Substitute soft sign pass port to ngraph (#8167)
* add base ngraph::SoftSign operation wrapper; add substite softsign pass draft code * add SoftSign convertor from ngraph to CNNNetwork * add unit tests; write DoTransformation * cpplint fixes * add pass description * cleanups; always use add layer * remove bf16 since it is CPU specific * add softsign evaluate unit test; code review fixes * add unit tests on checking const values * inherit softsign from :UnaryElementwiseArithmetic; code review fixes * remove unneeded visit_attributes * remove NGRAPH_TYPE_CASE macro * use ngraph::op::util::get_single_value in pattern checking * use legacy SubstituteSoftSignPass if there are FQ layers; build fix * remvoe deprecated softsign tests * fix deprecated error * add draft unit tests on softsign operation with new api * use new test API for softsign * use another evaluate virtual method
This commit is contained in:
Evgeny Kotov
GitHub
parent
95e1a423c6
commit
6860fd3ef4
@ -70,6 +70,7 @@
|
||||
#include "transformations/op_conversions/lstm_cell_decomposition.hpp"
|
||||
#include "transformations/remove_single_input_concat.hpp"
|
||||
#include "transformations/broadcast_const.hpp"
|
||||
#include "transformations/substitute_softsign.hpp"
|
||||
|
||||
#include <ngraph/opsets/opset7.hpp>
|
||||
|
||||
@ -713,6 +714,7 @@ void GNAPlugin::LoadNetwork(CNNNetwork & _network) {
|
||||
manager.register_pass<InsertTransposeAfterConvOrPool>();
|
||||
manager.register_pass<ReorderActivationAndPooling>();
|
||||
manager.register_pass<RemoveSingleInputConcat>();
|
||||
manager.register_pass<SubstituteSoftsign>();
|
||||
manager.register_pass<ngraph::pass::ConvertOpSet3ToOpSet2>();
|
||||
manager.register_pass<ngraph::pass::ConvertOpSet2ToOpSet1>();
|
||||
manager.register_pass<ngraph::pass::ConvertOpSet1ToLegacy>();
|
||||
@ -781,6 +783,9 @@ void GNAPlugin::LoadNetwork(CNNNetwork & _network) {
|
||||
passes->registerPass<SubstituteScaleShiftBroadCastPass>();
|
||||
}
|
||||
|
||||
if (fake_quantized)
|
||||
passes->registerPass<SubstituteSoftSignPass>();
|
||||
|
||||
// fake quantisation aware passes
|
||||
passes->registerPass<FuseFQIntoWeightsPass>();
|
||||
passes->registerPass<MoveFakeQuantizeLayerIntoQuantParamsPass>();
|
||||
@ -788,7 +793,6 @@ void GNAPlugin::LoadNetwork(CNNNetwork & _network) {
|
||||
passes->registerPass<TransposeWeightsFromNCHWToNHWCPass>();
|
||||
|
||||
passes->registerPass<SubstitutePReluPass>();
|
||||
passes->registerPass<SubstituteSoftSignPass>();
|
||||
|
||||
passes->registerPass<ReorderMaxPoolPass>();
|
||||
passes->registerPass<EltwiseSplitOverChannelsPass>();
|
||||
|
||||
79
inference-engine/src/gna_plugin/ops/softsign.cpp
Normal file
79
inference-engine/src/gna_plugin/ops/softsign.cpp
Normal file
@ -0,0 +1,79 @@
|
||||
// Copyright (C) 2021 Intel Corporation
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
|
||||
#include "softsign.hpp"
|
||||
|
||||
#include <ngraph/validation_util.hpp>
|
||||
|
||||
#include "ngraph/attribute_visitor.hpp"
|
||||
#include "ngraph/runtime/host_tensor.hpp"
|
||||
|
||||
#include <cmath>
|
||||
#include <cstddef>
|
||||
|
||||
NGRAPH_RTTI_DEFINITION(GNAPluginNS::SoftSign, "SoftSign", 0);
|
||||
|
||||
namespace GNAPluginNS {
|
||||
|
||||
template <typename T>
|
||||
void softsign(const T* arg, T* out, size_t count) {
|
||||
for (size_t i = 0; i < count; i++) {
|
||||
out[i] = 1 / (1 + std::abs(arg[i]));
|
||||
}
|
||||
}
|
||||
|
||||
SoftSign::SoftSign(const ngraph::Output<ngraph::Node>& arg) : ov::op::util::UnaryElementwiseArithmetic(arg) {
|
||||
constructor_validate_and_infer_types();
|
||||
}
|
||||
|
||||
