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GRN - reference revision and tests (#6629)

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* Add GRN shared single layer test instance for CPU

* Remove GRN backend tests from fused_op.in

* Init GRN new template reference tests

* Add more bias values to GRN single layer tests

* Add more GRN template reference test cases

* Remove unused parameter from GrnParams

* Refactor GRN template referene tests and add more types

* Add anonymous namespace

* Add bf16 type to cpu single layer tests

* Add Serialization test

* Add GRN to revised ops
This commit is contained in:
Katarzyna Mitrus 2021-07-16 13:47:13 +02:00 committed by GitHub
parent 6c22af8a77
commit fa8f45b7f2
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5 changed files with 191 additions and 56 deletions
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118
docs/template_plugin/tests/functional/op_reference/grn.cpp Normal file
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// Copyright (C) 2018-2021 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#include <gtest/gtest.h>
#include <ie_core.hpp>
#include <ie_ngraph_utils.hpp>
#include <ngraph/ngraph.hpp>
#include <shared_test_classes/base/layer_test_utils.hpp>
#include <tuple>
#include "base_reference_test.hpp"
using namespace ngraph;
using namespace InferenceEngine;
namespace {
struct GrnParams {
template <class IT>
GrnParams(const float bias, const ngraph::PartialShape& shape, const ngraph::element::Type& iType, const std::vector<IT>& iValues,
const std::vector<IT>& oValues)
: bias(bias), pshape(shape), inType(iType), outType(iType), inputData(CreateBlob(iType, iValues)), refData(CreateBlob(iType, oValues)) {}
float bias;
ngraph::PartialShape pshape;
ngraph::element::Type inType;
ngraph::element::Type outType;
InferenceEngine::Blob::Ptr inputData;
InferenceEngine::Blob::Ptr refData;
};
class ReferenceGrnLayerTest : public testing::TestWithParam<GrnParams>, public CommonReferenceTest {
public:
void SetUp() override {
auto params = GetParam();
function = CreateFunction(params.bias, params.pshape, params.inType);
inputData = {params.inputData};
refOutData = {params.refData};
}
static std::string getTestCaseName(const testing::TestParamInfo<GrnParams>& obj) {
auto param = obj.param;
std::ostringstream result;
result << "bias=" << param.bias << "_";
result << "shape=" << param.pshape << "_";
result << "iType=" << param.inType << "_";
result << "oType=" << param.outType;
return result.str();
}
private:
static std::shared_ptr<Function> CreateFunction(float bias, const PartialShape& input_shape, const element::Type& input_type) {
const auto in = std::make_shared<op::Parameter>(input_type, input_shape);
const auto grn = std::make_shared<op::v0::GRN>(in, bias);
return std::make_shared<Function>(NodeVector {grn}, ParameterVector {in});
}
};
TEST_P(ReferenceGrnLayerTest, CompareWithHardcodedRefs) {
Exec();
}
template <element::Type_t IN_ET>
std::vector<GrnParams> generateGrnParams(const ngraph::element::Type& type) {
using T = typename element_type_traits<IN_ET>::value_type;
std::vector<GrnParams> grnParams {
// bias 1e-6 // 2D // 3D // 4D
GrnParams(1e-6, ngraph::PartialShape {3, 4}, type, std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12},
std::vector<T> {0.182574, 0.365148, 0.547723, 0.730297, 0.379049, 0.454859, 0.530669, 0.606478, 0.426162, 0.473514, 0.520865, 0.568217}),
GrnParams(1e-6, ngraph::PartialShape {2, 3, 4}, type,
std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24},
std::vector<T> {0.0966737, 0.169031, 0.224231, 0.267261, 0.483368, 0.507093, 0.523205, 0.534522, 0.870063, 0.845154, 0.822179, 0.801784,
