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Removed getLayerByName from public API (#1110)

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* Fixed tests

* Removed getLayerByName from public API
This commit is contained in:
Ilya Lavrenov 2020-06-25 20:00:39 +03:00 committed by GitHub
parent ff769a2e31
commit 3a9db885bf
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GPG Key ID: 4AEE18F83AFDEB23
24 changed files with 274 additions and 206 deletions
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12
inference-engine/include/cpp/ie_cnn_network.h
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@ -197,18 +197,6 @@ public:
CALL_STATUS_FNC(addOutput, layerName, outputIndex);
}
/**
* @deprecated Migrate to IR v10 and work with ngraph::Function directly. The method will be removed in 2021.1
* @copybrief ICNNNetwork::getLayerByName
*
* Wraps ICNNNetwork::getLayerByName
*
* @param layerName Given name of the layer
* @return Status code of the operation. InferenceEngine::OK if succeeded
*/
INFERENCE_ENGINE_DEPRECATED("Migrate to IR v10 and work with ngraph::Function directly. The method will be removed in 2021.1")
CNNLayerPtr getLayerByName(const char* layerName) const;
/**
* @brief Helper method to get collect all input shapes with names of corresponding Data objects
*

12
inference-engine/include/ie_icnn_network.hpp
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@ -125,18 +125,6 @@ public:
virtual StatusCode addOutput(const std::string& layerName, size_t outputIndex = 0,
ResponseDesc* resp = nullptr) noexcept = 0;
/**
* @deprecated Migrate to IR v10 and work with ngraph::Function directly. The method will be removed in 2021.1
* @brief Gets network layer with the given name
*
* @param layerName Given name of the layer
* @param out Pointer to the found CNNLayer object with the given name
* @param resp Pointer to the response message that holds a description of an error if any occurred
* @return Status code of the operation. InferenceEngine::OK if succeeded
*/
INFERENCE_ENGINE_DEPRECATED("Migrate to IR v10 and work with ngraph::Function directly. The method will be removed in 2021.1")
virtual StatusCode getLayerByName(const char* layerName, CNNLayerPtr& out, ResponseDesc* resp) const noexcept = 0;
/**
* @brief Changes the inference batch size.
*

9
inference-engine/src/inference_engine/cnn_network_ngraph_impl.cpp
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@ -226,15 +226,6 @@ void CNNNetworkNGraphImpl::validate(int version) {
_ngraph_function->validate_nodes_and_infer_types();
}
StatusCode CNNNetworkNGraphImpl::getLayerByName(const char* layerName, CNNLayerPtr& out, ResponseDesc* resp) const
noexcept {
if (!cnnNetwork) {
const_cast<CNNNetworkNGraphImpl *>(this)->convertToCNNNetworkImpl();
}
if (!cnnNetwork) return GENERAL_ERROR;
return cnnNetwork->getLayerByName(layerName, out, resp);
}
StatusCode CNNNetworkNGraphImpl::addOutput(const std::string& layerName, size_t outputIndex,
ResponseDesc* resp) noexcept {
IE_PROFILING_AUTO_SCOPE(addOutput)

3
inference-engine/src/inference_engine/cnn_network_ngraph_impl.hpp
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@ -64,9 +64,6 @@ public:
INFERENCE_ENGINE_DEPRECATED("Use ngraph::Function directly")
void addLayer(const CNNLayerPtr& layer) noexcept override;
INFERENCE_ENGINE_DEPRECATED("Use ngraph::Function directly")
StatusCode getLayerByName(const char* layerName, CNNLayerPtr& out, ResponseDesc* resp) const noexcept override;
// public version
StatusCode setBatchSize(size_t size, ResponseDesc* responseDesc) noexcept override;

2
inference-engine/src/legacy_api/include/cnn_network_impl.hpp
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@ -98,7 +98,7 @@ public:
void removeData(const std::string& dataName);
StatusCode getLayerByName(const char* layerName, CNNLayerPtr& out, ResponseDesc* resp) const noexcept override;
StatusCode getLayerByName(const char* layerName, CNNLayerPtr& out, ResponseDesc* resp) const noexcept;
// public version
StatusCode setBatchSize(size_t size, ResponseDesc* responseDesc) noexcept override;

6
inference-engine/src/legacy_api/src/ie_deprecated.cpp
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@ -12,12 +12,6 @@ IE_SUPPRESS_DEPRECATED_START
namespace InferenceEngine {
CNNLayerPtr CNNNetwork::getLayerByName(const char* layerName) const {
CNNLayerPtr layer;
CALL_STATUS_FNC(getLayerByName, layerName, layer);
return layer;
}
CNNLayer::CNNLayer(const LayerParams& prms)
: node(nullptr), name(prms.name), type(prms.type), precision(prms.precision), userValue({0}) {}

11
inference-engine/tests/functional/inference_engine/cnn_network/cnn_ngraph_impl_tests.cpp
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@ -30,6 +30,7 @@
#include <ngraph/op/result.hpp>
#include "common_test_utils/file_utils.hpp"
#include "common_test_utils/common_utils.hpp"
#include "transformations/rt_info/primitives_priority_attribute.hpp"
#include "cnn_network_ngraph_impl.hpp"
@ -205,7 +206,7 @@ TEST(CNNNGraphImplTests, TestSaveAffinity) {
}
InferenceEngine::CNNNetwork cnnNet(ngraph);
auto cnnLayer = cnnNet.getLayerByName("testReLU");
auto cnnLayer = CommonTestUtils::getLayerByName(cnnNet, "testReLU");
ASSERT_NE(nullptr, cnnLayer);
ASSERT_EQ(cnnLayer->affinity, testAffinity);
}
@ -350,15 +351,15 @@ TEST(CNNNGraphImplTests, SaveAttributesAfterConversion) {
}
InferenceEngine::details::CNNNetworkNGraphImpl cnnNet(ngraph);
CNNLayerPtr layer;
ASSERT_EQ(OK, cnnNet.getLayerByName(name.c_str(), layer, nullptr));
auto * icnnnetwork = static_cast<InferenceEngine::ICNNNetwork*>(&cnnNet);
CNNLayerPtr layer = CommonTestUtils::getLayerByName(icnnnetwork, name);
layer->params["test"] = "2";
ASSERT_EQ(OK, cnnNet.getLayerByName(name.c_str(), layer, nullptr));
layer = CommonTestUtils::getLayerByName(icnnnetwork, name);
ASSERT_TRUE(layer->params.find("test") != layer->params.end());
ASSERT_EQ(layer->params["test"], "2");
cnnNet.convertToCNNNetworkImpl();
ASSERT_EQ(OK, cnnNet.getLayerByName(name.c_str(), layer, nullptr));
layer = CommonTestUtils::getLayerByName(icnnnetwork, name);
ASSERT_TRUE(layer->params.find("test") != layer->params.end());
ASSERT_EQ(layer->params["test"], "2");
}

7
inference-engine/tests/functional/inference_engine/local_test.cpp
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@ -6,6 +6,7 @@
#include <ie_core.hpp>
#include <net_pass.h>
#include "common_test_utils/common_utils.hpp"
using namespace ::testing;
using namespace std;
@ -213,12 +214,12 @@ protected:
IE_SUPPRESS_DEPRECATED_START
if (!isLSTM) {
auto power_layer = dynamic_pointer_cast<PowerLayer>(net.getLayerByName("power"));
auto power_layer = dynamic_pointer_cast<PowerLayer>(CommonTestUtils::getLayerByName(net, "power"));
ASSERT_EQ(power_layer->scale, 0.75f);
ASSERT_EQ(power_layer->offset, 0.35f);
ASSERT_EQ(power_layer->power, 0.5f);
auto sum_layer = dynamic_pointer_cast<EltwiseLayer>(net.getLayerByName("sum"));
auto sum_layer = dynamic_pointer_cast<EltwiseLayer>(CommonTestUtils::getLayerByName(net, "sum"));
std::vector<float> ref_coeff{0.77f, 0.33f};
ASSERT_EQ(sum_layer->coeff, ref_coeff);
@ -230,7 +231,7 @@ protected:
InferenceEngine::NetPass::UnrollRNN_if(net, [] (const RNNCellBase& rnn) -> bool { return true; });
net.serialize("UnrollRNN_if.xml");
EXPECT_EQ(0, std::remove("UnrollRNN_if.xml"));
auto lstmcell_layer = dynamic_pointer_cast<ClampLayer>(net.getLayerByName("LSTMCell:split_clip"));
auto lstmcell_layer = dynamic_pointer_cast<ClampLayer>(CommonTestUtils::getLayerByName(net, "LSTMCell:split_clip"));
float ref_coeff = 0.2f;
ASSERT_EQ(lstmcell_layer->min_value, -ref_coeff);