std::shared_ptr<ngraph::Node> SoftSign::clone_with_new_inputs(const ngraph::OutputVector& new_args) const {
|
||||
check_new_args_count(this, new_args);
|
||||
return std::make_shared<SoftSign>(new_args.at(0));
|
||||
}
|
||||
|
||||
template <ngraph::element::Type_t ET>
|
||||
inline bool evaluate(const ov::runtime::Tensor& arg, ov::runtime::Tensor& out, const size_t count) {
|
||||
using T = typename ngraph::element_type_traits<ET>::value_type;
|
||||
softsign<T>(arg.data<T>(), out.data<T>(), count);
|
||||
return true;
|
||||
}
|
||||
|
||||
namespace {
|
||||
bool evaluate_softsign(const ov::runtime::Tensor& arg, ov::runtime::Tensor& out) {
|
||||
bool rc = true;
|
||||
size_t count = shape_size(arg.get_shape());
|
||||
|
||||
switch (arg.get_element_type()) {
|
||||
case ov::element::Type_t::f16:
|
||||
rc = evaluate<ov::element::Type_t::f16>(arg, out, count);
|
||||
break;
|
||||
case ov::element::Type_t::f32:
|
||||
rc = evaluate<ov::element::Type_t::f32>(arg, out, count);
|
||||
break;
|
||||
default:
|
||||
rc = false;
|
||||
break;
|
||||
}
|
||||
return rc;
|
||||
}
|
||||
} // namespace
|
||||
|
||||
bool SoftSign::evaluate(ov::runtime::TensorVector& outputs,
|
||||
const ov::runtime::TensorVector& inputs,
|
||||
const ov::EvaluationContext& evaluation_context) const {
|
||||
return evaluate_softsign(inputs[0], outputs[0]);
|
||||
}
|
||||
|
||||
bool SoftSign::has_evaluate() const {
|
||||
switch (get_input_element_type(0)) {
|
||||
case ngraph::element::f16:
|
||||
case ngraph::element::f32:
|
||||
return true;
|
||||
default:
|
||||
break;
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
} // namespace GNAPluginNS
|
||||
30
inference-engine/src/gna_plugin/ops/softsign.hpp
Normal file
30
inference-engine/src/gna_plugin/ops/softsign.hpp
Normal file
@ -0,0 +1,30 @@
|
||||
// Copyright (C) 2021 Intel Corporation
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
|
||||
#pragma once
|
||||
|
||||
#include "openvino/op/op.hpp"
|
||||
#include "ngraph/node.hpp"
|
||||
#include "openvino/op/util/unary_elementwise_arithmetic.hpp"
|
||||
|
||||
namespace GNAPluginNS {
|
||||
/// \brief Neural Activation Function
|
||||
/// f(x) = x/(1.0 + |x|)
|
||||
///
|
||||
class SoftSign : public ov::op::util::UnaryElementwiseArithmetic {
|
||||
public:
|
||||
NGRAPH_RTTI_DECLARATION;
|
||||
|
||||
SoftSign() = default;
|
||||
/// \brief Constructs an SoftSign operation.
|
||||
///
|
||||
/// \param data Input tensor
|
||||
SoftSign(const ngraph::Output<ngraph::Node>& arg);
|
||||
std::shared_ptr<Node> clone_with_new_inputs(const ngraph::OutputVector& new_args) const override;
|
||||
bool evaluate(ov::runtime::TensorVector& output_values,
|
||||
const ov::runtime::TensorVector& input_values,
|
||||
const ov::EvaluationContext & evaluation_context) const override;
|
||||
bool has_evaluate() const override;
|
||||
};
|
||||
} // namespace GNAPluginNS
|
||||
@ -0,0 +1,89 @@
|
||||
// Copyright (C) 2021 Intel Corporation
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
|
||||
#include <openvino/cc/ngraph/itt.hpp>
|
||||
|
||||
#include "transformations/substitute_softsign.hpp"
|
||||
|
||||
#include "transformations/utils/transformation_helper.hpp"
|
||||
#include "transformations/utils/utils.hpp"
|
||||
|
||||
#include <ngraph/opsets/opset8.hpp>
|
||||
#include <ngraph/pattern/op/wrap_type.hpp>
|
||||
#include <ngraph/pattern/op/or.hpp>
|
||||
#include <ngraph/rt_info.hpp>
|
||||
#include <ops/softsign.hpp>
|
||||
|
||||
using namespace GNAPluginNS;
|
||||
|
||||
NGRAPH_RTTI_DEFINITION(SubstituteSoftsign, "SubstituteSoftsign", 0);
|
||||
|
||||
using Node = std::shared_ptr<ngraph::Node>;
|
||||
|
||||
namespace {
|
||||
|
||||