0.433574, 0.441836, 0.449215, 0.455842, 0.566982, 0.568075, 0.569005, 0.569803, 0.700389, 0.694314, 0.688796, 0.683763}),
GrnParams(1e-6, ngraph::PartialShape {1, 2, 3, 4}, type,
std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24},
std::vector<T> {0.0766965, 0.141421, 0.196116, 0.242536, 0.282166, 0.316228, 0.345705, 0.371391, 0.393919, 0.413803, 0.431455, 0.447214,
0.997055, 0.989949, 0.980581, 0.970143, 0.959365, 0.948683, 0.938343, 0.928477, 0.919145, 0.910366, 0.902134, 0.894427}),
GrnParams(1e-6, ngraph::PartialShape {2, 2, 3, 4}, type,
std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24,
25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48},
std::vector<T> {0.0766965, 0.141421, 0.196116, 0.242536, 0.282166, 0.316228, 0.345705, 0.371391, 0.393919, 0.413803, 0.431455, 0.447214,
0.997055, 0.989949, 0.980581, 0.970143, 0.959365, 0.948683, 0.938343, 0.928477, 0.919145, 0.910366, 0.902134, 0.894427,
0.559857, 0.564684, 0.56921, 0.573462, 0.577465, 0.581238, 0.584802, 0.588172, 0.591364, 0.594391, 0.597266, 0.6,
0.828589, 0.825307, 0.822192, 0.819232, 0.816416, 0.813733, 0.811176, 0.808736, 0.806405, 0.804176, 0.802043, 0.8}),
// bias 100.25 // 2D // 3D // 4D
GrnParams(100.25, ngraph::PartialShape {3, 4}, type, std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12},
std::vector<T> {0.0876216, 0.175243, 0.262865, 0.350486, 0.301923, 0.362308, 0.422693, 0.483077, 0.385076, 0.427863, 0.470649, 0.513435}),
GrnParams(100.25, ngraph::PartialShape {2, 3, 4}, type,
std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24},
std::vector<T> {0.0694629, 0.129032, 0.179525, 0.222137, 0.347314, 0.387097, 0.418891, 0.444273, 0.625166, 0.645161, 0.658258, 0.66641,
0.41125, 0.421303, 0.430287, 0.438356, 0.537789, 0.541675, 0.54503, 0.547945, 0.664327, 0.662047, 0.659774, 0.657534}),
GrnParams(100.25, ngraph::PartialShape {1, 2, 3, 4}, type,
std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24},
std::vector<T> {0.0608299, 0.115422, 0.164091, 0.207321, 0.245662, 0.279675, 0.309889, 0.336786, 0.360795, 0.38229, 0.401596, 0.418994,
0.790789, 0.807954, 0.820457, 0.829283, 0.835252, 0.839026, 0.841128, 0.841965, 0.841854, 0.841037, 0.839701, 0.837989f}),
GrnParams(100.25, ngraph::PartialShape {2, 2, 3, 4}, type,
std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24,
25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48},
std::vector<T> {0.0608299, 0.115422, 0.164091, 0.207321, 0.245662, 0.279675, 0.309889, 0.336786, 0.360795, 0.38229, 0.401596, 0.418994,
0.790789, 0.807954, 0.820457, 0.829283, 0.835252, 0.839026, 0.841128, 0.841965, 0.841854, 0.841037, 0.839701, 0.837989,
0.546293, 0.551788, 0.556938, 0.561772, 0.566319, 0.570601, 0.574641, 0.578458, 0.582069, 0.585489, 0.588734, 0.591816,
0.808514, 0.80646, 0.804466, 0.802532, 0.800658, 0.798842, 0.797083, 0.795379, 0.79373, 0.792133, 0.790586, 0.789088})};
return grnParams;
}
std::vector<GrnParams> generateGrnCombinedParams() {
const std::vector<std::vector<GrnParams>> grnTypeParams {generateGrnParams<element::Type_t::bf16>(ngraph::element::bf16),
generateGrnParams<element::Type_t::f16>(ngraph::element::f16),
generateGrnParams<element::Type_t::f32>(ngraph::element::f32)};
std::vector<GrnParams> combinedParams;
std::for_each(grnTypeParams.begin(), grnTypeParams.end(), [&](std::vector<GrnParams> params) {
combinedParams.insert(combinedParams.end(), params.begin(), params.end());
});
return combinedParams;
}
INSTANTIATE_TEST_SUITE_P(smoke_GRN_With_Hardcoded_Refs, ReferenceGrnLayerTest, ::testing::ValuesIn(generateGrnCombinedParams()),
ReferenceGrnLayerTest::getTestCaseName);
} // namespace

