Skip to content

Commit

Permalink
Add convolution pattern test
Browse files Browse the repository at this point in the history
  • Loading branch information
@maxnick
maxnick committed Oct 10, 2024
1 parent 01444d0 commit 4a33243
Showing 1 changed file with 100 additions and 18 deletions.
118 changes: 100 additions & 18 deletions src/plugins/intel_cpu/tests/functional/custom/subgraph_tests/src/common/lora_pattern.cpp
View file
Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@
//

#include "common_test_utils/node_builders/eltwise.hpp"
#include "common_test_utils/node_builders/convolution.hpp"
#include "common_test_utils/ov_tensor_utils.hpp"
#include "shared_test_classes/base/ov_subgraph.hpp"
#include "utils/cpu_test_utils.hpp"
Expand All @@ -12,6 +13,31 @@ namespace ov {
namespace test {

class LoraPattern : public SubgraphBaseTest {
protected:
void run_test() {
compile_model();
inferRequest = compiledModel.create_infer_request();
ASSERT_TRUE(inferRequest);
generate_inputs(targetStaticShapes.front());
for (const auto& input : inputs) {
inferRequest.set_tensor(input.first, input.second);
}

inferRequest.infer();
auto outputs = function->outputs();

auto tx_result = inferRequest.get_tensor(outputs[0]);
auto tz_result = inferRequest.get_tensor(outputs[1]);
ov::test::utils::compare(tx_result, tz_result, 1e-4, 1e-4);
}

protected:
static constexpr auto t4_name = "lora/MatMul.B";
static constexpr auto t5_name = "lora/MatMul.alpha";
static constexpr auto t6_name = "lora/MatMul.A";
};

class LoraPatternMatmul : public LoraPattern {
public:
void SetUp() override {
targetDevice = utils::DEVICE_CPU;
Expand Down Expand Up @@ -57,34 +83,90 @@ class LoraPattern : public SubgraphBaseTest {
function = std::make_shared<ov::Model>(ov::ResultVector({result_x, result_z}),
ov::SinkVector({t4_assign, t5_assign, t6_assign}),
ov::ParameterVector({param_y, param_w}));

targetStaticShapes = {{{{1, 20, K}}, {{N, K}}}};
}

public:
static constexpr size_t K = 563ul;
static constexpr size_t N = 2048ul;

static constexpr auto t4_name = "lora/MatMul.B";
static constexpr auto t5_name = "lora/MatMul.alpha";
static constexpr auto t6_name = "lora/MatMul.A";
};

TEST_F(LoraPattern, smoke_empty_states) {
compile_model();
inferRequest = compiledModel.create_infer_request();
ASSERT_TRUE(inferRequest);
targetStaticShapes = {{{{1, 20, K}}, {{N, K}}}};
generate_inputs(targetStaticShapes.front());
for (const auto& input : inputs) {
inferRequest.set_tensor(input.first, input.second);
TEST_F(LoraPatternMatmul, smoke_empty_states) {
run_test();
}

class LoraPatternConvolution : public LoraPattern {
public:
void SetUp() override {
targetDevice = utils::DEVICE_CPU;

auto netType = ov::element::f32;

ov::PartialShape shape_x = {-1, num_channels, -1, -1};

auto param_y = std::make_shared<ov::op::v0::Parameter>(netType, shape_x);

// Original Convolution that is modified by LoRA adapter later
auto tx = ov::test::utils::make_convolution(param_y,
netType,
{1, 1},
{1, 1},
{0, 0},
{0, 0},
{1, 1},
ov::op::PadType::EXPLICIT,
num_channels);

// LoRA parameters from states
auto variable_t4 = std::make_shared<ov::op::util::Variable>(
ov::op::util::VariableInfo{ov::PartialShape({num_channels, -1}), netType, t4_name});
auto t4 = std::make_shared<ov::op::v6::ReadValue>(variable_t4);
auto t4_assign = std::make_shared<ov::op::v6::Assign>(t4, variable_t4);

auto variable_t5 = std::make_shared<ov::op::util::Variable>(
ov::op::util::VariableInfo{ov::PartialShape({1, -1}), netType, t5_name});
auto t5 = std::make_shared<ov::op::v6::ReadValue>(variable_t5);
auto t5_assign = std::make_shared<ov::op::v6::Assign>(t5, variable_t5);

auto variable_t6 = std::make_shared<ov::op::util::Variable>(
ov::op::util::VariableInfo{ov::PartialShape({-1, num_channels}), netType, t6_name});
auto t6 = std::make_shared<ov::op::v6::ReadValue>(variable_t6);
auto t6_assign = std::make_shared<ov::op::v6::Assign>(t6, variable_t6);

// LoRA pattern with additional Transposes to move channel dimensions into positions where MatMul can be applied
auto t4940 =
std::make_shared<ov::op::v0::Constant>(ov::element::i32, ov::Shape{4}, std::vector<size_t>{2, 3, 0, 1});

auto t4941 = std::make_shared<ov::op::v1::Transpose>(param_y, t4940);
auto t4942 = std::make_shared<ov::op::v0::MatMul>(t4941, t6, false, true);
auto t4943 = std::make_shared<ov::op::v1::Multiply>(t4942, t5);
auto t4944 = std::make_shared<ov::op::v0::MatMul>(t4943, t4, false, true);

auto t4945 =
std::make_shared<ov::op::v0::Constant>(ov::element::i32, ov::Shape{4}, std::vector<size_t>{2, 3, 0, 1});
auto t4946 = std::make_shared<ov::op::v1::Transpose>(t4944, t4945);


// Mix LoRA part into normally computed activations after the "main" MatMul
auto tz = std::make_shared<ov::op::v1::Add>(tx, t4946);

auto result_x = std::make_shared<ov::op::v0::Result>(tx);
auto result_z = std::make_shared<ov::op::v0::Result>(tz);

function = std::make_shared<ov::Model>(ov::ResultVector({result_x, result_z}),
ov::SinkVector({t4_assign, t5_assign, t6_assign}),
ov::ParameterVector({param_y}));

targetStaticShapes = {{{1, num_channels, 64, 64}}};
}

inferRequest.infer();
auto outputs = function->outputs();
public:
static constexpr size_t num_channels = 320ul;
};

auto tx_result = inferRequest.get_tensor(outputs[0]);
auto tz_result = inferRequest.get_tensor(outputs[1]);
ov::test::utils::compare(tx_result, tz_result, 1e-4, 1e-4);
TEST_F(LoraPatternConvolution, smoke_empty_states) {
run_test();
}

} // namespace test
} // namespace ov

0 comments on commit 4a33243

Please sign in to comment.