void DoTransformation(Node start_node, Node last_node) {
|
||||
auto activation = std::make_shared<SoftSign>(start_node);
|
||||
activation->set_friendly_name(last_node->get_friendly_name());
|
||||
ngraph::copy_runtime_info(last_node, activation);
|
||||
ngraph::replace_node(last_node, activation);
|
||||
}
|
||||
|
||||
class IsConstValueAcceptable {
|
||||
public:
|
||||
IsConstValueAcceptable(double expected_value) :
|
||||
m_expected_value(expected_value) {}
|
||||
|
||||
bool operator()(const ngraph::Output<ngraph::Node>& output) const {
|
||||
auto node = std::dynamic_pointer_cast<ngraph::opset8::Constant>(output.get_node_shared_ptr());
|
||||
if (!node)
|
||||
return false;
|
||||
|
||||
float value;
|
||||
if (!ngraph::op::util::get_single_value(node, value)) {
|
||||
return false;
|
||||
}
|
||||
|
||||
return (value == m_expected_value);
|
||||
}
|
||||
|
||||
private:
|
||||
const double m_expected_value;
|
||||
};
|
||||
|
||||
} // namespace
|
||||
|
||||
SubstituteSoftsign::SubstituteSoftsign() {
|
||||
MATCHER_SCOPE(SubstituteSoftsign);
|
||||
|
||||
auto root = ngraph::pattern::any_input();
|
||||
auto abs = ngraph::pattern::wrap_type<ngraph::opset8::Abs>({root});
|
||||
|
||||
auto add_const = ngraph::pattern::wrap_type<ngraph::opset8::Constant>(IsConstValueAcceptable(1.0));
|
||||
auto add = ngraph::pattern::wrap_type<ngraph::opset8::Add>({abs, add_const});
|
||||
|
||||
auto power_const = ngraph::pattern::wrap_type<ngraph::opset8::Constant>(IsConstValueAcceptable(-1.0));
|
||||
auto power = ngraph::pattern::wrap_type<ngraph::opset8::Power>({add, power_const});
|
||||
|
||||
auto multiply = ngraph::pattern::wrap_type<ngraph::opset8::Multiply>({root, power});
|
||||
auto divide = ngraph::pattern::wrap_type<ngraph::opset8::Divide>({root, add});
|
||||
auto last = std::make_shared<ngraph::pattern::op::Or>(ngraph::OutputVector{multiply, divide});
|
||||
|
||||
ngraph::matcher_pass_callback callback = [=](ngraph::pattern::Matcher& m) {
|
||||
const auto& pattern_map = m.get_pattern_value_map();
|
||||
auto root_node = pattern_map.at(root).get_node_shared_ptr();
|
||||
|
||||
auto last_node_it = pattern_map.find(multiply);
|
||||
if (last_node_it == pattern_map.end())
|
||||
last_node_it = pattern_map.find(divide);
|
||||
auto last_node = last_node_it->second.get_node_shared_ptr();
|
||||
|
||||
DoTransformation(root_node, last_node);
|
||||
|
||||
return true;
|
||||
};
|
||||
|
||||
auto m = std::make_shared<ngraph::pattern::Matcher>(last, matcher_name);
|
||||
this->register_matcher(m, callback);
|
||||
}
|
||||
@ -0,0 +1,45 @@
|
||||
// Copyright (C) 2021 Intel Corporation
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <ngraph/pass/graph_rewrite.hpp>
|
||||
|
||||
namespace GNAPluginNS {
|
||||
|
||||
/**
|
||||
* @brief Current version of ModelOptimizer substitutes SoftSign activation
|
||||
* function with next subgraph
|
||||
* a layer
|
||||
* | \
|
||||
* abs \
|
||||
* | |
|
||||
* add |
|
||||
* | |
|
||||
* power |
|
||||
* \ /
|
||||
* Divide
|
||||
*
|
||||
* See model-optimizer/extensions/front/softsign_replacer.py
|
||||
*
|
||||
* The ConvertDivide transformation from CommonOptimizations
|
||||
* substitutes Divide with {-1} and add constant {1}
|
||||
* - GNA supports Power [0, 2.8]
|
||||
* - Add, Power, Divide layers are more perfomance expensive in GNA
|
||||
* than SoftSign PWL
|
||||
*
|
||||
* Legacy SubstituteSoftSignPass supports irv7 model where SoftSign subgraph
|
||||
* could have been without add layer. Current ModelOptimezer always generates
|
||||
* SoftSign subgraph with that layer.
|
||||
*
|
||||
* SubstituteSoftsign transformation does backward substitution to SoftSign.