5
inference-engine/tests/functional/inference_engine/ngraph_reshape_tests.cpp
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@ -28,6 +28,7 @@
#include "common_test_utils/test_common.hpp"
#include "common_test_utils/data_utils.hpp"
#include "common_test_utils/file_utils.hpp"
#include "common_test_utils/common_utils.hpp"
#include "generic_ie.hpp"
IE_SUPPRESS_DEPRECATED_START
@ -282,7 +283,7 @@ TEST_F(NGraphReshapeTests, ReshapeNewIRWithNewExtension1) {
SizeVector outDims = output["activation"]->getTensorDesc().getDims();
ASSERT_EQ(outDims, refAfterReshape);
// Convert to CNNNetwork
auto layer = network.getLayerByName("activation");
auto layer = CommonTestUtils::getLayerByName(network, "activation");
ASSERT_EQ("CustomTestLayer", layer->type);
}
@ -352,7 +353,7 @@ TEST_F(NGraphReshapeTests, ReshapeNewIRWithNewExtension2) {
SizeVector outDims = output["activation"]->getTensorDesc().getDims();
ASSERT_EQ(outDims, refAfterReshape);
// Convert to CNNNetwork
auto layer = network.getLayerByName("activation");
auto layer = CommonTestUtils::getLayerByName(network, "activation");
ASSERT_EQ("CustomTestLayer", layer->type);
ASSERT_EQ("false", layer->params["test1"]);
ASSERT_EQ("3", layer->params["test2"]);

3
inference-engine/tests/functional/plugin/myriad/ngraph/conversions/dynamic_shape_resolver.cpp
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@ -11,6 +11,7 @@
#include "ie_common.h"
#include "common_test_utils/test_common.hpp"
#include "common_test_utils/common_utils.hpp"
#include "details/ie_cnn_network_iterator.hpp"
#include <gtest/gtest.h>
@ -36,7 +37,7 @@ public:
protected:
InferenceEngine::CNNLayerPtr getDynamicShapeResolverLayer() const {
return cnnNetwork.getLayerByName(s_FriendlyName);
return CommonTestUtils::getLayerByName(cnnNetwork, s_FriendlyName);
}
InferenceEngine::CNNNetwork cnnNetwork;

3
inference-engine/tests/functional/plugin/shared/src/ngraph_conversion_tests/conv_bias_fusion.cpp
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@ -3,6 +3,7 @@
// SPDX-License-Identifier: Apache-2.0
//
#include "common_test_utils/common_utils.hpp"
#include "ngraph_conversion_tests/conv_bias_fusion.hpp"
#include <ngraph/variant.hpp>
@ -58,7 +59,7 @@ TEST_P(ConvBiasFusion, ConvBiasFusion) {
}
} else {
IE_SUPPRESS_DEPRECATED_START
auto add_layer = net.getLayerByName(getOutputName().c_str());
auto add_layer = CommonTestUtils::getLayerByName(net, getOutputName());
ASSERT_EQ(add_layer->params["originalLayersNames"], "add,conv");
IE_SUPPRESS_DEPRECATED_END
}

26
inference-engine/tests/ie_test_utils/common_test_utils/common_utils.hpp
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@ -9,6 +9,9 @@
#include <iterator>
#include <vector>
#include <cpp/ie_cnn_network.h>
#include <details/ie_cnn_network_iterator.hpp>
namespace CommonTestUtils {
template<typename vecElementType>
@ -32,4 +35,27 @@ inline std::string vec2str(const std::vector<std::vector<vecElementType>> &vec)
return result.str();
}
inline InferenceEngine::CNNLayerPtr getLayerByName(const InferenceEngine::ICNNNetwork * icnnnetwork,
const std::string & layerName) {
IE_SUPPRESS_DEPRECATED_START
InferenceEngine::details::CNNNetworkIterator i(icnnnetwork), end;
while (i != end) {
auto layer = *i;
if (layer->name == layerName)
return layer;
++i;
}
std::stringstream stream;
stream << "Layer " << layerName << " not found in network";
throw InferenceEngine::NotFound(stream.str());
IE_SUPPRESS_DEPRECATED_END
}
inline InferenceEngine::CNNLayerPtr getLayerByName(const InferenceEngine::CNNNetwork & network,
const std::string & layerName) {
const InferenceEngine::ICNNNetwork & icnnnetwork = static_cast<const InferenceEngine::ICNNNetwork&>(network);
return getLayerByName(&icnnnetwork, layerName);
}
} // namespace CommonTestUtils

5
inference-engine/tests_deprecated/functional/shared_tests/ie_class/ie_class.hpp
View File

@ -22,6 +22,7 @@
#include <ngraph/op/subtract.hpp>
#include "common_test_utils/file_utils.hpp"
#include "common_test_utils/common_utils.hpp"
#include "common_test_utils/unicode_utils.hpp"
#include "ngraph_functions/subgraph_builders.hpp"
@ -1293,7 +1294,7 @@ TEST_P(IEClassLoadNetworkTest, QueryNetworkHETEROwithMULTINoThrowv7) {
for (auto && layer : result.supportedLayersMap) {
IE_SUPPRESS_DEPRECATED_START
EXPECT_NO_THROW(actualNetwork.getLayerByName(layer.first.c_str()));
EXPECT_NO_THROW(CommonTestUtils::getLayerByName(actualNetwork, layer.first));
IE_SUPPRESS_DEPRECATED_END
}
} else {
@ -1321,7 +1322,7 @@ TEST_P(IEClassLoadNetworkTest, QueryNetworkMULTIwithHETERONoThrowv7) {
for (auto && layer : result.supportedLayersMap) {
IE_SUPPRESS_DEPRECATED_START
EXPECT_NO_THROW(actualNetwork.getLayerByName(layer.first.c_str()));
EXPECT_NO_THROW(CommonTestUtils::getLayerByName(actualNetwork, layer.first));
IE_SUPPRESS_DEPRECATED_END
}
} else {

7
inference-engine/tests_deprecated/functional/shared_tests/transformations/concat_test.cpp
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@ -5,6 +5,7 @@
#include "low_precision_transformer_single_layer_tests.hpp"
#include "low_precision_transformations/concat.hpp"
#include "low_precision_transformations/eltwise.hpp"
#include "common_test_utils/common_utils.hpp"
ConcatTestModel::ConcatTestModel(
const bool signedIntervals,
@ -90,14 +91,14 @@ bool ConcatTestModel::transform(CNNNetwork& network, LayerTransformation::Params
LowPrecisionTransformer transformer(transformations);
transformer.transform(network);
const CNNLayerPtr concatLayer = network.getLayerByName("concat");
const CNNLayerPtr concatLayer = CommonTestUtils::getLayerByName(network, "concat");
if (concatLayer == nullptr) {
THROW_IE_EXCEPTION << "concat layer was not found";
}
const std::vector<size_t> dims = concatLayer->outData[0]->getDims();
if (dims.size() == 4ul) {
const CNNLayerPtr fakeQuantizeLayer1 = network.getLayerByName("fakeQuantize1");
const CNNLayerPtr fakeQuantizeLayer1 = CommonTestUtils::getLayerByName(network, "fakeQuantize1");
QuantizeLayer* fakeQuantize1 = dynamic_cast<QuantizeLayer*>(fakeQuantizeLayer1.get());
if (fakeQuantize1 == nullptr) {
THROW_IE_EXCEPTION << "incorrect type for layer " << fakeQuantizeLayer1->name;
@ -106,7 +107,7 @@ bool ConcatTestModel::transform(CNNNetwork& network, LayerTransformation::Params
//
}
const CNNLayerPtr fakeQuantizeLayer2 = network.getLayerByName("fakeQuantize2");
const CNNLayerPtr fakeQuantizeLayer2 = CommonTestUtils::getLayerByName(network, "fakeQuantize2");
QuantizeLayer* fakeQuantize2 = dynamic_cast<QuantizeLayer*>(fakeQuantizeLayer2.get());
if (fakeQuantize2 == nullptr) {
THROW_IE_EXCEPTION << "incorrect type for layer " << fakeQuantizeLayer2->name;

