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[GPU] Allow to set empty tensor for inner network of condition primitive (#21415)

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Sergey Shlyapnikov 2023-12-02 01:21:21 +04:00 committed by GitHub
parent 0a271c136a
commit 009951d969
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GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 83 additions and 6 deletions
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13
src/plugins/intel_gpu/src/graph/impls/common/condition.cpp
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@ -109,18 +109,25 @@ struct condition_impl : typed_primitive_impl<condition> {
if (iter != branch.input_map.end()) {
const primitive_id& input_internal_id = iter->second;
auto mem_ptr = instance.input_memory_ptr(mem_idx);
if (mem_ptr) {
auto dep = instance.dependencies()[mem_idx];
auto layout = dep.first->get_impl_params()->get_output_layout(dep.second);
if (mem_ptr) {
GPU_DEBUG_LOG << "Reshape input from " << mem_ptr->get_layout().to_short_string() << " to "
<< layout.to_short_string() << std::endl;
// Preallocation logic may allocate more memory than actually produced on current iteration, so
// we need to adjust input buffers layout
mem_ptr = instance.get_network().get_engine().reinterpret_buffer(*mem_ptr, layout);
} else if (layout.count() == 0) {
// Use dummy memory for empty tensor
mem_ptr = std::make_shared<simple_attached_memory>(layout, nullptr);
}
OPENVINO_ASSERT(mem_ptr != nullptr, "[GPU] Can't assign nullptr memory buffer for condition primitive with id=", instance.id(), " ("
"mem_idx=", mem_idx, ", "
"external_id=", input_external_id, ", "
"internal_id=", input_internal_id, ")");
executed_net->set_input_data(input_internal_id, mem_ptr);
GPU_DEBUG_LOG << "Inner net - Inputs[" << mem_idx << "]" << mem_ptr->get_layout().to_short_string()
<< std::endl;
GPU_DEBUG_LOG << "Inner net - Inputs[" << mem_idx << "]: layout=" << mem_ptr->get_layout().to_short_string() << ", "
<< "allocation_type=" << mem_ptr->get_allocation_type() << std::endl;
}
}
}

3
src/plugins/intel_gpu/src/graph/input_layout.cpp
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@ -43,7 +43,8 @@ event::ptr input_layout_inst::set_data(memory::ptr mem) {
auto& engine = get_network().get_engine();
auto& stream = get_network().get_stream();
if (mem->is_allocated_by(engine)) {
// Allow to set dummy simple_attached_memory empty tensor as network input
if (mem->is_allocated_by(engine) || mem->get_layout().count() == 0) {
OPENVINO_ASSERT(!_outputs.empty(), "[GPU] Can't set data for empty input memory");
_outputs[0] = mem;
ev = stream.create_user_event(true);

69
src/plugins/intel_gpu/tests/unit/test_cases/condition_gpu_test.cpp
View File

@ -978,3 +978,72 @@ TEST(condition_gpu, empty_body_with_different_shapes) {
auto out_pshape = output_layout.get_partial_shape();
ASSERT_EQ(out_pshape, oned_pshape);
}
TEST(condition_gpu, set_empty_tensor) {
auto& engine = get_test_engine();
ExecutionConfig config = get_test_default_config(engine);
config.set_property(ov::intel_gpu::optimize_data(true));
config.set_property(ov::intel_gpu::allow_new_shape_infer(true));
auto empty_mem = engine.allocate_memory({ { 1, 1, 1, 1 }, data_types::f16, format::bfyx });
auto empty_input_mem = engine.reinterpret_buffer(*empty_mem, { { 1, 1, 0, 1 }, data_types::f16, format::bfyx });
auto input_mem = engine.allocate_memory({ { 1, 1, 4, 1 }, data_types::f32, format::bfyx });
auto predicate_mem = engine.allocate_memory({ { 1, 1, 1, 1 }, data_types::u8, format::bfyx });
auto concat_data = engine.allocate_memory({ { 1, 1, 4, 1 }, data_types::f32, format::bfyx });
set_values(predicate_mem, {1});
primitive_id empty_input_id = "input1";
primitive_id reorder_id = "reorder";
primitive_id input_id = "input2";
primitive_id pred_id = "predicate";
primitive_id branch_input_id1 = "branch_input1";
primitive_id branch_input_id2 = "branch_input2";
primitive_id concat_data_id = "concat_data";
primitive_id concat_id = "concat";
primitive_id cond_id = "condi";
condition::branch branch_true;
{
topology branch_true_topology;
branch_true_topology.add(
input_layout(branch_input_id1, { { 1, 1, -1, 1 }, data_types::f32, format::bfyx }),
data(concat_data_id, concat_data),
concatenation(concat_id, { input_info(branch_input_id1), input_info(concat_data_id) }, 2)
);
branch_true.inner_program = program::build_program(engine, branch_true_topology, config, false, false, true);
branch_true.input_map.insert({reorder_id, branch_input_id1});
branch_true.output_map.insert({0, concat_id});
}
condition::branch branch_false;
{
topology branch_false_topology;
branch_false_topology.add(
input_layout(branch_input_id2, { { 1, 1, 4, 1 }, data_types::f32, format::bfyx }),
reorder("result", input_info(branch_input_id2), format::bfyx, data_types::f32)
);
branch_false.inner_program = program::build_program(engine, branch_false_topology, config, false, false, true);
branch_false.input_map.insert({input_id, branch_input_id2});
branch_false.output_map.insert({0, "result"});
}
auto empty_input_layout = layout({ 1, 1, -1, 1 }, data_types::f32, format::bfyx);
topology topology;
topology.add(input_layout(pred_id, predicate_mem->get_layout()));
topology.add(input_layout(empty_input_id, empty_input_layout));
topology.add(input_layout(input_id, input_mem->get_layout()));
topology.add(reorder(reorder_id, input_info(empty_input_id), format::bfyx, data_types::f32));
topology.add(condition(cond_id, {input_info(pred_id), input_info(reorder_id), input_info(input_id)}, branch_true, branch_false));
network net(engine, topology, config);
ASSERT_TRUE(net.get_primitive(cond_id)->get_node().as<condition>().get_branch_false().inner_program->can_be_optimized());
ASSERT_FALSE(net.get_primitive(cond_id)->get_node().as<condition>().get_branch_true().inner_program->can_be_optimized());
net.set_input_data(pred_id, predicate_mem);
net.set_input_data(empty_input_id, empty_input_mem);
net.set_input_data(input_id, input_mem);
ASSERT_NO_THROW(net.execute());
ASSERT_NO_THROW(net.get_output(cond_id).get_memory());
}