|
||||
* TODO: remove that pass as soon as ModelOptimizer will not substitute SoftSign activation
|
||||
*/
|
||||
class SubstituteSoftsign : public ngraph::pass::MatcherPass {
|
||||
public:
|
||||
NGRAPH_RTTI_DECLARATION;
|
||||
SubstituteSoftsign();
|
||||
};
|
||||
|
||||
} // namespace GNAPluginNS
|
||||
@ -13,6 +13,7 @@ addIeTargetTest(
|
||||
gmock
|
||||
commonTestUtils_s
|
||||
GNAPlugin_test_static
|
||||
engines_test_util
|
||||
ADD_CPPLINT
|
||||
LABELS
|
||||
GNA
|
||||
|
||||
40
inference-engine/tests/unit/gna/ngraph/op_eval/softsign.cpp
Normal file
40
inference-engine/tests/unit/gna/ngraph/op_eval/softsign.cpp
Normal file
@ -0,0 +1,40 @@
|
||||
// Copyright (C) 2021 Intel Corporation
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
|
||||
#include "ops/softsign.hpp"
|
||||
|
||||
#include <string>
|
||||
#include <vector>
|
||||
|
||||
#include "execute_tools.hpp"
|
||||
#include "gtest/gtest.h"
|
||||
#include "ngraph/runtime/host_tensor.hpp"
|
||||
#include "ngraph/validation_util.hpp"
|
||||
#include "ngraph/opsets/opset8.hpp"
|
||||
|
||||
using namespace GNAPluginNS;
|
||||
|
||||
TEST(op_eval, softsign) {
|
||||
auto p = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32, ngraph::Shape{4});
|
||||
auto softsign = std::make_shared<SoftSign>(p);
|
||||
auto fun = std::make_shared<ngraph::Function>(ngraph::OutputVector{softsign}, ngraph::ParameterVector{p});
|
||||
|
||||
float inputs[] = {-1.0, 0.0, 1.0, 20.0};
|
||||
std::vector<float> expected_result{0.5, 1.0, 0.5, 0.047619};
|
||||
|
||||
ov::runtime::TensorVector result(1);
|
||||
ov::runtime::Tensor input{ov::element::f32, ov::Shape{4}, inputs};
|
||||
|
||||
ASSERT_TRUE(fun->evaluate(result, ov::runtime::TensorVector{input}));
|
||||
|
||||
EXPECT_EQ(result.size(), 1);
|
||||
EXPECT_EQ(result[0].get_element_type(), ngraph::element::f32);
|
||||
EXPECT_EQ(result[0].get_shape(), ngraph::Shape{4});
|
||||
EXPECT_EQ(result[0].get_size(), 4);
|
||||
|
||||
const float * result_data = result[0].data<float>();
|
||||
for (size_t i = 0; i < result[0].get_size(); ++i)
|
||||
EXPECT_NEAR(result_data[i], expected_result[i], 0.000001);
|
||||
}
|
||||
|
||||
@ -0,0 +1,167 @@
|
||||
// Copyright (C) 2021 Intel Corporation
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
|
||||
#include <gtest/gtest.h>
|
||||
|
||||
#include "transformations/substitute_softsign.hpp"
|
||||
|
||||
#include "common_test_utils/ngraph_test_utils.hpp"
|
||||
#include <ngraph/function.hpp>
|
||||
#include <ngraph/opsets/opset8.hpp>
|
||||
#include <ngraph/pass/manager.hpp>
|
||||
#include <transformations/init_node_info.hpp>
|
||||
#include <ops/softsign.hpp>
|
||||
|
||||
namespace testing {
|
||||
|
||||
namespace {
|
||||
|
||||
std::shared_ptr<ngraph::Function> createSoftSignFunction() {
|
||||
auto input_params = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32,
|
||||
ngraph::Shape{ 1, 1, 1, 64 });
|
||||
|
||||
auto softsign = std::make_shared<GNAPluginNS::SoftSign>(input_params);
|
||||
|
||||
ngraph::ResultVector results{ std::make_shared<ngraph::op::Result>(softsign) };
|
||||
|
||||
return std::make_shared<ngraph::Function>(ngraph::ResultVector{results},
|
||||
ngraph::ParameterVector{input_params});
|
||||
}
|
||||
|
||||
} // namespace
|
||||
|
||||
TEST(TransformationTests, SubstituteSoftSignMulPower) {
|
||||
std::shared_ptr<ngraph::Function> func(nullptr), reference_func(nullptr);
|
||||
|
||||
{
|
||||
auto input_params = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32,
|
||||
ngraph::Shape{ 1, 1, 1, 64 });
|
||||
|
||||
auto abs = std::make_shared<ngraph::op::Abs>(input_params);
|
||||
|
||||