35
inference-engine/tests/functional/inference_engine/serialization/single_layer/grn.cpp Normal file
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@ -0,0 +1,35 @@
// Copyright (C) 2020-2021 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#include <vector>
#include "shared_test_classes/single_layer/grn.hpp"
using namespace LayerTestsDefinitions;
namespace {
TEST_P(GrnLayerTest, Serialize) {
Serialize();
}
const std::vector<InferenceEngine::Precision> netPrecisions = {
InferenceEngine::Precision::FP32
};
const auto basicCases = ::testing::Combine(
::testing::ValuesIn(netPrecisions),
::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
::testing::Values(InferenceEngine::Layout::ANY),
::testing::Values(InferenceEngine::Layout::ANY),
// input shapes
::testing::Values(std::vector<size_t>{2, 16, 15, 20}),
// bias
::testing::Values(1e-6f),
::testing::Values(CommonTestUtils::DEVICE_CPU));
INSTANTIATE_TEST_CASE_P(smoke_GRN_Serialization, GrnLayerTest,
basicCases,
GrnLayerTest::getTestCaseName);
} // namespace

37
inference-engine/tests/functional/plugin/cpu/shared_tests_instances/single_layer_tests/grn.cpp Normal file
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@ -0,0 +1,37 @@
// Copyright (C) 2020-2021 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//
#include <vector>
#include "single_layer_tests/grn.hpp"
#include "common_test_utils/test_constants.hpp"
using namespace LayerTestsDefinitions;
namespace {
const std::vector<InferenceEngine::Precision> netPrecisions = {
InferenceEngine::Precision::BF16,
InferenceEngine::Precision::FP16,
InferenceEngine::Precision::FP32,
};
const auto basicCases = ::testing::Combine(
::testing::ValuesIn(netPrecisions),
::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
::testing::Values(InferenceEngine::Layout::ANY),
::testing::Values(InferenceEngine::Layout::ANY),
// input shapes
::testing::Values(std::vector<size_t>{16, 24},
std::vector<size_t>{3, 16, 24},
std::vector<size_t>{1, 3, 30, 30},
std::vector<size_t>{2, 16, 15, 20}),
// bias
::testing::Values(1e-6f, 0.33f, 1.1f, 2.25f, 100.25f),
::testing::Values(CommonTestUtils::DEVICE_CPU));
INSTANTIATE_TEST_CASE_P(smoke_GRN_Basic, GrnLayerTest,
basicCases,
GrnLayerTest::getTestCaseName);
} // namespace

1
inference-engine/tests/ie_test_utils/functional_test_utils/layer_tests_summary/utils/constants.py
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@ -42,6 +42,7 @@ VERIFIED_OP_REFERENCES = [
'GatherElements-6',
'GatherND-5',
'Gelu-7',
'GRN-1',
'GroupConvolution-1',
'GroupConvolutionBackpropData-1',
'GRUSequence-5',

56
ngraph/test/backend/fused_op.in.cpp
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@ -221,62 +221,6 @@ NGRAPH_TEST(${BACKEND_NAME}, mvn_mean_variance_normalization_not_shared_across_c
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, grn_4d)
{
const Shape data_shape{1, 2, 3, 4};
const auto data = make_shared<op::Parameter>(element::f32, data_shape);
float bias{1e-6f};
const auto grn = make_shared<op::GRN>(data, bias);
const auto function = make_shared<Function>(NodeVector{grn}, ParameterVector{data});
auto test_case = test::TestCase<TestEngine>(function);
vector<float> input_data(shape_size(data_shape));
iota(begin(input_data), end(input_data), 1);
test_case.add_input<float>(input_data);
test_case.add_expected_output<float>(
data_shape, {0.0766965f, 0.14142136f, 0.19611613f, 0.24253564f, 0.28216633f, 0.31622776f,
0.34570536f, 0.37139067f, 0.39391932f, 0.41380295f, 0.4314555f, 0.4472136f,
0.9970545f, 0.98994946f, 0.9805807f, 0.97014254f, 0.9593655f, 0.9486833f,
0.9383431f, 0.9284767f, 0.91914505f, 0.9103665f, 0.9021342f, 0.8944272f});
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, DISABLED_grn_2d_with_bias)
{
const Shape data_shape{3, 4};
const auto data = make_shared<op::Parameter>(element::f32, data_shape);
float bias{2.25f};
const auto grn = make_shared<op::GRN>(data, bias);
const auto function = make_shared<Function>(NodeVector{grn}, ParameterVector{data});
auto test_case = test::TestCase<TestEngine>(function);
vector<float> input_data(shape_size(data_shape));
iota(begin(input_data), end(input_data), 1);
test_case.add_input<float>(input_data);
test_case.add_expected_output<float>(data_shape,
{0.5547002f,
0.8f,
0.8944272f,
0.9363292f,
0.95782626f,
0.9701425f,
0.9778024f,
0.98287225f,
0.9863939f,
0.9889363f,
0.9908301f,
0.99227786f});
test_case.run();
}
// TODO: Issue: 37534
NGRAPH_TEST(${BACKEND_NAME}, DISABLED_squared_difference)
{