Skip to content

[GPU] Fix MVN fusion accuracy issue #30416

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Draft
wants to merge 1 commit into
base: master
Choose a base branch
from
+71 −1
Draft

[GPU] Fix MVN fusion accuracy issue #30416

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 2 additions & 1 deletion src/plugins/intel_gpu/src/kernel_selector/kernels/mvn/mvn_kernel_bfyx_opt.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -135,7 +135,8 @@ JitConstants MVNKernelBfyxOpt::GetJitConstants(const mvn_params& params, MVNKern
"((in_data_set_idx + iteration_in_data_set_offset) % OUTPUT_SIZE_X)" };
}
}
auto conf = FusedOpsConfiguration("", idx_order, "result", activation_dt, 1, LoadType::LT_UNALIGNED, BoundaryCheck::DISABLED);
//TODO: Need to know why set to DISABLE.
auto conf = FusedOpsConfiguration("", idx_order, "result", activation_dt, 1, LoadType::LT_UNALIGNED, BoundaryCheck::ENABLED);
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Since the index calculation function has changed, it seems to need to check for performance. right?

jit.Merge(MakeFusedOpsJitConstants(params, { conf }));
}

Expand Down
69 changes: 69 additions & 0 deletions src/plugins/intel_gpu/tests/unit/test_cases/mvn_gpu_test.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -974,3 +974,72 @@ TEST_P(mvn_random_test_bsv32, random_cached) {
this->execute(GetParam(), true);
}
#endif

TEST(mvn_gpu_test, fusion_mul_add) {

auto run_network = [&](bool use_opt_kernel = false) -> cldnn::memory::ptr {
auto& engine = get_test_engine();
const size_t b_length = 2;
const size_t f_length = 10;
const size_t y_length = 32;
cldnn::layout input0_dyn_layout({-1,-1,y_length}, data_types::f16, format::bfyx);
cldnn::layout input1_dyn_layout({-1,-1,y_length}, data_types::f16, format::bfyx);
cldnn::layout input2_dyn_layout({-1,-1,y_length}, data_types::f16, format::bfyx);

cldnn::layout input0_static_layout({b_length, f_length, y_length}, data_types::f16, format::bfyx);
cldnn::layout input1_static_layout({b_length, 1, y_length}, data_types::f16, format::bfyx);
cldnn::layout input2_static_layout({b_length, 1, y_length}, data_types::f16, format::bfyx);

auto input0 = engine.allocate_memory(input0_static_layout);
auto input1 = engine.allocate_memory(input1_static_layout);
auto input2 = engine.allocate_memory(input2_static_layout);

std::vector<ov::float16> input0_values(input0->count(), 0.f);
std::vector<ov::float16> input1_values(input1->count(), 2.f);
std::vector<ov::float16> input2_values(input2->count(), 0.1f);
for (size_t i = 0; i < input0_values.size(); i++) {
input0_values[i] = ov::float16(i * 0.03f);
}
set_values(input0, input0_values);
set_values(input1, input1_values);
set_values(input0, input2_values);

topology topo;
topo.add(input_layout("input0", input0_dyn_layout));
topo.add(input_layout("input1", input1_dyn_layout));//Gather, ADD_1
topo.add(input_layout("input2", input2_dyn_layout));//Gather_1
topo.add(mvn("mvn", input_info("input0"), true, 1e-06f, true, {2}));
topo.add(eltwise("mul", {input_info("mvn"), input_info("input1")}, eltwise_mode::prod, {}, data_types::f16));
topo.add(eltwise("add", {input_info("mul"), input_info("input2")}, eltwise_mode::sum, {}, data_types::f16));
topo.add(reorder("result",input_info("add"), format::bfyx, data_types::f32));

ExecutionConfig config = get_test_default_config(engine);
config.set_property(ov::intel_gpu::allow_new_shape_infer(true));

if (use_opt_kernel) {
config.set_property(ov::intel_gpu::force_implementations(ov::intel_gpu::ImplForcingMap{ {"mvn", {format::type::bfyx, "mvn_gpu_bfyx_opt"}} }));
} else {
config.set_property(ov::intel_gpu::force_implementations(ov::intel_gpu::ImplForcingMap{ {"mvn", {format::type::bfyx, "mvn_gpu_ref"}} }));
}

cldnn::network::ptr net = get_network(engine, topo, config, get_test_stream_ptr(), false);

net->set_input_data("input0", input0);
net->set_input_data("input1", input1);
net->set_input_data("input2", input2);

auto outputs = net->execute();
auto output = outputs.at("result").get_memory();
return output;
};

auto mem_ref_ptr = run_network(false);
auto mem_opt_ptr = run_network(true);
cldnn::mem_lock<float> ref_data(mem_ref_ptr, get_test_stream());
cldnn::mem_lock<float> opt_data(mem_opt_ptr, get_test_stream());

ASSERT_EQ(ref_data.size(), opt_data.size());
for (size_t i = 0; i < ref_data.size(); i++) {
ASSERT_NEAR(static_cast<float>(ref_data[i]), static_cast<float>(opt_data[i]), 1.e-1f);
}
}
Loading