auto const_1 = ngraph::opset8::Constant::create(ngraph::element::f32, ngraph::Shape{}, {1});
|
||||
auto const_neg_1 = ngraph::opset8::Constant::create(ngraph::element::f32, ngraph::Shape{}, {-1});
|
||||
|
||||
auto add = std::make_shared<ngraph::opset8::Add>(abs, const_1);
|
||||
auto power = std::make_shared<ngraph::opset8::Power>(add, const_neg_1);
|
||||
|
||||
auto mul = std::make_shared<ngraph::opset8::Multiply>(power, input_params);
|
||||
ngraph::ResultVector results{ std::make_shared<ngraph::op::Result>(mul) };
|
||||
|
||||
func = std::make_shared<ngraph::Function>(ngraph::ResultVector{results},
|
||||
ngraph::ParameterVector{input_params});
|
||||
ngraph::pass::Manager m;
|
||||
m.register_pass<ngraph::pass::InitNodeInfo>();
|
||||
m.register_pass<GNAPluginNS::SubstituteSoftsign>();
|
||||
m.run_passes(func);
|
||||
ASSERT_NO_THROW(check_rt_info(func));
|
||||
}
|
||||
|
||||
reference_func = createSoftSignFunction();
|
||||
|
||||
const FunctionsComparator func_comparator = FunctionsComparator::with_default().enable(FunctionsComparator::ATTRIBUTES);
|
||||
const FunctionsComparator::Result result = func_comparator(func, reference_func);
|
||||
ASSERT_TRUE(result.valid);
|
||||
}
|
||||
|
||||
TEST(TransformationTests, SubstituteSoftSignDivide) {
|
||||
std::shared_ptr<ngraph::Function> func(nullptr), reference_func(nullptr);
|
||||
|
||||
{
|
||||
auto input_params = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32,
|
||||
ngraph::Shape{ 1, 1, 1, 64 });
|
||||
|
||||
auto abs = std::make_shared<ngraph::opset8::Abs>(input_params);
|
||||
|
||||
auto const_1 = ngraph::opset8::Constant::create(ngraph::element::f32, ngraph::Shape{}, {1});
|
||||
auto add = std::make_shared<ngraph::opset8::Add>(abs, const_1);
|
||||
|
||||
auto divide = std::make_shared<ngraph::opset8::Divide>(input_params, add);
|
||||
ngraph::ResultVector results{ std::make_shared<ngraph::opset8::Result>(divide) };
|
||||
|
||||
func = std::make_shared<ngraph::Function>(ngraph::ResultVector{results},
|
||||
ngraph::ParameterVector{input_params});
|
||||
ngraph::pass::Manager m;
|
||||
m.register_pass<ngraph::pass::InitNodeInfo>();
|
||||
m.register_pass<GNAPluginNS::SubstituteSoftsign>();
|
||||
m.run_passes(func);
|
||||
ASSERT_NO_THROW(check_rt_info(func));
|
||||
}
|
||||
|
||||
reference_func = createSoftSignFunction();
|
||||
|
||||
const FunctionsComparator func_comparator = FunctionsComparator::with_default().enable(FunctionsComparator::ATTRIBUTES);
|
||||
const FunctionsComparator::Result result = func_comparator(func, reference_func);
|
||||
ASSERT_TRUE(result.valid);
|
||||
}
|
||||
|
||||
TEST(TransformationTests, SubstituteSoftSignMulPowerInvalidAddConst) {
|
||||
std::shared_ptr<ngraph::Function> func(nullptr), reference_func(nullptr);
|
||||
|
||||
{
|
||||
auto input_params = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32,
|
||||
ngraph::Shape{ 1, 1, 1, 64 });
|
||||
|
||||
auto abs = std::make_shared<ngraph::op::Abs>(input_params);
|
||||
|
||||
auto const_1 = ngraph::opset8::Constant::create(ngraph::element::f32, ngraph::Shape{}, {1.1});
|
||||
auto const_neg_1 = ngraph::opset8::Constant::create(ngraph::element::f32, ngraph::Shape{}, {-1});
|
||||
|
||||
auto add = std::make_shared<ngraph::opset8::Add>(abs, const_1);
|
||||
auto power = std::make_shared<ngraph::opset8::Power>(add, const_neg_1);
|
||||
|
||||
auto mul = std::make_shared<ngraph::opset8::Multiply>(power, input_params);
|
||||
ngraph::ResultVector results{ std::make_shared<ngraph::op::Result>(mul) };
|
||||
|
||||
func = std::make_shared<ngraph::Function>(ngraph::ResultVector{results},
|
||||
ngraph::ParameterVector{input_params});
|
||||
ngraph::pass::Manager m;
|
||||
