236 lines
8.6 KiB
C++
236 lines
8.6 KiB
C++
//*****************************************************************************
|
|
// Copyright 2017-2020 Intel Corporation
|
|
//
|
|
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
// you may not use this file except in compliance with the License.
|
|
// You may obtain a copy of the License at
|
|
//
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
//
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
// See the License for the specific language governing permissions and
|
|
// limitations under the License.
|
|
//*****************************************************************************
|
|
|
|
#include "ie_engines.hpp"
|
|
|
|
#include "ngraph/op/get_output_element.hpp"
|
|
#include "ngraph/opsets/opset.hpp"
|
|
#include "ngraph/pass/manager.hpp"
|
|
#include "opset1_upgrade.hpp"
|
|
|
|
using namespace ngraph;
|
|
|
|
namespace
|
|
{
|
|
/// Extracts the data from two blobs and returns them as a pair of vectors.
|
|
template <typename T>
|
|
std::pair<std::vector<T>, std::vector<T>>
|
|
extract_test_results(InferenceEngine::MemoryBlob::CPtr computed,
|
|
InferenceEngine::MemoryBlob::CPtr expected)
|
|
{
|
|
const auto computed_data = computed->rmap();
|
|
const auto expected_data = expected->rmap();
|
|
|
|
const auto* computed_data_buffer = computed_data.template as<const T*>();
|
|
const auto* expected_data_buffer = expected_data.template as<const T*>();
|
|
|
|
std::vector<T> computed_values(computed_data_buffer,
|
|
computed_data_buffer + computed->size());
|
|
std::vector<T> expected_values(expected_data_buffer,
|
|
expected_data_buffer + computed->size());
|
|
|
|
return std::make_pair(std::move(computed_values), std::move(expected_values));
|
|
}
|
|
|
|
/// Compares two blobs containing floating point elements.
|
|
template <typename T>
|
|
typename std::enable_if<std::is_floating_point<T>::value, testing::AssertionResult>::type
|
|
compare_blobs(InferenceEngine::MemoryBlob::CPtr computed,
|
|
InferenceEngine::MemoryBlob::CPtr expected,
|
|
const size_t tolerance_bits)
|
|
{
|
|
const auto test_results = extract_test_results<T>(computed, expected);
|
|
|
|
return ngraph::test::all_close_f(test_results.first, test_results.second, tolerance_bits);
|
|
}
|
|
|
|
/// Compares two blobs containing integer elements.
|
|
template <typename T>
|
|
typename std::enable_if<std::is_integral<T>::value, testing::AssertionResult>::type
|
|
compare_blobs(InferenceEngine::MemoryBlob::CPtr computed,
|
|
InferenceEngine::MemoryBlob::CPtr expected,
|
|
const size_t)
|
|
{
|
|
const auto test_results = extract_test_results<T>(computed, expected);
|
|
|
|
return ngraph::test::all_close<T>(test_results.first, test_results.second);
|
|
}
|
|
|
|
/// Compares two blobs elementwise
|
|
inline testing::AssertionResult compare_blobs(InferenceEngine::MemoryBlob::CPtr computed,
|
|
InferenceEngine::MemoryBlob::CPtr expected,
|
|
const size_t tolerance_bits)
|
|
{
|
|
const auto& computed_precision = computed->getTensorDesc().getPrecision();
|
|
const auto& expected_precision = expected->getTensorDesc().getPrecision();
|
|
|
|
if (computed_precision != expected_precision)
|
|
{
|
|
return testing::AssertionFailure();
|
|
}
|
|
|
|
switch (static_cast<InferenceEngine::Precision::ePrecision>(computed_precision))
|
|
{
|
|
case InferenceEngine::Precision::FP32:
|
|
return compare_blobs<float>(computed, expected, tolerance_bits);
|
|
break;
|
|
case InferenceEngine::Precision::I8:
|
|
return compare_blobs<int8_t>(computed, expected, tolerance_bits);
|
|
break;
|
|
case InferenceEngine::Precision::I16:
|
|
return compare_blobs<int16_t>(computed, expected, tolerance_bits);
|
|
break;
|
|
case InferenceEngine::Precision::I32:
|
|
return compare_blobs<int32_t>(computed, expected, tolerance_bits);
|
|
break;
|
|
case InferenceEngine::Precision::I64:
|
|
return compare_blobs<int64_t>(computed, expected, tolerance_bits);
|
|
break;
|
|
case InferenceEngine::Precision::U8:
|
|
return compare_blobs<uint8_t>(computed, expected, tolerance_bits);
|
|
break;
|
|
