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Remove legacy test utils #871

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merged 1 commit into from
Feb 8, 2024
Merged

Remove legacy test utils #871

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4 changes: 4 additions & 0 deletions modules/nvidia_plugin/tests/unit/CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -37,6 +37,10 @@ ov_add_test_target(
openvino::gmock
openvino::ov_models
openvino::commonTestUtils
openvino::funcSharedTests
INCLUDES
PRIVATE
"${OpenVINO_SOURCE_DIR}/src/plugins/template/include"
ADD_CPPLINT
ADD_CLANG_FORMAT
LABELS
Expand Down
84 changes: 42 additions & 42 deletions modules/nvidia_plugin/tests/unit/cuda_multi_graph_ti_test.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -4,12 +4,21 @@

#include <gtest/gtest.h>

#include "common_test_utils/node_builders/eltwise.hpp"
#include "common_test_utils/node_builders/gru_cell.hpp"
#include "common_test_utils/test_constants.hpp"
#include "cuda_graph_topology_runner.hpp"
#include "cuda_simple_execution_delegator.hpp"
#include "ops/parameter.hpp"
#include "ops/result.hpp"
#include "ov_models/builders.hpp"
#include "functional_test_utils/ov_plugin_cache.hpp"
#include "openvino/op/concat.hpp"
#include "openvino/op/constant.hpp"
#include "openvino/op/parameter.hpp"
#include "openvino/op/result.hpp"
#include "openvino/op/split.hpp"
#include "openvino/op/squeeze.hpp"
#include "openvino/op/unsqueeze.hpp"
#include "ov_models/utils/data_utils.hpp"
#include "template/properties.hpp"
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I wonder how compilation has passed with this line.. This file is not available in the repo.


using namespace ov::nvidia_gpu;
using namespace testing;
Expand Down Expand Up @@ -41,49 +50,38 @@ void generateInput(ov::Tensor& tensor, int to = TO, int from = FROM, int seed =
std::generate(ptr, ptr + tensor.get_size(), [&dist, &engine]() { return CalcType{dist(engine)}; });
}

std::vector<std::vector<CalcType>> calcRefs(std::shared_ptr<ov::Model> model,
const std::vector<std::shared_ptr<ov::Tensor>>& inputs) {
ov::TensorVector calcRefs(std::shared_ptr<ov::Model> model, const std::vector<std::shared_ptr<ov::Tensor>>& inputs) {
auto refModel = model->clone();

auto referenceInputs = std::vector<std::vector<uint8_t>>(inputs.size());
auto refInputsTypes = std::vector<ov::element::Type>(inputs.size());
for (std::size_t i = 0; i < inputs.size(); ++i) {
const auto& input = inputs[i];
const auto inputSize = input->get_byte_size();
std::shared_ptr<ov::Core> core = ov::test::utils::PluginCache::get().core();

auto& referenceInput = referenceInputs[i];
referenceInput.resize(inputSize);

const auto* buffer = static_cast<const uint8_t*>(input->data());
std::copy(buffer, buffer + inputSize, referenceInput.data());

refInputsTypes[i] = CALC_ELEMENT_TYPE;
auto compiled_model_ref = core->compile_model(
refModel, ov::test::utils::DEVICE_TEMPLATE, {{ov::template_plugin::disable_transformations(true)}});
auto infer_request_ref = compiled_model_ref.create_infer_request();
auto params = refModel->get_parameters();
OPENVINO_ASSERT(params.size() == inputs.size());
for (int i = 0; i < params.size(); i++) {
infer_request_ref.set_tensor(params[i]->get_default_output(), *inputs[i]);
}
infer_request_ref.infer();

const auto expectedOutputs = ngraph::helpers::interpreterFunction(refModel, referenceInputs, refInputsTypes);

std::vector<std::vector<CalcType>> res(expectedOutputs.size());
for (std::size_t i = 0; i < expectedOutputs.size(); ++i) {
EXPECT_EQ(expectedOutputs[i].first, CALC_ELEMENT_TYPE);
const auto& expOut = expectedOutputs[i].second;
auto& resOut = res[i];
const auto resOutSize = expOut.size() / sizeof(CalcType);
resOut.resize(resOutSize);

const auto* buffer = static_cast<const CalcType*>(static_cast<const void*>(expOut.data()));
std::copy(buffer, buffer + resOutSize, resOut.data());
ov::TensorVector outputs;
for (const auto& output : refModel->outputs()) {
outputs.push_back(infer_request_ref.get_tensor(output));
}
return res;