m.register_pass<ngraph::pass::InitNodeInfo>();
|
||||
m.register_pass<GNAPluginNS::SubstituteSoftsign>();
|
||||
m.run_passes(func);
|
||||
ASSERT_NO_THROW(check_rt_info(func));
|
||||
}
|
||||
|
||||
reference_func = ngraph::clone_function(*func);
|
||||
|
||||
const FunctionsComparator func_comparator = FunctionsComparator::with_default().enable(FunctionsComparator::ATTRIBUTES);
|
||||
const FunctionsComparator::Result result = func_comparator(func, reference_func);
|
||||
ASSERT_TRUE(result.valid);
|
||||
}
|
||||
|
||||
TEST(TransformationTests, SubstituteSoftSignMulPowerInvalidPowerConst) {
|
||||
std::shared_ptr<ngraph::Function> func(nullptr), reference_func(nullptr);
|
||||
|
||||
{
|
||||
auto input_params = std::make_shared<ngraph::opset8::Parameter>(ngraph::element::f32,
|
||||
ngraph::Shape{ 1, 1, 1, 64 });
|
||||
|
||||
auto abs = std::make_shared<ngraph::op::Abs>(input_params);
|
||||
|
||||
auto const_1 = ngraph::opset8::Constant::create(ngraph::element::f32, ngraph::Shape{}, {1});
|
||||
auto const_neg_1 = ngraph::opset8::Constant::create(ngraph::element::f32, ngraph::Shape{}, {-1.1});
|
||||
|
||||
auto add = std::make_shared<ngraph::opset8::Add>(abs, const_1);
|
||||
auto power = std::make_shared<ngraph::opset8::Power>(add, const_neg_1);
|
||||
|
||||
auto mul = std::make_shared<ngraph::opset8::Multiply>(power, input_params);
|
||||
ngraph::ResultVector results{ std::make_shared<ngraph::op::Result>(mul) };
|
||||
|
||||
func = std::make_shared<ngraph::Function>(ngraph::ResultVector{results},
|
||||
ngraph::ParameterVector{input_params});
|
||||
ngraph::pass::Manager m;
|
||||
m.register_pass<ngraph::pass::InitNodeInfo>();
|
||||
m.register_pass<GNAPluginNS::SubstituteSoftsign>();
|
||||
m.run_passes(func);
|
||||
ASSERT_NO_THROW(check_rt_info(func));
|
||||
}
|
||||
|
||||
reference_func = ngraph::clone_function(*func);
|
||||
|
||||
const FunctionsComparator func_comparator = FunctionsComparator::with_default().enable(FunctionsComparator::ATTRIBUTES);
|
||||
const FunctionsComparator::Result result = func_comparator(func, reference_func);
|
||||
ASSERT_TRUE(result.valid);
|
||||
}
|
||||
|
||||
} // namespace testing
|
||||
@ -218,12 +218,6 @@ TEST_F(I16QuantisationTest, canDetectLeakyRelu) {
|
||||
.gna().propagate_forward().called_with().pwl_inserted_into_nnet();
|
||||
}
|
||||
|
||||
TEST_F(I16QuantisationTest, canDetectSoftWSignSubgraph) {
|
||||
assert_that().onInferModel(TFSoftsignUnfoldedModel())
|
||||
.inNotCompactMode().withGNAConfig(GNA_CONFIG_KEY(SCALE_FACTOR), 1.0f)
|
||||
.gna().propagate_forward().called_with().pwls_inserted_into_nnet({kActSigmoid});
|
||||
}
|
||||
|
||||
TEST_F(I16QuantisationTest, MaxPool_followedAfterActivation) {
|
||||
assert_that().onInferModel(maxpoolAfterRelu())
|
||||
.inNotCompactMode().withGNAConfig(GNA_CONFIG_KEY(SCALE_FACTOR), 1.0f)
|
||||
|
||||
@ -1,97 +0,0 @@
|
||||
// Copyright (C) 2018-2021 Intel Corporation
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
//
|
||||
|
||||
#include <vector>
|
||||
#include <gtest/gtest.h>
|
||||
#include <single_layer_common.hpp>
|
||||
#include <ngraph/op/parameter.hpp>
|
||||
#include <ngraph/ops.hpp>
|
||||
#include <ie_precision.hpp>
|
||||
#include <legacy/ngraph_ops/power.hpp>
|
||||
#include <debug.h>
|
||||
#include "../gna_matcher.hpp"
|
||||
|
||||
typedef struct {
|
||||
std::string activationType;
|
||||
size_t input_shape;
|
||||
std::pair<float, float> range;
|
||||
} ActivationCaseParam;
|
||||
|
||||
using ActivationCaseParam2 = std::tuple<InferenceEngine::Precision, ActivationCaseParam>;
|
||||
|
||||
class GNAActivationTest : public GNATest<>,
|
||||
public testing::WithParamInterface<ActivationCaseParam2> {