3
inference-engine/tests_deprecated/functional/shared_tests/transformations/fq_as_output.cpp
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@ -3,6 +3,7 @@
//
#include "low_precision_transformer_single_layer_tests.hpp"
#include "common_test_utils/common_utils.hpp"
std::string FakeQuantizeAsOutputTest::getName() const {
return "FakeQuantizeAsOutputTest";
@ -14,7 +15,7 @@ bool FakeQuantizeAsOutputTest::transform(CNNNetwork& network, LayerTransformatio
LowPrecisionTransformer transformer(LowPrecisionTransformer::getAllTransformations(params));
transformer.transform(network);
const auto fq = network.getLayerByName("FakeQuantize12");
const auto fq = CommonTestUtils::getLayerByName(network, "FakeQuantize12");
if (fq == nullptr)
THROW_IE_EXCEPTION << "Layer 'FakeQuantize12' should not be transformed";

17
inference-engine/tests_deprecated/functional/shared_tests/transformations/quantization_on_inverted_weights_test.cpp
View File

@ -3,6 +3,7 @@
//
#include "low_precision_transformer_single_layer_tests.hpp"
#include "common_test_utils/common_utils.hpp"
std::string QuantizationOnInvertedWeightsTestModel::getModel(SingleLayerTransformationsTestParams& p) const {
size_t type_size = sizeof(InferenceEngine::PrecisionTrait<InferenceEngine::Precision::FP32>::value_type);
@ -59,13 +60,13 @@ std::string QuantizationOnInvertedWeightsTestModel::getName() const {
}
bool QuantizationOnInvertedWeightsTestModel::transform(CNNNetwork& network, LayerTransformation::Params& params) const {
CNNLayerPtr weightsFakeQuantize = network.getLayerByName("FakeQuantize12");
CNNLayerPtr weightsFakeQuantize = CommonTestUtils::getLayerByName(network, "FakeQuantize12");
Blob::Ptr weights = CNNNetworkHelper::quantizeWeights(*weightsFakeQuantize, false);
CNNLayerPtr biasesConvolutionConst = network.getLayerByName("Const13");
CNNLayerPtr biasesConvolutionConst = CommonTestUtils::getLayerByName(network, "Const13");
Blob::Ptr biases = getBlob(biasesConvolutionConst, "custom");
CNNLayerPtr convolution = network.getLayerByName("Convolution14");
CNNLayerPtr convolution = CommonTestUtils::getLayerByName(network, "Convolution14");
convolution->blobs.emplace("weights", weights);
convolution->blobs.emplace("biases", biases);
@ -73,15 +74,15 @@ bool QuantizationOnInvertedWeightsTestModel::transform(CNNNetwork& network, Laye
weightableLayer->_weights = weights;
weightableLayer->_biases = biases;
CNNLayerPtr weightsConstInput = network.getLayerByName("Const7");
CNNLayerPtr weightsConstInput = CommonTestUtils::getLayerByName(network, "Const7");
CNNNetworkHelper::removeLayer(network, weightsConstInput);
CNNLayerPtr weightsConstInputLow = network.getLayerByName("Const8");
CNNLayerPtr weightsConstInputLow = CommonTestUtils::getLayerByName(network, "Const8");
CNNNetworkHelper::removeLayer(network, weightsConstInputLow);
CNNLayerPtr weightsConstInputHigh = network.getLayerByName("Const9");
CNNLayerPtr weightsConstInputHigh = CommonTestUtils::getLayerByName(network, "Const9");
CNNNetworkHelper::removeLayer(network, weightsConstInputHigh);
CNNLayerPtr weightsConstOutputLow = network.getLayerByName("Const10");
CNNLayerPtr weightsConstOutputLow = CommonTestUtils::getLayerByName(network, "Const10");
CNNNetworkHelper::removeLayer(network, weightsConstOutputLow);
CNNLayerPtr weightsConstOutputHigh = network.getLayerByName("Const11");
CNNLayerPtr weightsConstOutputHigh = CommonTestUtils::getLayerByName(network, "Const11");
CNNNetworkHelper::removeLayer(network, weightsConstOutputHigh);
CNNNetworkHelper::removeLayer(network, weightsFakeQuantize);

17
inference-engine/tests_deprecated/functional/shared_tests/transformations/quantization_on_weights_test.cpp
View File

@ -3,6 +3,7 @@
//
#include "low_precision_transformer_single_layer_tests.hpp"
#include "common_test_utils/common_utils.hpp"
std::string QuantizationOnWeightsTestModel::getModel(SingleLayerTransformationsTestParams& p) const {
size_t type_size = sizeof(InferenceEngine::PrecisionTrait<InferenceEngine::Precision::FP32>::value_type);
@ -59,13 +60,13 @@ std::string QuantizationOnWeightsTestModel::getName() const {
}
bool QuantizationOnWeightsTestModel::transform(CNNNetwork& network, LayerTransformation::Params& params) const {
CNNLayerPtr weightsFakeQuantize = network.getLayerByName("FakeQuantize12");
CNNLayerPtr weightsFakeQuantize = CommonTestUtils::getLayerByName(network, "FakeQuantize12");
Blob::Ptr weights = CNNNetworkHelper::quantizeWeights(*weightsFakeQuantize, false);
CNNLayerPtr biasesConvolutionConst = network.getLayerByName("Const13");
CNNLayerPtr biasesConvolutionConst = CommonTestUtils::getLayerByName(network, "Const13");
Blob::Ptr biases = getBlob(biasesConvolutionConst, "custom");
CNNLayerPtr convolution = network.getLayerByName("Convolution14");
CNNLayerPtr convolution = CommonTestUtils::getLayerByName(network, "Convolution14");
convolution->blobs.emplace("weights", weights);
convolution->blobs.emplace("biases", biases);
@ -73,15 +74,15 @@ bool QuantizationOnWeightsTestModel::transform(CNNNetwork& network, LayerTransfo
weightableLayer->_weights = weights;
weightableLayer->_biases = biases;
CNNLayerPtr weightsConstInput = network.getLayerByName("Const7");
CNNLayerPtr weightsConstInput = CommonTestUtils::getLayerByName(network, "Const7");
CNNNetworkHelper::removeLayer(network, weightsConstInput);
CNNLayerPtr weightsConstInputLow = network.getLayerByName("Const8");
CNNLayerPtr weightsConstInputLow = CommonTestUtils::getLayerByName(network, "Const8");
CNNNetworkHelper::removeLayer(network, weightsConstInputLow);
CNNLayerPtr weightsConstInputHigh = network.getLayerByName("Const9");
CNNLayerPtr weightsConstInputHigh = CommonTestUtils::getLayerByName(network, "Const9");
CNNNetworkHelper::removeLayer(network, weightsConstInputHigh);
CNNLayerPtr weightsConstOutputLow = network.getLayerByName("Const10");
CNNLayerPtr weightsConstOutputLow = CommonTestUtils::getLayerByName(network, "Const10");
CNNNetworkHelper::removeLayer(network, weightsConstOutputLow);
CNNLayerPtr weightsConstOutputHigh = network.getLayerByName("Const11");
CNNLayerPtr weightsConstOutputHigh = CommonTestUtils::getLayerByName(network, "Const11");
CNNNetworkHelper::removeLayer(network, weightsConstOutputHigh);
CNNNetworkHelper::removeLayer(network, weightsFakeQuantize);

