Add reproducible TCs for ov_gpu_unit_tests

src/plugins/intel_gpu/tests/unit/passes/add_required_reorders_test.cpp

@@ -0,0 +1,65 @@
+// Copyright (C) 2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "test_utils.h"
+
+#include "intel_gpu/runtime/engine.hpp"
+
+#include "intel_gpu/graph/network.hpp"
+#include "intel_gpu/graph/program.hpp"
+#include "data_inst.h"
+#include "shape_of_inst.h"
+#include "gather_inst.h"
+#include "eltwise_inst.h"
+#include "reshape_inst.h"
+#include "concatenation_inst.h"
+#include "pass_manager.h"
+#include "to_string_utils.h"
+
+#include "program_wrapper.h"
+
+#include <memory>
+
+using namespace cldnn;
+using namespace ::tests;
+
+TEST(add_required_reorders, input_reorder_inside_shape_of_subgraph) {
+    auto& engine = get_test_engine();
+    auto input_layout_dynamic = layout{ov::PartialShape{1, 32, ov::Dimension::dynamic(), ov::Dimension::dynamic()},
+                                       data_types::f16, format::bfyx};
+    auto input = engine.allocate_memory({ov::PartialShape{1, 32, 32, 32}, data_types::f16, format::bfyx});
+    auto data_0 = engine.allocate_memory({ ov::PartialShape{}, data_types::i32, format::bfyx });
+    auto data_1 = engine.allocate_memory({ ov::PartialShape{}, data_types::f32, format::bfyx });
+
+    topology topology;
+    topology.add(input_layout("input", input_layout_dynamic));
+    topology.add(data("data_0", data_0));
+    topology.add(data("data_1", data_1));
+    topology.add(shape_of("shape_of", input_info("input"), 4, data_types::i32));
+    topology.add(gather("gather0", input_info("shape_of"), input_info("data_0"), 0, {}, 0, true));
+    topology.add(eltwise("eltwise0", {input_info("gather0"), input_info("data_1")}, eltwise_mode::prod, data_types::f32));
+    topology.add(reshape("reshape0", input_info("eltwise0"), false, {},
+                         ov::PartialShape{1}, reshape::reshape_mode::unsqueeze));
+    topology.add(gather("gather1", input_info("shape_of"), input_info("data_0"), 0, {}, 0, true));
+    topology.add(eltwise("eltwise1", {input_info("gather1"), input_info("data_1")}, eltwise_mode::prod, data_types::f32));
+    topology.add(reshape("reshape1", input_info("eltwise1"), false, {},
+                         ov::PartialShape{1}, reshape::reshape_mode::unsqueeze));
+    topology.add(concatenation("concat0", {input_info("reshape0"), input_info("reshape1")}, 0, data_types::f32));
+
+    ExecutionConfig config = get_test_default_config(engine);
+    config.set_property(ov::intel_gpu::allow_new_shape_infer(true));
+    config.set_property(ov::intel_gpu::optimize_data(true));
+    network network(engine, topology, config);
+    network.set_input_data("input", input);
+
+    network.execute();
+
+    auto prog = network.get_program();
+    ASSERT_NE(prog, nullptr);
+
+    auto& eltwise_node = prog->get_node("eltwise0");
+    auto eltwise_in_layout = eltwise_node.get_input_layout();
+
+    ASSERT_EQ(eltwise_in_layout.data_type, data_types::f32);
+}

src/plugins/intel_gpu/tests/unit/passes/prepare_buffer_fusing_test.cpp

@@ -13,6 +13,8 @@
 #include "fully_connected_inst.h"
 #include "permute_inst.h"
 #include "reorder_inst.h"
+#include "shape_of_inst.h"
+#include "gather_inst.h"
 #include "intel_gpu/graph/network.hpp"
 #include "pass_manager.h"
 #include "to_string_utils.h"
@@ -520,6 +522,61 @@ TEST(prepare_buffer_fusing, crop_b_axis) {
     }
 }
 