|
||||
public:
|
||||
|
||||
static std::string getTestName(const testing::TestParamInfo<ActivationCaseParam2>& params) {
|
||||
std::string test_name = std::string(std::get<0>(params.param).name()) + "_";
|
||||
test_name += std::get<1>(params.param).activationType + "_";
|
||||
test_name += std::to_string(std::get<1>(params.param).input_shape) + "_";
|
||||
test_name += std::to_string(std::get<1>(params.param).range.first) + "_";
|
||||
test_name += std::to_string(std::get<1>(params.param).range.second);
|
||||
return test_name;
|
||||
}
|
||||
|
||||
std::shared_ptr<ngraph::Function> buildNgraphFunction(const ActivationCaseParam& param) {
|
||||
|
||||
auto shape = ngraph::Shape{1, param.input_shape};
|
||||
auto inputN = std::make_shared<ngraph::op::Parameter>(ngraph::element::f32, shape);
|
||||
|
||||
auto absN = std::make_shared<ngraph::op::v0::Abs>(inputN);
|
||||
|
||||
auto powerN = std::make_shared<ngraph::op::PowerIE>(absN, -1, 1, 1.0);
|
||||
|
||||
auto eltwiseN = std::make_shared<ngraph::op::v1::Multiply>(powerN, inputN);
|
||||
|
||||
auto function = std::make_shared<ngraph::Function>(ngraph::NodeVector{eltwiseN}, ngraph::ParameterVector{inputN});
|
||||
return function;
|
||||
}
|
||||
};
|
||||
|
||||
TEST_P(GNAActivationTest, ActivationTest) {
|
||||
const auto precision = std::get<0>(GetParam());
|
||||
const auto param = std::get<1>(GetParam());
|
||||
|
||||
if (precision == InferenceEngine::Precision::FP32) {
|
||||
auto input_data = generate_random_1d<float>(param.input_shape, param.range.first, param.range.second);
|
||||
std::vector<float> expected_result(param.input_shape);
|
||||
|
||||
|
||||
for (std::size_t i = 0; i < expected_result.size(); i++) {
|
||||
auto & x = input_data[i];
|
||||
if (param.activationType == "softsign") {
|
||||
expected_result[i] = x / (1 + fabs(x));
|
||||
} else {
|
||||
FAIL() << "Unsupported activation type: " << param.activationType;
|
||||
}
|
||||
}
|
||||
|
||||
assert_that().onInferNgraphModel(buildNgraphFunction(param))
|
||||
.inNotCompactMode()
|
||||
.gna()
|
||||
.propagate_forward()
|
||||
.onCPU()
|
||||
.called_with_input(input_data)
|
||||
.equals_to(expected_result);
|
||||
} else {
|
||||
assert_that().onInferNgraphModel(buildNgraphFunction(param))
|
||||
.inNotCompactMode()
|
||||
.gna()
|
||||
.withGNAConfig(GNA_CONFIG_KEY(SCALE_FACTOR), 1.0f)
|
||||
.withGNAConfig(GNA_CONFIG_KEY(PRECISION), precision.name())
|
||||
.propagate_forward()
|
||||
.called_with().pwls_inserted_into_nnet({kActSigmoid});
|
||||
}
|
||||
}
|
||||
|
||||
static const ActivationCaseParam gna_activation_test_params[] = {
|
||||
{"softsign", 200, {-10, 10}},
|
||||
};
|
||||
|
||||
INSTANTIATE_TEST_SUITE_P(
|
||||
GNALayerTests, GNAActivationTest,
|
||||
::testing::Combine(
|
||||
::testing::Values(InferenceEngine::Precision::FP32, InferenceEngine::Precision::I16, InferenceEngine::Precision::I8),
|
||||
::testing::ValuesIn(gna_activation_test_params)),
|
||||
GNAActivationTest::getTestName);
|
||||
@ -2164,146 +2164,6 @@ std::string TFLeakyReluModel() {
|
||||
)V0G0N";
|
||||
}
|
||||
|
||||
std::string TFSoftsignUnfoldedModel() {
|
||||
return R"V0G0N(
|
||||
<?xml version="1.0" ?>
|
||||
<net name="LSTM_statics_1000_1frame_test_unpack" version="7">
|
||||
<layers>
|
||||
<layer id="0" name="input_batch" type="Input">
|
||||
<output>
|
||||
<port id="0" precision="FP32">
|
||||
<dim>1</dim>
|
||||
<dim>64</dim>
|
||||
</port>
|
||||
</output>
|
||||
</layer>
|
||||
<layer id="42" name="FC_layer0/packed/ExpandDims_/Dims/Output_0/Data__const" type="Const">
|
||||
<output>
|
||||
<port id="1" precision="I32">
|
||||
<dim>1</dim>
|
||||