16
inference-engine/tests_deprecated/unit/cnn_network/cnn_net_reader_impl_test.cpp
View File

@ -11,6 +11,7 @@
#include "unit_test_utils/mocks/mock_icnn_network.hpp"
#include "unit_test_utils/mocks/mock_iformat_parser.hpp"
#include "common_test_utils/common_utils.hpp"
using namespace testing;
using namespace InferenceEngine;
@ -1748,8 +1749,7 @@ TEST_F(CNNNetReaderImplTest, canRead3DConvolution) {
ResponseDesc resp;
auto network = reader.getNetwork(&resp);
CNNLayerPtr layer;
ASSERT_EQ(OK, network->getLayerByName("3D_conv", layer, nullptr));
CNNLayerPtr layer = CommonTestUtils::getLayerByName(network, "3D_conv");
auto* conv = dynamic_cast<ConvolutionLayer*>(layer.get());
ASSERT_NE(nullptr, conv);
ASSERT_EQ(conv->_kernel[X_AXIS], 5);
@ -1816,9 +1816,7 @@ TEST_F(CNNNetReaderImplTest, canRead3DPooling) {
ResponseDesc resp;
auto network = reader.getNetwork(&resp);
CNNLayerPtr layer;
ASSERT_EQ(OK, network->getLayerByName("3D_pooling", layer, nullptr));
CNNLayerPtr layer = CommonTestUtils::getLayerByName(network, "3D_pooling");
auto* pool = dynamic_cast<PoolingLayer*>(layer.get());
ASSERT_NE(nullptr, pool);
ASSERT_EQ(pool->_kernel[X_AXIS], 5);
@ -2025,9 +2023,7 @@ TEST_F(CNNNetReaderImplTest, canParseSimpleTI) {
auto network = reader.getNetwork(&resp);
ASSERT_NE(nullptr, network) << resp.msg;
CNNLayerPtr layer;
sts = network->getLayerByName("SomeTI", layer, &resp);
ASSERT_EQ(OK, sts) << resp.msg;
CNNLayerPtr layer = CommonTestUtils::getLayerByName(network, "SomeTI");
auto* ti = dynamic_cast<TensorIterator*>(layer.get());
ASSERT_NE(nullptr, ti);
@ -2125,9 +2121,7 @@ TEST_F(CNNNetReaderImplTest, canParseScalar) {
auto net = reader.getNetwork(&resp);
ASSERT_NE(nullptr, net) << resp.msg;
CNNLayerPtr layer;
sts = net->getLayerByName("scalar", layer, &resp);
ASSERT_EQ(OK, sts) << resp.msg;
CNNLayerPtr layer = CommonTestUtils::getLayerByName(net, "scalar");
ASSERT_NE(nullptr, layer.get());
ASSERT_EQ(layer->type, "Const");
auto actualBlob = layer->blobs.begin()->second;

3
inference-engine/tests_deprecated/unit/engines/mkldnn/graph/structure/graph_deconv_concat_tests.cpp
View File

@ -9,6 +9,7 @@
#include "ir_gen_helper.hpp"
#include <ie_core.hpp>
#include "common_test_utils/common_layers_params.hpp"
#include "common_test_utils/common_utils.hpp"
using namespace ::testing;
using namespace std;
@ -331,7 +332,7 @@ protected:
// Compare with reference
auto deconv = network.getLayerByName("Deconvolution_1");
auto deconv = CommonTestUtils::getLayerByName(network, "Deconvolution_1");
InferenceEngine::TBlob<float> deconv_ref(deconv->outData[0]->getTensorDesc());
deconv_ref.allocate();

34
inference-engine/tests_deprecated/unit/engines/mkldnn/normalizer/supported_fusions_test.cpp
View File

@ -13,7 +13,7 @@
#include "common_test_utils/xml_net_builder/xml_net_builder.hpp"
#include "common_test_utils/common_layers_params.hpp"
#include "common_test_utils/data_utils.hpp"
#include "common_test_utils/common_utils.hpp"
struct conv_eltwise_params {
std::vector<size_t> in1;
@ -88,8 +88,8 @@ protected:
InferenceEngine::IExecutableNetwork::Ptr exeNetwork1;
ASSERT_NO_THROW(score_engine->LoadNetwork(exeNetwork1, network, {}));
auto conv = network.getLayerByName("Convolution2");
auto eltwise = network.getLayerByName("Eltwise3");
auto conv = CommonTestUtils::getLayerByName(network, "Convolution2");
auto eltwise = CommonTestUtils::getLayerByName(network, "Eltwise3");
ASSERT_EQ(conv->precision, InferenceEngine::Precision::I8);
ASSERT_EQ(conv->outData[0]->getPrecision(), InferenceEngine::Precision::I8);
@ -148,9 +148,9 @@ protected:
InferenceEngine::IExecutableNetwork::Ptr exeNetwork1;
ASSERT_NO_THROW(score_engine->LoadNetwork(exeNetwork1, network, { }));
auto conv = network.getLayerByName("Convolution2");
auto eltwise = network.getLayerByName("Eltwise3");
auto relu4 = network.getLayerByName("ReLU4");
auto conv = CommonTestUtils::getLayerByName(network, "Convolution2");
auto eltwise = CommonTestUtils::getLayerByName(network, "Eltwise3");
auto relu4 = CommonTestUtils::getLayerByName(network, "ReLU4");
ASSERT_EQ(conv->precision, InferenceEngine::Precision::I8);
ASSERT_EQ(conv->outData[0]->getPrecision(), InferenceEngine::Precision::I8);
@ -209,9 +209,9 @@ protected:
InferenceEngine::IExecutableNetwork::Ptr exeNetwork1;
ASSERT_NO_THROW(score_engine->LoadNetwork(exeNetwork1, network, { }));
auto conv2 = network.getLayerByName("Convolution2");
auto conv3 = network.getLayerByName("Convolution3");
auto eltwise = network.getLayerByName("Eltwise3");
auto conv2 = CommonTestUtils::getLayerByName(network, "Convolution2");
auto conv3 = CommonTestUtils::getLayerByName(network, "Convolution3");
auto eltwise = CommonTestUtils::getLayerByName(network, "Eltwise3");
ASSERT_EQ(conv2->precision, InferenceEngine::Precision::I8);
ASSERT_EQ(conv2->outData[0]->getPrecision(), InferenceEngine::Precision::I8);
@ -268,10 +268,10 @@ protected:
InferenceEngine::IExecutableNetwork::Ptr exeNetwork1;
ASSERT_NO_THROW(score_engine->LoadNetwork(exeNetwork1, network, { }));
auto conv2 = network.getLayerByName("Convolution2");
auto conv3 = network.getLayerByName("Convolution3");
auto eltwise = network.getLayerByName("Eltwise3");
auto relu5 = network.getLayerByName("ReLU5");
auto conv2 = CommonTestUtils::getLayerByName(network, "Convolution2");
auto conv3 = CommonTestUtils::getLayerByName(network, "Convolution3");
auto eltwise = CommonTestUtils::getLayerByName(network, "Eltwise3");
auto relu5 = CommonTestUtils::getLayerByName(network, "ReLU5");
ASSERT_EQ(conv2->precision, InferenceEngine::Precision::I8);
ASSERT_EQ(conv2->outData[0]->getPrecision(), InferenceEngine::Precision::I8);
@ -344,10 +344,10 @@ protected:
InferenceEngine::IExecutableNetwork::Ptr exeNetwork1;
ASSERT_NO_THROW(score_engine->LoadNetwork(exeNetwork1, network, {}));
auto conv2 = network.getLayerByName("Convolution2");
auto conv3 = network.getLayerByName("Convolution3");
auto eltwise = network.getLayerByName("Eltwise3");
auto relu5 = network.getLayerByName("ReLU5");
auto conv2 = CommonTestUtils::getLayerByName(network, "Convolution2");
auto conv3 = CommonTestUtils::getLayerByName(network, "Convolution3");
auto eltwise = CommonTestUtils::getLayerByName(network, "Eltwise3");
auto relu5 = CommonTestUtils::getLayerByName(network, "ReLU5");
ASSERT_EQ(conv2->precision, InferenceEngine::Precision::I8);
ASSERT_EQ(conv2->outData[0]->getPrecision(), InferenceEngine::Precision::I8);

