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[GPU] Fix reset output issue (#27695)
### Details: - *Fix invalid output memory usages by reset output memory* - *At the previous iteration, gather primitive has output memory which is refer input memory because it is optimized out but it also use input memory as output without reallocation memory at the next iteration which turns to executed from optimized out. it makes memory corruption issue.* - *Reset output memory when the current prim status is changed from optimized / skipped to executed*  ### Tickets: - *154591*
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src/plugins/intel_gpu/tests/unit/dynamic_execution/skip_gather_at_runtime.cpp
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| // Copyright (C) 2024 Intel Corporation | ||
| // SPDX-License-Identifier: Apache-2.0 | ||
| // | ||
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| #include "test_utils.h" | ||
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| #include <intel_gpu/primitives/input_layout.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> | ||
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| #include "gather_inst.h" | ||
| #include "program_wrapper.h" | ||
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| #include <cmath> | ||
| #include <algorithm> | ||
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| using namespace cldnn; | ||
| using namespace ::tests; | ||
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| namespace skip_gather_tests { | ||
| enum execution_status { | ||
| optimized = 0, | ||
| skipped = 1, | ||
| executed = 2 | ||
| }; | ||
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| struct gather_iter_params { | ||
| ov::PartialShape input1_shape; | ||
| ov::PartialShape input2_shape; | ||
| execution_status expected_status; | ||
| }; | ||
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| struct skip_gather_params { | ||
| std::vector<gather_iter_params> input_data; | ||
| int axis; | ||
| }; | ||
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| class skip_gather_at_runtime_test : public testing::TestWithParam<skip_gather_params> {}; | ||
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| TEST_P(skip_gather_at_runtime_test, runtime_skip) { | ||
| auto p = GetParam(); | ||
| auto& engine = get_test_engine(); | ||
| auto axis = p.axis; | ||
| auto input1_rank = p.input_data[0].input1_shape.size(); | ||
| auto input1_layout_dynamic = layout {ov::PartialShape::dynamic(input1_rank), data_types::f16, format::get_default_format(input1_rank)}; | ||
| auto input2_rank = p.input_data[0].input2_shape.size(); | ||
| auto input2_layout_dynamic = layout {ov::PartialShape::dynamic(input2_rank), data_types::f16, format::get_default_format(input2_rank)}; | ||
| topology topology(input_layout("input1", input1_layout_dynamic), | ||
| input_layout("input2", input1_layout_dynamic), | ||
| reshape("squeeze", input_info("input2"), false, {-1}, {-1}, reshape::reshape_mode::base), | ||
| gather("gather", | ||
| input_info("input1"), | ||
| input_info("squeeze"), | ||
| axis, | ||
| p.input_data[0].input1_shape.size(), | ||
| ov::Shape{}, | ||
| 0, | ||
| true), | ||
| reorder("reorder", input_info("gather"), format::get_default_format(input1_rank), data_types::f32)); | ||
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| 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)); | ||
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| network network(engine, topology, config); | ||
| auto gather_inst = network.get_primitive("gather"); | ||
| for (auto in_shape_data : p.input_data) { | ||
| auto input1_static_layout = layout {in_shape_data.input1_shape, data_types::f16, format::get_default_format(input1_rank)}; | ||
| auto input1_mem = engine.allocate_memory(input1_static_layout); | ||
| network.set_input_data("input1", input1_mem); | ||
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| auto input2_static_layout = layout {in_shape_data.input2_shape, data_types::f16, format::get_default_format(input2_rank)}; | ||
| auto intpu2_unit_static_layout = layout {ov::PartialShape{1}, data_types::f16, format::get_default_format(input2_rank)}; | ||
| auto input2_mem = (input2_static_layout.count() == 0)? engine.allocate_memory(intpu2_unit_static_layout) : engine.allocate_memory(input2_static_layout); | ||
| if (input2_static_layout.count() == 0) | ||
| input2_mem = engine.reinterpret_buffer(*input2_mem, input2_static_layout); | ||
| network.set_input_data("input2", input2_mem); | ||
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| auto outputs = network.execute(); | ||
| if (in_shape_data.expected_status == execution_status::executed) { | ||
| ASSERT_FALSE(engine.is_the_same_buffer(gather_inst->dep_memory(0), gather_inst->output_memory(0))); | ||
| ASSERT_FALSE(gather_inst->can_be_optimized()); | ||
| } else if (in_shape_data.expected_status == execution_status::optimized) { | ||
| ASSERT_TRUE(engine.is_the_same_buffer(gather_inst->dep_memory(0), gather_inst->output_memory(0))); | ||
| ASSERT_TRUE(gather_inst->can_be_optimized()); | ||
| } else { | ||
| ASSERT_TRUE(gather_inst->get_output_layout(0).count() == 0); | ||
| } | ||
| } | ||
| } | ||
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| INSTANTIATE_TEST_SUITE_P(smoke, skip_gather_at_runtime_test, | ||
| testing::ValuesIn(std::vector<skip_gather_params> { | ||
| {{{ov::PartialShape{1,1,8}, ov::PartialShape{1,1}, execution_status::optimized},{ov::PartialShape{1,1,8}, ov::PartialShape{1,0}, execution_status::skipped}, {ov::PartialShape{1,11,8}, ov::PartialShape{1,6}, execution_status::executed}}, 1}, | ||
| {{{ov::PartialShape{1,2,8}, ov::PartialShape{1,1}, execution_status::executed},{ov::PartialShape{1,1,8}, ov::PartialShape{1,0}, execution_status::skipped}, {ov::PartialShape{1,11,8}, ov::PartialShape{1,6}, execution_status::executed}}, 1}, | ||
| {{{ov::PartialShape{1,1,8}, ov::PartialShape{1,1}, execution_status::optimized},{ov::PartialShape{1,1,8}, ov::PartialShape{1,1}, execution_status::optimized},{ov::PartialShape{1,11,8}, ov::PartialShape{1,6}, execution_status::executed}}, 1} | ||
| })); | ||
| } // skip gather tests |