp"
 
@@ -211,7 +209,7 @@ struct network {
     bool is_dynamic() const { return _is_dynamic; }
     size_t get_weights_cache_capacity() const { return _weights_cache_capacity; }
 
-    memory_pool& get_memory_pool() {
+    memory_pool& get_memory_pool() const {
         return *_memory_pool;
     }
 
@@ -284,7 +282,9 @@ struct network {
     void dump_memory_pool(std::string dump_path, int64_t curr_iter);
 
 #ifdef GPU_DEBUG_CONFIG
-    int64_t iteration = 0;
+    mutable int64_t iteration = 0;
+    friend class NetworkDebugHelper;
+    friend class NodeDebugHelper;
 #endif
 };
 }  // namespace cldnn