13
inference-engine/tests_deprecated/unit/graph_tools/graph_copy_tests.cpp
View File

@ -5,6 +5,7 @@
#include <gtest/gtest.h>
#include <graph_tools.hpp>
#include <common_test_utils/test_assertions.hpp>
#include <common_test_utils/common_utils.hpp>
#include <unordered_set>
#include <gmock/gmock-generated-function-mockers.h>
#include <gmock/gmock-generated-matchers.h>
@ -93,8 +94,8 @@ TEST_F(GraphCopyTests, canPreserveAttributes) {
ADD_ATTR(1, "id", "r-1-2-3");
ADD_ATTR(2, "id", "r-1-2-3");
CNNNetwork cloned (clone);
auto idMemOutput = cloned.getLayerByName("1")->GetParamAsString("id");
auto idMemInput = cloned.getLayerByName("2")->GetParamAsString("id");
auto idMemOutput = CommonTestUtils::getLayerByName(cloned, "1")->GetParamAsString("id");
auto idMemInput = CommonTestUtils::getLayerByName(cloned, "2")->GetParamAsString("id");
ASSERT_STREQ(idMemInput.c_str(), idMemOutput.c_str());
ASSERT_STREQ(idMemInput.c_str(), "r-1-2-3");
@ -111,12 +112,12 @@ TEST_F(GraphCopyTests, canQuantizeTopology) {
auto iclone = ModelQuantizer<FP32_2_FP32>().quantize(*mockNet, std::vector<float >({1.0f, 1.0f}));
auto clone = CNNNetwork(iclone);
CNNNetBFS(clone.getLayerByName("1"), [&](CNNLayerPtr layer) {
CNNNetBFS(CommonTestUtils::getLayerByName(clone, "1"), [&](CNNLayerPtr layer) {
auto params = getInjectedData<QuantizedLayerParams>(layer);
ASSERT_NE(params, nullptr);
});
CNNNetBFS(clone.getLayerByName("3"), [&](CNNLayerPtr layer) {
CNNNetBFS(CommonTestUtils::getLayerByName(clone, "3"), [&](CNNLayerPtr layer) {
auto params = getInjectedData<QuantizedLayerParams>(layer);
ASSERT_NE(params, nullptr);
});
@ -176,7 +177,7 @@ TEST(CNNSpecificGraphCopyTests, copyNetworkWithClampLayer) {
auto copied_net = CNNNetwork(copied_net_ptr);
//check that Clamp layer was properly copied
auto layer = std::dynamic_pointer_cast<ClampLayer>(copied_net.getLayerByName("ClampLayer"));
auto layer = std::dynamic_pointer_cast<ClampLayer>(CommonTestUtils::getLayerByName(copied_net, "ClampLayer"));
ASSERT_NE(layer, nullptr) << "Could not perform dynamic cast from base pointer to Clamp layer pointer. "
"Net copy could be incorrect.";
}
@ -310,7 +311,7 @@ TEST(CNNSpecificGraphCopyTests, copyNetworkWithDeconvolution) {
auto copied_net = CNNNetwork(copied_net_ptr);
// check that Clamp layer was properly copied
auto layer = std::dynamic_pointer_cast<DeconvolutionLayer>(copied_net.getLayerByName("upsample_merged"));
auto layer = std::dynamic_pointer_cast<DeconvolutionLayer>(CommonTestUtils::getLayerByName(copied_net, "upsample_merged"));
ASSERT_NE(layer, nullptr) << "Could not perform dynamic cast from base pointer to Deconvolution layer pointer. "
"Net copy could be incorrect.";
}

5
inference-engine/tests_deprecated/unit/graph_tools/graph_test_base.hpp
View File

@ -11,6 +11,7 @@
#include "details/ie_cnn_network_tools.h"
#include "unit_test_utils/mocks/mock_icnn_network.hpp"
#include "common_test_utils/common_utils.hpp"
namespace GraphTest {
@ -116,7 +117,7 @@ class GraphTestsBase : public ::testing::Test {
long int nForward = 0;
CNNLayerPtr layerExist;
try {
layerExist = wrap.getLayerByName(a.c_str());
layerExist = CommonTestUtils::getLayerByName(wrap, a.c_str());
if (!layerExist) {
return 0;
}
@ -144,7 +145,7 @@ class GraphTestsBase : public ::testing::Test {
int countBackwardConnections(std::string a, std::string b, int from_port_id=-1) {
CNNLayerPtr layerExist;
try {
layerExist = wrap.getLayerByName(b.c_str());
layerExist = CommonTestUtils::getLayerByName(wrap, b.c_str());
if (!layerExist) {
return 0;
}

85
inference-engine/tests_deprecated/unit/graph_tools/graph_tools_test.cpp
View File