+TEST(prepare_buffer_fusing, skip_in_place_concat_inside_shape_of_subgraph) {
+    auto& engine = get_test_engine();
+    auto input_layout_dynamic = layout{ov::PartialShape{1, 32, ov::Dimension::dynamic(), ov::Dimension::dynamic()},
+                                       data_types::f16, format::bfyx};
+    auto input = engine.allocate_memory({ov::PartialShape{1, 32, 32, 32}, data_types::f16, format::bfyx});
+    auto data_0 = engine.allocate_memory({ ov::PartialShape{}, data_types::i32, format::bfyx });
+    auto data_1 = engine.allocate_memory({ ov::PartialShape{}, data_types::f32, format::bfyx });
+    auto data_2 = engine.allocate_memory({ ov::PartialShape{4}, data_types::i32, format::bfyx });
+
+    const ov::op::AutoBroadcastSpec& broadcast_spec = ov::op::AutoBroadcastSpec(ov::op::AutoBroadcastType::NUMPY);
+
+    topology topology;
+    topology.add(input_layout("input", input_layout_dynamic));
+    topology.add(data("data_0", data_0));
+    topology.add(data("data_1", data_1));
+    topology.add(data("data_2", data_2));
+    topology.add(shape_of("shape_of", input_info("input"), 4, data_types::i32));
+    topology.add(gather("gather0", input_info("shape_of"), input_info("data_0"), 0, {}, 0, true));
+    topology.add(reorder("reorder0", input_info("gather0"), format::any, data_types::f32,
+                         std::vector<float>(), reorder_mean_mode::subtract, padding(), true));
+    topology.add(eltwise("eltwise0", input_info("reorder0"), input_info("data_1"), eltwise_mode::prod, broadcast_spec));
+    topology.add(reshape("reshape0", input_info("eltwise0"), false, {},
+                         ov::PartialShape{1}, reshape::reshape_mode::unsqueeze));
+    topology.add(gather("gather1", input_info("shape_of"), input_info("data_0"), 0, {}, 0, true));
+    topology.add(reorder("reorder1", input_info("gather1"), format::any, data_types::f32,
+                         std::vector<float>(), reorder_mean_mode::subtract, padding(), true));
+    topology.add(eltwise("eltwise1", input_info("reorder1"), input_info("data_1"), eltwise_mode::prod, broadcast_spec));
+    topology.add(reshape("reshape1", input_info("eltwise1"), false, {},
+                         ov::PartialShape{1}, reshape::reshape_mode::unsqueeze));
+    topology.add(crop("crop", input_info("shape_of"), tensor({2,1,1,1,1,1,1,1,1}), tensor({0,0,0,0,1,1,1,1,1})));
+    topology.add(concatenation("concat0", {input_info("reshape0"), input_info("reshape1")}, 0, data_types::f32));
+    topology.add(reorder("reorder3", input_info("concat0"), format::any, data_types::i32,
+                         std::vector<float>(), reorder_mean_mode::subtract, padding(), true));
+    topology.add(concatenation("concat1", {input_info("reorder3"), input_info("crop")}, 0, data_types::i32));
+    topology.add(eltwise("eltwise2", input_info("concat1"), input_info("data_2"), eltwise_mode::prod, broadcast_spec));
+
+    ExecutionConfig config = get_test_default_config(engine);
+    config.set_property(ov::intel_gpu::allow_new_shape_infer(true));
+    config.set_property(ov::intel_gpu::optimize_data(true));
+    network network(engine, topology, config);
+    network.set_input_data("input", input);
+
+    network.execute();
+
+    auto prog = network.get_program();
+    ASSERT_NE(prog, nullptr);
+
+    auto& crop_node = prog->get_node("crop");
+    auto impl_param = crop_node.get_kernel_impl_params();
+    auto crop_mem = network.get_output_memory("crop");
+    ASSERT_EQ(impl_param->get_output_layout(), crop_mem->get_layout());
+    auto in_place = engine.is_the_same_buffer(*network.get_output_memory("crop"), *network.get_output_memory("concat1"));
+    ASSERT_FALSE(in_place);
+}
+
 #ifdef ENABLE_ONEDNN_FOR_GPU
 TEST(prepare_buffer_fusing, in_place_onednn_concat_static) {
     auto& engine = get_test_engine();

src/plugins/intel_gpu/tests/unit/passes/remove_redundant_reorders_tests.cpp

@@ -19,6 +19,8 @@
 #include "activation_inst.h"
 #include "mvn_inst.h"
 #include "concatenation_inst.h"
+#include "shape_of_inst.h"
+#include "gather_inst.h"
 #include "pass_manager.h"
 #include "to_string_utils.h"
 
