Update output shape to 4d for static reshape not using new_shape_infer

src/plugins/intel_gpu/src/graph/eltwise.cpp

@@ -396,9 +396,6 @@ eltwise_inst::typed_primitive_inst(network& network, eltwise_node const& node) :
         bool use_new_shape_infer = network.get_config().get_property(ov::intel_gpu::allow_new_shape_infer);
         auto input0_pshape = node.get_input_pshape(0);
 
-        if (!use_new_shape_infer && input0_pshape.size() < 4)
-            input0_pshape.insert(input0_pshape.end(), 4 - input0_pshape.size(), 1);
-
         for (size_t i = 1; i < inputs_count; ++i) {
             auto input_pshape = node.get_input_pshape(i);
 

src/plugins/intel_gpu/src/graph/reshape.cpp

@@ -115,7 +115,11 @@ layout reshape_inst::calc_output_layout(reshape_node const& node, kernel_impl_pa
     if (desc->output_shape.count() == 0) {
         if (desc->output_partial_shape.size() != 0) {
             format out_fmt = format::adjust_to_rank(input_layout.format, desc->output_partial_shape.rank().get_length());
-            return layout{desc->output_partial_shape, input_layout.data_type, out_fmt};
+            auto use_new_shape_infer = node.get_program().is_new_shape_infer();
+            auto output_shape = desc->output_partial_shape;
+            if (!use_new_shape_infer && output_shape.size() < 4)
+                output_shape.insert(output_shape.end(), 4 - output_shape.size(), 1);
+            return layout{output_shape, input_layout.data_type, out_fmt};
         } else {
             OPENVINO_ASSERT("[GPU] Output shape is not provided");
         }

src/plugins/intel_gpu/tests/unit/test_cases/eltwise_gpu_test.cpp

@@ -10,9 +10,11 @@
 #include <intel_gpu/primitives/eltwise.hpp>
 #include <intel_gpu/primitives/gather.hpp>
 #include <intel_gpu/primitives/reorder.hpp>
+#include <intel_gpu/primitives/reshape.hpp>
 #include <intel_gpu/primitives/data.hpp>
 
 #include "eltwise_inst.h"
+#include "reshape_inst.h"
 
 using namespace cldnn;
 using namespace ::tests;
@@ -3442,7 +3444,7 @@ TEST(eltwise_gpu_f32, broadcast_test_dim3_dim4) {
 TEST(eltwise_gpu_f32, broadcast_test_dim3_dim4_new_shape_infer_false) {
     auto& engine = get_test_engine();
 
-    ov::Shape in2_shape = {1, 4, 1, 1};
+    ov::Shape in2_shape = {1, 1, 4, 1};
     auto input2 = engine.allocate_memory({ ov::PartialShape(in2_shape), data_types::f32, format::bfyx });
 
     std::vector<float> const_input = {
@@ -3457,26 +3459,27 @@ TEST(eltwise_gpu_f32, broadcast_test_dim3_dim4_new_shape_infer_false) {
     });
 
     float answers[16] = {
-        1.5, 0.5, 7.5, 4,
-        2.5, 0.5, 8.5, 7.7,
-        3.5, 1, 9.5, 14.5,
-        4.5, 0, 10.5, 10.5
+        1.5, 2.5, 5.5, 4,
+        2.5, 2.5, 6.5, 7.7,
+        3.5, 3, 7.5, 14.5,
+        4.5, 2, 8.5, 10.5
     };
 
     ExecutionConfig config = get_test_default_config(engine);
     config.set_property(ov::intel_gpu::allow_new_shape_infer(false));
 
-    // in1:dim3, int2:dim4
+    // Eltwise in1:dim3, int2:dim4
     {
-        ov::Shape in1_shape = {2, 4, 2};
+        ov::Shape in1_shape = {1, 2, 2, 4};
 
         auto input = engine.allocate_memory({ ov::PartialShape(in1_shape), data_types::f32, format::bfyx });
         set_values(input, const_input);
 
         topology topology;
         topology.add(input_layout("input", input->get_layout()));
         topology.add(input_layout("input2", input2->get_layout()));
-        topology.add(eltwise("eltwise", { input_info("input"), input_info("input2") }, eltwise_mode::sum));
+        topology.add(reshape("reshape_input1", input_info("input"), false, {}, ov::PartialShape({2, 2, 4})));
+        topology.add(eltwise("eltwise", { input_info("reshape_input1"), input_info("input2") }, eltwise_mode::sum));
 
         network network(engine, topology, config);