@ -14,6 +14,7 @@
#include <memory>
#include "details/ie_cnn_network_tools.h"
#include "details/ie_cnn_network_iterator.hpp"
#include <common_test_utils/common_utils.hpp>
using namespace testing;
using namespace InferenceEngine;
@ -346,7 +347,7 @@ TEST_F(GraphToolsTest, CNNNetSwapLayersSwapWithItself) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("2");
auto l = CommonTestUtils::getLayerByName(wrap, "2");
ASSERT_NO_THROW(CNNNetSwapLayers(l, l));
@ -366,8 +367,8 @@ TEST_F(GraphToolsTest, CNNNetSwapLayersSimpleCase_1) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("1");
auto r = wrap.getLayerByName("2");
auto l = CommonTestUtils::getLayerByName(wrap, "1");
auto r = CommonTestUtils::getLayerByName(wrap, "2");
ASSERT_NO_THROW(CNNNetSwapLayers(l, r));
@ -387,8 +388,8 @@ TEST_F(GraphToolsTest, CNNNetSwapLayersSimpleCase_2) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("2");
auto r = wrap.getLayerByName("3");
auto l = CommonTestUtils::getLayerByName(wrap, "2");
auto r = CommonTestUtils::getLayerByName(wrap, "3");
ASSERT_NO_THROW(CNNNetSwapLayers(l, r));
@ -409,8 +410,8 @@ TEST_F(GraphToolsTest, CNNNetSwapLayersSimpleCase_3) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("1");
auto r = wrap.getLayerByName("2");
auto l = CommonTestUtils::getLayerByName(wrap, "1");
auto r = CommonTestUtils::getLayerByName(wrap, "2");
ASSERT_NO_THROW(CNNNetSwapLayers(l, r));
@ -435,8 +436,8 @@ TEST_F(GraphToolsTest, CNNNetSwapLayersDoesSwapDims) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("1");
auto r = wrap.getLayerByName("2");
auto l = CommonTestUtils::getLayerByName(wrap, "1");
auto r = CommonTestUtils::getLayerByName(wrap, "2");
ASSERT_NO_THROW(CNNNetSwapLayers(l, r));
@ -462,8 +463,8 @@ TEST_F(GraphToolsTest, CNNNetSwapLayersSimpleCase_4) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("2");
auto r = wrap.getLayerByName("4");
auto l = CommonTestUtils::getLayerByName(wrap, "2");
auto r = CommonTestUtils::getLayerByName(wrap, "4");
ASSERT_NO_THROW(CNNNetSwapLayers(l, r));
@ -486,8 +487,8 @@ TEST_F(GraphToolsTest, CNNNetSwapLayersSplit) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("2");
auto r = wrap.getLayerByName("3");
auto l = CommonTestUtils::getLayerByName(wrap, "2");
auto r = CommonTestUtils::getLayerByName(wrap, "3");
ASSERT_NO_THROW(CNNNetSwapLayers(l, r));
@ -507,8 +508,8 @@ TEST_F(GraphToolsTest, CNNNetSwapLayersSplit_2) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("1");
auto r = wrap.getLayerByName("2");
auto l = CommonTestUtils::getLayerByName(wrap, "1");
auto r = CommonTestUtils::getLayerByName(wrap, "2");
ASSERT_NO_THROW(CNNNetSwapLayers(l, r));
@ -532,8 +533,8 @@ TEST_F(GraphToolsTest, CNNNetSwapLayersSplit_3) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("1");
auto r = wrap.getLayerByName("2");
auto l = CommonTestUtils::getLayerByName(wrap, "1");
auto r = CommonTestUtils::getLayerByName(wrap, "2");
ASSERT_NO_THROW(CNNNetSwapLayers(l, r));
@ -560,8 +561,8 @@ TEST_F(GraphToolsTest, CNNNetSwapLayersSplit_4) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("1");
auto r = wrap.getLayerByName("2");
auto l = CommonTestUtils::getLayerByName(wrap, "1");
auto r = CommonTestUtils::getLayerByName(wrap, "2");
ASSERT_NO_THROW(CNNNetSwapLayers(l, r));
@ -590,8 +591,8 @@ TEST_F(GraphToolsTest, CanNotInsertLayerIntoNonAdjiacendLayers) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("1");
auto r = wrap.getLayerByName("3");
auto l = CommonTestUtils::getLayerByName(wrap, "1");
auto r = CommonTestUtils::getLayerByName(wrap, "3");
ASSERT_ANY_THROW(CNNNetworkInsertLayer(l, r, createGenericLayer("3")));
}
@ -608,8 +609,8 @@ TEST_F(GraphToolsTest, CNNNetworkInsertLayerSimpleCase) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("1");
auto r = wrap.getLayerByName("2");
auto l = CommonTestUtils::getLayerByName(wrap, "1");
auto r = CommonTestUtils::getLayerByName(wrap, "2");
CNNNetworkInsertLayer(l, r, createGenericLayer("3"));
@ -630,8 +631,8 @@ TEST_F(GraphToolsTest, CNNNetworkInsertLayerSimpleCaseWithMultipleOutputs) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("1");
auto r = wrap.getLayerByName("3");
auto l = CommonTestUtils::getLayerByName(wrap, "1");
auto r = CommonTestUtils::getLayerByName(wrap, "3");
CNNNetworkInsertLayer(l, r, createGenericLayer("4"));
@ -654,8 +655,8 @@ TEST_F(GraphToolsTest, CNNNetworkInsertLayerSimpleCaseWithMultipleInputs) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("3");
auto r = wrap.getLayerByName("2");
auto l = CommonTestUtils::getLayerByName(wrap, "3");
auto r = CommonTestUtils::getLayerByName(wrap, "2");
CNNNetworkInsertLayer(l, r, createGenericLayer("4"));
@ -678,9 +679,9 @@ TEST_F(GraphToolsTest, CNNNetworkInsertLayerSplitAndConcat) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("1");
auto r = wrap.getLayerByName("2");
auto r2 = wrap.getLayerByName("3");
auto l = CommonTestUtils::getLayerByName(wrap, "1");
auto r = CommonTestUtils::getLayerByName(wrap, "2");
auto r2 = CommonTestUtils::getLayerByName(wrap, "3");
CNNNetworkInsertLayer(l, r, createGenericLayer("4"), 1);
CNNNetworkInsertLayer(l, r2, createGenericLayer("5"), 2);
@ -705,7 +706,7 @@ TEST_F(GraphToolsTest, CNNNetworkInsertAfterLastLayer) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
auto l = wrap.getLayerByName("2");
auto l = CommonTestUtils::getLayerByName(wrap, "2");
CNNNetworkInsertLayer(l, nullptr, createGenericLayer("3"));
@ -726,7 +727,7 @@ TEST_F(GraphToolsTest, CNNNetworkInsertAfterAll) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
CNNNetworkInsertLayer(wrap.getLayerByName("1"), nullptr, createGenericLayer("5"));
CNNNetworkInsertLayer(CommonTestUtils::getLayerByName(wrap, "1"), nullptr, createGenericLayer("5"));
ASSERT_CONNECTION(1, 5);
ASSERT_CONNECTION(5, 2);
@ -747,7 +748,7 @@ TEST_F(GraphToolsTest, CNNNetworkInsertAllAfterSplit) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
CNNNetworkInsertLayer(wrap.getLayerByName("1"), nullptr, createGenericLayer("5"));
CNNNetworkInsertLayer(CommonTestUtils::getLayerByName(wrap, "1"), nullptr, createGenericLayer("5"));
ASSERT_CONNECTION(1, 5);
ASSERT_CONNECTION(5, 2);
@ -769,7 +770,7 @@ TEST_F(GraphToolsTest, CNNNetworkInsert1AfterSplitBeforeEltwise) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
CNNNetworkInsertLayer(wrap.getLayerByName("1"), wrap.getLayerByName("4"), createGenericLayer("5"));
CNNNetworkInsertLayer(CommonTestUtils::getLayerByName(wrap, "1"), CommonTestUtils::getLayerByName(wrap, "4"), createGenericLayer("5"));
ASSERT_CONNECTION(1, 3);
ASSERT_CONNECTION(1, 5);
@ -792,7 +793,7 @@ TEST_F(GraphToolsTest, CNNNetworkInsert1AfterSplit) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
CNNNetworkInsertLayer(wrap.getLayerByName("1"), wrap.getLayerByName("4"), createGenericLayer("5"));
CNNNetworkInsertLayer(CommonTestUtils::getLayerByName(wrap, "1"), CommonTestUtils::getLayerByName(wrap, "4"), createGenericLayer("5"));
ASSERT_CONNECTION(1, 2);
ASSERT_CONNECTION(1, 3);
@ -815,7 +816,7 @@ TEST_F(GraphToolsTest, CNNNetworkInsertAfter2ConnectionsToEltwise) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
CNNNetworkInsertLayer(wrap.getLayerByName("1"), wrap.getLayerByName("2"), createGenericLayer("5"));
CNNNetworkInsertLayer(CommonTestUtils::getLayerByName(wrap, "1"), CommonTestUtils::getLayerByName(wrap, "2"), createGenericLayer("5"));
ASSERT_CONNECTION(1, 5);
ASSERT_MN_CONNECTIONS(5, 2, 1, 2);
@ -855,8 +856,8 @@ TEST_F(GraphToolsTest, CNNNetworkRemoveInputOrOutputLayer) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
ASSERT_ANY_THROW(CNNNetworkRemoveLayer(wrap.getLayerByName("1")));
ASSERT_ANY_THROW(CNNNetworkRemoveLayer(wrap.getLayerByName("3")));
ASSERT_ANY_THROW(CNNNetworkRemoveLayer(CommonTestUtils::getLayerByName(wrap, "1")));
ASSERT_ANY_THROW(CNNNetworkRemoveLayer(CommonTestUtils::getLayerByName(wrap, "3")));
}
TEST_F(GraphToolsTest, CNNNetworkRemoveLayerThaHas2Outputs) {
@ -876,7 +877,7 @@ TEST_F(GraphToolsTest, CNNNetworkRemoveLayerThaHas2Outputs) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
CNNNetworkRemoveLayer(wrap.getLayerByName("2"));
CNNNetworkRemoveLayer(CommonTestUtils::getLayerByName(wrap, "2"));
ASSERT_2_CONNECTIONS(1, 3);
ASSERT_CONNECTION(1, 4);
@ -904,7 +905,7 @@ TEST_F(GraphToolsTest, CNNNetworkRemoveLayerSplit) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
CNNNetworkRemoveLayer(wrap.getLayerByName("2"));
CNNNetworkRemoveLayer(CommonTestUtils::getLayerByName(wrap, "2"));
ASSERT_2_CONNECTIONS(1, 3);
// means all remained references removed
@ -934,7 +935,7 @@ TEST_F(GraphToolsTest, CNNNetworkRemoveLayerSplit2) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
CNNNetworkRemoveLayer(wrap.getLayerByName("2"));
CNNNetworkRemoveLayer(CommonTestUtils::getLayerByName(wrap, "2"));
ASSERT_2_CONNECTIONS(1, 3);
ASSERT_3_CONNECTIONS(1, 4);
@ -962,7 +963,7 @@ TEST_F(GraphToolsTest, CNNNetworkRemoveSimpleLayer) {
return l== nullptr ? GENERAL_ERROR : OK;
})));
CNNNetworkRemoveLayer(wrap.getLayerByName("2"));
CNNNetworkRemoveLayer(CommonTestUtils::getLayerByName(wrap, "2"));
ASSERT_CONNECTION(1, 3);