case InferenceEngine::Precision::U16:
|
|
return compare_blobs<uint16_t>(computed, expected, tolerance_bits);
|
|
break;
|
|
case InferenceEngine::Precision::U32:
|
|
return compare_blobs<uint32_t>(computed, expected, tolerance_bits);
|
|
break;
|
|
case InferenceEngine::Precision::U64:
|
|
return compare_blobs<uint64_t>(computed, expected, tolerance_bits);
|
|
break;
|
|
case InferenceEngine::Precision::BOOL:
|
|
return compare_blobs<uint8_t>(computed, expected, tolerance_bits);
|
|
break;
|
|
default: THROW_IE_EXCEPTION << "Not implemented yet";
|
|
}
|
|
}
|
|
};
|
|
|
|
test::IE_Engine::IE_Engine(const std::shared_ptr<Function> function, const char* device)
|
|
: m_function{function}
|
|
{
|
|
upgrade_and_validate_function(m_function);
|
|
const auto cnn_network = InferenceEngine::CNNNetwork(m_function);
|
|
m_network_inputs = cnn_network.getInputsInfo();
|
|
m_network_outputs = cnn_network.getOutputsInfo();
|
|
|
|
InferenceEngine::Core ie;
|
|
auto exe_network = ie.LoadNetwork(cnn_network, device);
|
|
m_inference_req = exe_network.CreateInferRequest();
|
|
}
|
|
|
|
void test::IE_Engine::infer()
|
|
{
|
|
if (m_network_inputs.size() != m_allocated_inputs)
|
|
{
|
|
THROW_IE_EXCEPTION << "The tested graph has " << m_network_inputs.size() << " inputs, but "
|
|
<< m_allocated_inputs << " were passed.";
|
|
}
|
|
else
|
|
{
|
|
m_inference_req.Infer();
|
|
}
|
|
}
|
|
|
|
testing::AssertionResult test::IE_Engine::compare_results(const size_t tolerance_bits)
|
|
{
|
|
auto comparison_result = testing::AssertionSuccess();
|
|
|
|
for (const auto& output : m_network_outputs)
|
|
{
|
|
InferenceEngine::MemoryBlob::CPtr computed_output_blob =
|
|
InferenceEngine::as<InferenceEngine::MemoryBlob>(m_inference_req.GetBlob(output.first));
|
|
|
|
const auto& expected_output_blob = m_expected_outputs[output.first];
|
|
|
|
comparison_result =
|
|
compare_blobs(computed_output_blob, expected_output_blob, tolerance_bits);
|
|
|
|
if (comparison_result == testing::AssertionFailure())
|
|
{
|
|
break;
|
|
}
|
|
}
|
|
|
|
return comparison_result;
|
|
}
|
|
|
|
std::shared_ptr<Function>
|
|
test::IE_Engine::upgrade_and_validate_function(const std::shared_ptr<Function> function) const
|
|
{
|
|
pass::Manager passes;
|
|
passes.register_pass<pass::Opset1Upgrade>();
|
|
passes.run_passes(function);
|
|
|
|
static std::set<NodeTypeInfo> ie_ops = get_ie_ops();
|
|
for (const auto& node : function->get_ops())
|
|
{
|
|
if (ie_ops.find(node->get_type_info()) == ie_ops.end())
|
|
{
|
|
if (node->get_type_info() == op::GetOutputElement::type_info)
|
|
{
|
|
// IE currently can handle GetOutputElement op;
|
|
continue;
|
|
}
|
|
else
|
|
{
|
|
THROW_IE_EXCEPTION << "Unsupported operator detected in the graph: "
|
|
<< node->get_type_info().name;
|
|
}
|
|
}
|
|
}
|
|
|
|
return function;
|
|
}
|
|
|
|
std::set<NodeTypeInfo> test::IE_Engine::get_ie_ops() const
|
|
{
|
|
std::set<NodeTypeInfo> ie_ops = get_opset1().get_type_info_set();
|
|
const auto& opset2 = get_opset2().get_type_info_set();
|
|
ie_ops.insert(opset2.begin(), opset2.end());
|
|
const auto& opset3 = get_opset3().get_type_info_set();
|
|
ie_ops.insert(opset3.begin(), opset3.end());
|
|
const auto& opset4 = get_opset4().get_type_info_set();
|
|
ie_ops.insert(opset4.begin(), opset4.end());
|
|
return ie_ops;
|
|
}
|
|
|
|
void test::IE_Engine::reset()
|
|
{
|
|
m_allocated_inputs = 0;
|
|
m_allocated_expected_outputs = 0;
|
|
m_expected_outputs.clear();
|
|
}
|
|
|
|
namespace InferenceEngine
|
|
{
|
|
// those definitions and template specializations are required for clang (both Linux and Mac)
|
|
// Without this section the linker is not able to find destructors for missing TBlob specializations
|
|
// which are instantiated in the unit tests that use TestCase and this engine
|
|
#ifdef __clang__
|
|
template <typename T, typename U>
|
|
TBlob<T, U>::~TBlob()
|
|
{
|
|
free();
|
|
}
|
|
|
|
template class TBlob<unsigned int>;
|
|
template class TBlob<bool>;
|
|
template class TBlob<ngraph::bfloat16>;
|
|
template class TBlob<ngraph::float16>;
|
|
#endif
|
|
}
|