@@ -323,3 +325,55 @@ TEST(remove_redundant_reorders, fuse_reorder_to_prev_concat_dyn) {
 
     ASSERT_EQ(concat_layout.data_type, data_types::f32);
 }
+
+TEST(remove_redundant_reorders, not_to_fuse_concat_with_reorder_inside_shape_of_subgraph) {
+    auto& engine = get_test_engine();
+    auto input_layout_dynamic = layout{ov::PartialShape{1, 32, ov::Dimension::dynamic(), ov::Dimension::dynamic()},
+                                       data_types::f16, format::bfyx};
+    auto input = engine.allocate_memory({ov::PartialShape{1, 32, 32, 32}, data_types::f16, format::bfyx});
+    auto data_0 = engine.allocate_memory({ ov::PartialShape{}, data_types::i32, format::bfyx });
+    auto data_1 = engine.allocate_memory({ ov::PartialShape{}, data_types::f32, format::bfyx });
+    auto data_2 = engine.allocate_memory({ ov::PartialShape{2}, data_types::i32, format::bfyx });
+
+    const ov::op::AutoBroadcastSpec& broadcast_spec = ov::op::AutoBroadcastSpec(ov::op::AutoBroadcastType::NUMPY);
+
+    topology topology;
+    topology.add(input_layout("input", input_layout_dynamic));
+    topology.add(data("data_0", data_0));
+    topology.add(data("data_1", data_1));
+    topology.add(data("data_2", data_2));
+    topology.add(shape_of("shape_of", input_info("input"), 4, data_types::i32));
+    topology.add(gather("gather0", input_info("shape_of"), input_info("data_0"), 0, {}, 0, true));
+    topology.add(reorder("reorder0", input_info("gather0"), format::any, data_types::f32,
+                         std::vector<float>(), reorder_mean_mode::subtract, padding(), true));
+    topology.add(eltwise("eltwise0", input_info("reorder0"), input_info("data_1"), eltwise_mode::prod, broadcast_spec));
+    topology.add(reshape("reshape0", input_info("eltwise0"), false, {},
+                         ov::PartialShape{1}, reshape::reshape_mode::unsqueeze));
+    topology.add(gather("gather1", input_info("shape_of"), input_info("data_0"), 0, {}, 0, true));
+    topology.add(reorder("reorder1", input_info("gather1"), format::any, data_types::f32,
+                         std::vector<float>(), reorder_mean_mode::subtract, padding(), true));
+    topology.add(eltwise("eltwise1", input_info("reorder1"), input_info("data_1"), eltwise_mode::prod, broadcast_spec));
+    topology.add(reshape("reshape1", input_info("eltwise1"), false, {},
+                         ov::PartialShape{1}, reshape::reshape_mode::unsqueeze));
+    topology.add(concatenation("concat0", {input_info("reshape0"), input_info("reshape1")}, 0, data_types::f32));
+    topology.add(reorder("reorder3", input_info("concat0"), format::any, data_types::i32,
+                         std::vector<float>(), reorder_mean_mode::subtract, padding(), true));
+    topology.add(concatenation("concat1", {input_info("reorder3"), input_info("data_2")}, 0, data_types::i32));
+
+    ExecutionConfig config = get_test_default_config(engine);
+    config.set_property(ov::intel_gpu::allow_new_shape_infer(true));
+    config.set_property(ov::intel_gpu::optimize_data(true));
+    network network(engine, topology, config);
+    network.set_input_data("input", input);
+
+    network.execute();
+
+    auto prog = network.get_program();
+    ASSERT_NE(prog, nullptr);
+
+    ASSERT_TRUE(has_node(*prog, "reorder3"));
+    auto& concat_node = prog->get_node("concat0");
+    auto concat_layout = concat_node.get_output_layout();
+
+    ASSERT_EQ(concat_layout.data_type, data_types::f32);
+}