</port>
|
||||
</output>
|
||||
<blobs>
|
||||
<custom offset="0" precision="I32" size="4"/>
|
||||
</blobs>
|
||||
</layer>
|
||||
<layer id="43" name="FC_layer0/packed/ExpandDims_131" type="Unsqueeze">
|
||||
<input>
|
||||
<port id="0">
|
||||
<dim>1</dim>
|
||||
<dim>64</dim>
|
||||
</port>
|
||||
<port id="1">
|
||||
<dim>1</dim>
|
||||
</port>
|
||||
</input>
|
||||
<output>
|
||||
<port id="2" precision="FP32">
|
||||
<dim>1</dim>
|
||||
<dim>1</dim>
|
||||
<dim>64</dim>
|
||||
</port>
|
||||
</output>
|
||||
</layer>
|
||||
<layer id="44" name="abs_FC_layer0/Softsign" type="Abs">
|
||||
<input>
|
||||
<port id="0">
|
||||
<dim>1</dim>
|
||||
<dim>1</dim>
|
||||
<dim>64</dim>
|
||||
</port>
|
||||
</input>
|
||||
<output>
|
||||
<port id="1" precision="FP32">
|
||||
<dim>1</dim>
|
||||
<dim>1</dim>
|
||||
<dim>64</dim>
|
||||
</port>
|
||||
</output>
|
||||
</layer>
|
||||
<layer id="45" name="FC_layer0/Softsign_plus_1/fused_power" type="Power">
|
||||
<data power="-1.0" scale="1" shift="1.0"/>
|
||||
<input>
|
||||
<port id="0">
|
||||
<dim>1</dim>
|
||||
<dim>1</dim>
|
||||
<dim>64</dim>
|
||||
</port>
|
||||
</input>
|
||||
<output>
|
||||
<port id="1" precision="FP32">
|
||||
<dim>1</dim>
|
||||
<dim>1</dim>
|
||||
<dim>64</dim>
|
||||
</port>
|
||||
</output>
|
||||
</layer>
|
||||
<layer id="46" name="div_FC_layer0/Softsign/mul_" type="Eltwise">
|
||||
<data operation="mul"/>
|
||||
<input>
|
||||
<port id="0">
|
||||
<dim>1</dim>
|
||||
<dim>1</dim>
|
||||
<dim>64</dim>
|
||||
</port>
|
||||
<port id="1">
|
||||
<dim>1</dim>
|
||||
<dim>1</dim>
|
||||
<dim>64</dim>
|
||||
</port>
|
||||
</input>
|
||||
<output>
|
||||
<port id="2" precision="FP32">
|
||||
<dim>1</dim>
|
||||
<dim>1</dim>
|
||||
<dim>64</dim>
|
||||
</port>
|
||||
</output>
|
||||
</layer>
|
||||
<layer id="47" name="unstack_6/Squeeze_/value/Output_0/Data__const" type="Const">
|
||||
<output>
|
||||
<port id="1" precision="I32">
|
||||
<dim>1</dim>
|
||||
</port>
|
||||
</output>
|
||||
<blobs>
|
||||
<custom offset="4" precision="I32" size="4"/>
|
||||
</blobs>
|
||||
</layer>
|
||||
<layer id="48" name="unstack_6/Squeeze_" type="Squeeze">
|
||||
<input>
|
||||
<port id="0">
|
||||
<dim>1</dim>
|
||||
<dim>1</dim>
|
||||
<dim>64</dim>
|
||||
</port>
|
||||
<port id="1">
|
||||
<dim>1</dim>
|
||||
</port>
|
||||
</input>
|
||||
<output>
|
||||
<port id="2" precision="FP32">
|
||||
<dim>1</dim>
|
||||
<dim>64</dim>
|
||||
</port>
|
||||
</output>
|
||||
</layer>
|
||||
</layers>
|
||||
<edges>
|
||||
<edge from-layer="0" from-port="0" to-layer="43" to-port="0"/>
|
||||
<edge from-layer="42" from-port="1" to-layer="43" to-port="1"/>
|
||||
<edge from-layer="43" from-port="2" to-layer="44" to-port="0"/>
|
||||
<edge from-layer="44" from-port="1" to-layer="45" to-port="0"/>
|
||||
<edge from-layer="45" from-port="1" to-layer="46" to-port="0"/>
|
||||
<edge from-layer="43" from-port="2" to-layer="46" to-port="1"/>
|
||||
<edge from-layer="46" from-port="2" to-layer="48" to-port="0"/>
|
||||
<edge from-layer="47" from-port="1" to-layer="48" to-port="1"/>
|
||||
</edges>
|
||||
</net>
|
||||
|
||||
)V0G0N";
|
||||
}
|
||||
|
||||
std::string maxpoolAfterRelu() {
|
||||
return R"V0G0N(
|
||||
<?xml version="1.0" ?>
|
||||
|
||||
@ -39,7 +39,6 @@ std::string ClampActivationModel();
|
||||
std::string IdentityActivationModel();
|
||||
std::string maxpoolAfterRelu();
|
||||
std::string TFLeakyReluModel();
|
||||
std::string TFSoftsignUnfoldedModel();
|
||||
std::string cropWithoutOffsetModel();
|
||||
std::string cropWithAlignedOffsetModel();
|
||||
std::string cropWithOffsetModel();
|
||||
|
||||
Loading…
Reference in New Issue
Block a user