176
inference-engine/tests_deprecated/unit/inference_engine_tests/util_const_infer_test.cpp
View File

@ -19,6 +19,7 @@
#include "util_const_infer_test.hpp"
#include <details/ie_cnn_network_tools.h>
#include <precision_utils.h>
#include "common_test_utils/common_utils.hpp"
namespace IE = InferenceEngine;
@ -241,8 +242,8 @@ TEST_F(RemoveLayerTests, canTrimL2) {
ASSERT_EQ(newLayer_names, refNewLayers);
IE::CNNNetwork cnnNetwork(net);
ASSERT_THROW(cnnNetwork.getLayerByName("layer2"), IE::NotFound);
auto newLayer = cnnNetwork.getLayerByName(refNewLayers[0].c_str());
ASSERT_THROW(CommonTestUtils::getLayerByName(cnnNetwork, "layer2"), IE::NotFound);
auto newLayer = CommonTestUtils::getLayerByName(cnnNetwork, refNewLayers[0].c_str());
ASSERT_EQ(newLayer->type, "Const");
ASSERT_EQ(constData["data5"], newLayer->blobs.at("custom"));
ASSERT_EQ(nullptr, net->getData("data7"));
@ -283,11 +284,14 @@ TEST_F(RemoveLayerTests, canTrimI1andL1) {
for (auto layer : newLayers) newLayer_names.push_back(layer->name);
ASSERT_EQ(newLayer_names, refNewLayers);
IE::CNNLayerPtr layer;
ASSERT_EQ(IE::NOT_FOUND, net->getLayerByName("input1", layer, nullptr));
ASSERT_EQ(nullptr, layer);
ASSERT_EQ(IE::NOT_FOUND, net->getLayerByName("layer1", layer, nullptr));
ASSERT_EQ(nullptr, layer);
IE::CNNNetwork cnnNetwork(net);
ASSERT_THROW(cnnNetwork.getLayerByName("input1"), IE::NotFound);
ASSERT_THROW(cnnNetwork.getLayerByName("layer1"), IE::NotFound);
auto newLayerD4 = cnnNetwork.getLayerByName(refNewLayers[0].c_str());
auto newLayerD7 = cnnNetwork.getLayerByName(refNewLayers[1].c_str());
auto newLayerD4 = CommonTestUtils::getLayerByName(cnnNetwork, refNewLayers[0]);
auto newLayerD7 = CommonTestUtils::getLayerByName(cnnNetwork, refNewLayers[1]);
auto newData4 = net->getData("data4__layer4");
auto newData7 = net->getData("data7__layer2");
ASSERT_EQ(newLayerD4->type, "Const");
@ -471,7 +475,7 @@ TEST_F(RemoveLayerTests, notTrimFirstConstInput) {
ASSERT_EQ(net->allLayers().size(), originalLayersNum);
IE::CNNNetwork cnnNetwork(net);
auto input4 = cnnNetwork.getLayerByName(constLayer->name.c_str());
auto input4 = CommonTestUtils::getLayerByName(cnnNetwork, constLayer->name.c_str());
ASSERT_EQ(data10->getInputTo().size(), 1);
ASSERT_EQ(data10->getCreatorLayer().lock(), input4);
ASSERT_EQ(layer6->insData.size(), 2);
@ -491,7 +495,7 @@ TEST_F(RemoveLayerTests, canSaveConstForEltWise) {
testTransformator->trimShapeInputs({input2}, sortedLayers);
IE::CNNNetwork cnnNetwork(net);
ASSERT_NO_THROW(input2 = cnnNetwork.getLayerByName(input2->name.c_str()));
ASSERT_NO_THROW(input2 = CommonTestUtils::getLayerByName(cnnNetwork, input2->name.c_str()));
ASSERT_EQ(net->allLayers().size(), 10);
ASSERT_EQ(layer1->insData.size(), 2);
ASSERT_EQ(layer1->insData[1].lock(), data2);
@ -512,7 +516,7 @@ TEST_F(RemoveLayerTests, canSaveDataWithMultipleInputTo) {
testTransformator->trimShapeInputs({input3}, sortedLayers);
IE::CNNNetwork cnnNetwork(net);
ASSERT_NO_THROW(input3 = cnnNetwork.getLayerByName(input3->name.c_str()));
ASSERT_NO_THROW(input3 = CommonTestUtils::getLayerByName(cnnNetwork, input3->name.c_str()));
ASSERT_EQ(net->allLayers().size(), originalLayersNum);
ASSERT_EQ(layer2->insData.size(), 2);
ASSERT_EQ(layer2->insData[0].lock(), getData("data2"));
@ -542,7 +546,7 @@ TEST_F(RemoveLayerTests, canFoldConstSubgraphToConst) {
ASSERT_EQ(net->allLayers().size(), originalLayersNum - 7);
ASSERT_EQ(newLayer_names, refNewLayers);
IE::CNNNetwork cnnNetwork(net);
auto newLayer = cnnNetwork.getLayerByName(refNewLayers[0].c_str());
auto newLayer = CommonTestUtils::getLayerByName(cnnNetwork, refNewLayers[0].c_str());
ASSERT_EQ(newLayer->type, "Const");
ASSERT_EQ(newLayer->outData[0], getData("data9"));
}
@ -604,7 +608,7 @@ TEST_F(RemoveLayerTests, canFoldConstSubgraphs) {
IE::CNNNetwork cnnNetwork(net);
ASSERT_EQ(net->allLayers().size(), originalLayersNum - 7);
auto newLayer = cnnNetwork.getLayerByName(refNewLayers[0].c_str());
auto newLayer = CommonTestUtils::getLayerByName(cnnNetwork, refNewLayers[0].c_str());
auto actualBlob = newLayer->blobs["custom"];
ASSERT_NE(actualBlob, nullptr);
ASSERT_FALSE(actualBlob->buffer() == nullptr);
@ -677,7 +681,7 @@ TEST_F(RemoveLayerTests, canFullTrim) {
IE::CNNNetwork cnnNetwork(net);
std::string newName = "layer5__data9__Const";
ASSERT_THROW(cnnNetwork.getLayerByName(newName.c_str()), IE::NotFound);
ASSERT_THROW(CommonTestUtils::getLayerByName(cnnNetwork, newName.c_str()), IE::NotFound);
ASSERT_EQ(net->allLayers().size(), 2);
ASSERT_EQ(layer6->insData.size(), 1);
ASSERT_EQ(layer6->insData[0].lock(), getData("data10"));
@ -754,14 +758,14 @@ TEST_F(AdvancedShapeInferTests, canReshape) {
std::map<std::string, IE::SizeVector> inputShapes = {{"data2", newShape}};
cnnNetwork.reshape(inputShapes);
ASSERT_NO_THROW(cnnNetwork.getLayerByName("layer2"));
ASSERT_NO_THROW(CommonTestUtils::getLayerByName(cnnNetwork, "layer2"));
ASSERT_EQ(getData("data3")->getTensorDesc().getDims(), IE::SizeVector{3});
ASSERT_EQ(net->allLayers().size(), originalLayersNum);
IE::ConstTransformer transformator(net.get());
transformator.fullTrim();
ASSERT_THROW(cnnNetwork.getLayerByName("layer2"), IE::NotFound);
ASSERT_THROW(CommonTestUtils::getLayerByName(cnnNetwork, "layer2"), IE::NotFound);
ASSERT_EQ(getData("data4")->getTensorDesc().getDims(), newShape);
ASSERT_EQ(net->allLayers().size(), originalLayersNum - 1);
}
@ -1038,7 +1042,9 @@ TEST_F(AdvancedShapeInferTests, MulWithTensorConstInferTest) {
transformator.foldConstSubgraphs();
switch(precisionOutData) {
case IE::Precision::U8: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<uint8_t *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<uint8_t *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1046,7 +1052,9 @@ TEST_F(AdvancedShapeInferTests, MulWithTensorConstInferTest) {
break;
}
case IE::Precision::I32: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1054,7 +1062,9 @@ TEST_F(AdvancedShapeInferTests, MulWithTensorConstInferTest) {
break;
}
case IE::Precision::I64: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<long long int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<long long int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1062,7 +1072,9 @@ TEST_F(AdvancedShapeInferTests, MulWithTensorConstInferTest) {
break;
}
case IE::Precision::U64: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<unsigned long long int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<unsigned long long int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1070,7 +1082,9 @@ TEST_F(AdvancedShapeInferTests, MulWithTensorConstInferTest) {
break;
}
case IE::Precision::FP16: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<IE::ie_fp16 *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<IE::ie_fp16 *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1078,7 +1092,9 @@ TEST_F(AdvancedShapeInferTests, MulWithTensorConstInferTest) {
break;
}
case IE::Precision::FP32: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<float *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<float *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1165,7 +1181,9 @@ TEST_F(AdvancedShapeInferTests, MulWithScalarConstInferTest) {
transformator.foldConstSubgraphs();
switch(precisionOutData) {
case IE::Precision::U8: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<uint8_t *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<uint8_t *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1173,7 +1191,9 @@ TEST_F(AdvancedShapeInferTests, MulWithScalarConstInferTest) {
break;
}
case IE::Precision::I32: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1181,7 +1201,9 @@ TEST_F(AdvancedShapeInferTests, MulWithScalarConstInferTest) {
break;
}
case IE::Precision::I64: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<long long int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<long long int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1189,7 +1211,9 @@ TEST_F(AdvancedShapeInferTests, MulWithScalarConstInferTest) {
break;
}