return outputs;
}

void validateOutput(const ov::Tensor& tensor, const std::vector<CalcType>& refVector, float threshold) {
void validateOutput(const ov::Tensor& tensor, const ov::Tensor& ref_tensor, float threshold) {
EXPECT_EQ(tensor.get_element_type(), CALC_ELEMENT_TYPE);
EXPECT_EQ(ref_tensor.get_element_type(), CALC_ELEMENT_TYPE);
const auto size = tensor.get_size();
EXPECT_EQ(size, refVector.size());
EXPECT_EQ(size, ref_tensor.get_size());
const auto* ptr = getConstPtr(tensor);
bool areEqual = std::equal(ptr, ptr + size, refVector.cbegin(), [threshold](auto val1, auto val2) {
return std::abs(val1 - val2) < threshold;
});
const auto* ref_ptr = getConstPtr(ref_tensor);
bool areEqual = std::equal(
ptr, ptr + size, ptr, [threshold](auto val1, auto val2) { return std::abs(val1 - val2) < threshold; });
EXPECT_TRUE(areEqual);
}

Expand Down Expand Up @@ -121,7 +119,7 @@ class GRUTI {
auto squeeze = std::make_shared<ov::op::v0::Squeeze>(bodyParams[0], axis);
ov::OutputVector out_vector = {squeeze, bodyParams[1]};
auto gru_cell =
ngraph::builder::makeGRU(out_vector, WRB, hidden_size, {"sigmoid", "tanh"}, {}, {}, clip, false);
ov::test::utils::make_gru(out_vector, WRB, hidden_size, {"sigmoid", "tanh"}, {}, {}, clip, false);
auto unsqueeze = std::make_shared<ov::op::v0::Unsqueeze>(gru_cell->output(0), axis);
ov::ResultVector results{std::make_shared<ov::op::v0::Result>(gru_cell->output(0)),
std::make_shared<ov::op::v0::Result>(unsqueeze)};
Expand Down Expand Up @@ -202,10 +200,12 @@ class SplitConcatAddTI {
}

auto squeeze = std::make_shared<ov::op::v0::Squeeze>(bodyParams[0], axisConstant);
const auto split = ngraph::builder::makeSplit(squeeze, CALC_ELEMENT_TYPE, 2, 1);
const auto split_axis_op =
std::make_shared<ov::op::v0::Constant>(ov::element::i64, ov::Shape{}, std::vector<int64_t>{1});
const auto split = std::make_shared<ov::op::v1::Split>(squeeze, split_axis_op, 2);
const auto concat =
std::make_shared<ov::op::v0::Concat>(ov::OutputVector{split->output(0), split->output(1)}, 1);
const auto add0 = ngraph::builder::makeEltwise(concat->output(0), bodyParams[1], EltwiseTypes::ADD);
const auto add0 = ov::test::utils::make_eltwise(concat->output(0), bodyParams[1], EltwiseTypes::ADD);

auto unsqueeze = std::make_shared<ov::op::v0::Unsqueeze>(add0->output(0), axisConstant);
ov::ResultVector results{std::make_shared<ov::op::v0::Result>(add0->output(0)),
Expand Down Expand Up @@ -299,13 +299,13 @@ class CudaMultiGraphTest : public Test {

void run() { runner_.Run(*inferRequestContext_, deviceMemBlock_); }

void calcRefs() { refOutputs_ = ::calcRefs(model_, inputTensors_); }
void calcRefs() { refOutputTensors_ = ::calcRefs(model_, inputTensors_); }

void validate(float threshold = THRESHOLD) {
const auto size = outputTensors_.size();
EXPECT_EQ(size, refOutputs_.size());
EXPECT_EQ(size, refOutputTensors_.size());
for (std::size_t i = 0; i < size; ++i) {
validateOutput(*outputTensors_[i], refOutputs_[i], THRESHOLD);
validateOutput(*outputTensors_[i], refOutputTensors_[i], THRESHOLD);
}
}

Expand Down Expand Up @@ -349,6 +349,7 @@ class CudaMultiGraphTest : public Test {
SimpleExecutionDelegator simpleExecutionDelegator_{};
std::vector<std::shared_ptr<ov::Tensor>> inputTensors_{populateTensors(model_->inputs())};
std::vector<std::shared_ptr<ov::Tensor>> outputTensors_{populateTensors(model_->outputs())};
ov::TensorVector refOutputTensors_;
std::map<std::string, std::size_t> inputIndices_{populateInputIndices(model_)};
std::map<std::string, std::size_t> outputIndices_{populateOutputIndices(model_)};
std::unique_ptr<InferenceRequestContext> inferRequestContext_ =
Expand All @@ -363,7 +364,6 @@ class CudaMultiGraphTest : public Test {
false);
DeviceMemBlock deviceMemBlock_{runner_.GetSubGraph().memoryManager()->mutableTensorsMemoryModel()};

std::vector<std::vector<CalcType>> refOutputs_;
int currentSeed_ = SEED;
};

Expand Down