case IE::Precision::U64: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<unsigned long long int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<unsigned long long int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1197,7 +1221,9 @@ TEST_F(AdvancedShapeInferTests, MulWithScalarConstInferTest) {
break;
}
case IE::Precision::FP16: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<IE::ie_fp16 *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<IE::ie_fp16 *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1205,7 +1231,9 @@ TEST_F(AdvancedShapeInferTests, MulWithScalarConstInferTest) {
break;
}
case IE::Precision::FP32: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<float *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<float *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1291,7 +1319,9 @@ TEST_F(AdvancedShapeInferTests, AddWithScalarConstInferTest) {
transformator.foldConstSubgraphs();
switch(precisionOutData) {
case IE::Precision::U8: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<uint8_t *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<uint8_t *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1299,7 +1329,9 @@ TEST_F(AdvancedShapeInferTests, AddWithScalarConstInferTest) {
break;
}
case IE::Precision::I32: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1307,7 +1339,9 @@ TEST_F(AdvancedShapeInferTests, AddWithScalarConstInferTest) {
break;
}
case IE::Precision::I64: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<long long int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<long long int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1315,7 +1349,9 @@ TEST_F(AdvancedShapeInferTests, AddWithScalarConstInferTest) {
break;
}
case IE::Precision::U64: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<unsigned long long int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<unsigned long long int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1323,7 +1359,9 @@ TEST_F(AdvancedShapeInferTests, AddWithScalarConstInferTest) {
break;
}
case IE::Precision::FP16: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<IE::ie_fp16 *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<IE::ie_fp16 *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1331,7 +1369,9 @@ TEST_F(AdvancedShapeInferTests, AddWithScalarConstInferTest) {
break;
}
case IE::Precision::FP32: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<float *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<float *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1417,7 +1457,9 @@ TEST_F(AdvancedShapeInferTests, AddWithTensorConstInferTest) {
transformator.foldConstSubgraphs();
switch(precisionOutData) {
case IE::Precision::U8: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<uint8_t *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<uint8_t *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1425,7 +1467,9 @@ TEST_F(AdvancedShapeInferTests, AddWithTensorConstInferTest) {
break;
}
case IE::Precision::I32: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1433,7 +1477,9 @@ TEST_F(AdvancedShapeInferTests, AddWithTensorConstInferTest) {
break;
}
case IE::Precision::I64: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<long long int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<long long int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1441,7 +1487,9 @@ TEST_F(AdvancedShapeInferTests, AddWithTensorConstInferTest) {
break;
}
case IE::Precision::U64: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<unsigned long long int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<unsigned long long int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1449,7 +1497,9 @@ TEST_F(AdvancedShapeInferTests, AddWithTensorConstInferTest) {
break;
}
case IE::Precision::FP16: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<IE::ie_fp16 *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<IE::ie_fp16 *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1457,7 +1507,9 @@ TEST_F(AdvancedShapeInferTests, AddWithTensorConstInferTest) {
break;
}
case IE::Precision::FP32: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<float *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<float *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1543,7 +1595,9 @@ TEST_F(AdvancedShapeInferTests, AddWithBroadcastingConstInferTest) {
transformator.foldConstSubgraphs();
switch(precisionOutData) {
case IE::Precision::U8: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<uint8_t *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<uint8_t *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1551,7 +1605,9 @@ TEST_F(AdvancedShapeInferTests, AddWithBroadcastingConstInferTest) {
break;
}
case IE::Precision::I32: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1559,7 +1615,9 @@ TEST_F(AdvancedShapeInferTests, AddWithBroadcastingConstInferTest) {
break;
}
case IE::Precision::I64: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<long long int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<long long int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1567,7 +1625,9 @@ TEST_F(AdvancedShapeInferTests, AddWithBroadcastingConstInferTest) {
break;
}
case IE::Precision::U64: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<unsigned long long int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<unsigned long long int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1575,7 +1635,9 @@ TEST_F(AdvancedShapeInferTests, AddWithBroadcastingConstInferTest) {
break;
}
case IE::Precision::FP16: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<IE::ie_fp16 *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<IE::ie_fp16 *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1583,7 +1645,9 @@ TEST_F(AdvancedShapeInferTests, AddWithBroadcastingConstInferTest) {
break;
}
case IE::Precision::FP32: {
auto *l = cnnNetwork.getLayerByName("addLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<float *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("addLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<float *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1669,7 +1733,9 @@ TEST_F(AdvancedShapeInferTests, MulWithBroadcastingConstInferTest) {
transformator.foldConstSubgraphs();
switch(precisionOutData) {
case IE::Precision::U8: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<uint8_t *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<uint8_t *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1677,7 +1743,9 @@ TEST_F(AdvancedShapeInferTests, MulWithBroadcastingConstInferTest) {
break;
}
case IE::Precision::I32: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1685,7 +1753,9 @@ TEST_F(AdvancedShapeInferTests, MulWithBroadcastingConstInferTest) {
break;
}
case IE::Precision::I64: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<long long int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<long long int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1693,7 +1763,9 @@ TEST_F(AdvancedShapeInferTests, MulWithBroadcastingConstInferTest) {
break;
}
case IE::Precision::U64: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<unsigned long long int *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<unsigned long long int *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1701,7 +1773,9 @@ TEST_F(AdvancedShapeInferTests, MulWithBroadcastingConstInferTest) {
break;
}
case IE::Precision::FP16: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<IE::ie_fp16 *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<IE::ie_fp16 *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);
@ -1709,7 +1783,9 @@ TEST_F(AdvancedShapeInferTests, MulWithBroadcastingConstInferTest) {
break;
}
case IE::Precision::FP32: {
auto *l = cnnNetwork.getLayerByName("mulLayer__data3__Const").get()->blobs.at("custom")->cbuffer().as<float *>();
InferenceEngine::CNNLayerPtr layer;
ASSERT_EQ(InferenceEngine::OK, net->getLayerByName("mulLayer__data3__Const", layer, nullptr));
auto *l = layer->blobs.at("custom")->cbuffer().as<float *>();
ASSERT_EQ(l[0], ref[0]);
ASSERT_EQ(l[1], ref[1]);
ASSERT_EQ(l[2], ref[2]);