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/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
*
* 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 "luci/CircleOptimizer.h"
#include "luci/Pass/FuseBCQPass.h"
#include "luci/Pass/FuseInstanceNormPass.h"
#include "luci/Pass/ResolveCustomOpAddPass.h"
#include "luci/Pass/ResolveCustomOpBatchMatMulPass.h"
#include "luci/Pass/ResolveCustomOpMatMulPass.h"
#include "luci/Pass/QuantizeWithMinMaxPass.h"
#include "luci/Pass/QuantizeDequantizeWeightsPass.h"
// TODO add more passes
#include "luci/Pass/ShapeInferencePass.h"
#include "luci/Pass/TypeInferencePass.h"
// logo passes
#include <logo/RemoveDeadNodeWithQueryPass.h>
#include "ProgressReporter.h"
#include "CircleOptimizerUtils.h"
#include <logo/Phase.h>
#include <memory>
namespace
{
using namespace luci;
class OptimizeOptionsImpl final : public luci::CircleOptimizer::Options
{
public:
void enable(Algorithm) final;
void param(AlgorithmParameters, const std::string &) final;
const std::string param(AlgorithmParameters) const final;
bool query(Algorithm) final;
private:
std::vector<Algorithm> _algorithms;
std::map<AlgorithmParameters, const std::string> _algorithm_params;
};
void OptimizeOptionsImpl::enable(Algorithm algo) { _algorithms.push_back(algo); }
void OptimizeOptionsImpl::param(AlgorithmParameters param, const std::string &str)
{
_algorithm_params.insert(std::pair<AlgorithmParameters, const std::string>(param, str));
}
const std::string OptimizeOptionsImpl::param(AlgorithmParameters param) const
{
auto param_str = _algorithm_params.find(param);
if (param_str != _algorithm_params.end())
{
return param_str->second;
}
else
{
return std::string();
}
}
bool OptimizeOptionsImpl::query(Algorithm algo)
{
std::vector<Algorithm>::iterator it = std::find(_algorithms.begin(), _algorithms.end(), algo);
if (it == _algorithms.end())
return false;
return true;
}
} // namespace
namespace luci
{
CircleOptimizer::Options *CircleOptimizer::options(void)
{
if (_options == nullptr)
{
_options = std::make_unique<OptimizeOptionsImpl>();
}
return _options.get();
}
void CircleOptimizer::optimize(loco::Graph *g) const
{
logo::Phase phase;
/* TRANSFORM DECLARATION BEGIN */
if (_options->query(Options::Algorithm::ResolveCustomOpAdd))
{
phase.emplace_back(std::make_unique<luci::ResolveCustomOpAddPass>());
}
if (_options->query(Options::Algorithm::ResolveCustomOpBatchMatMul))
{
phase.emplace_back(std::make_unique<luci::ResolveCustomOpBatchMatMulPass>());
}
if (_options->query(Options::Algorithm::ResolveCustomOpMatMul))
{
phase.emplace_back(std::make_unique<luci::ResolveCustomOpMatMulPass>());
}
if (_options->query(Options::Algorithm::FuseInstanceNorm))
{
phase.emplace_back(std::make_unique<FuseInstanceNormPass>());
}
if (_options->query(Options::Algorithm::FuseBCQ))
{
phase.emplace_back(std::make_unique<FuseBCQPass>());
}
// Shape inference is needed for added nodes doing above transformations
phase.emplace_back(std::make_unique<luci::ShapeInferencePass>());
phase.emplace_back(std::make_unique<luci::TypeInferencePass>());
phase.emplace_back(std::make_unique<logo::RemoveDeadNodeWithQueryPass>());
/* TRANSFORM DECLARATION END */
ProgressReporter prog(g, logo::PhaseStrategy::Saturate);
logo::PhaseRunner<logo::PhaseStrategy::Saturate> phase_runner{g};
phase_runner.attach(&prog);
phase_runner.run(phase);
}
void CircleOptimizer::quantize(loco::Graph *g) const
{
// Fake quantization of weights
if (_options->query(Options::Algorithm::QuantizeDequantizeWeights))
{
static const std::vector<std::string> fakeq_supported_input_dtype{"float32"};
static const std::vector<std::string> fakeq_supported_output_dtype{"uint8"};
static const std::vector<std::string> fakeq_supported_granularity{"layer"};
auto input_dtype = _options->param(Options::AlgorithmParameters::Quantize_input_dtype);
auto output_dtype = _options->param(Options::AlgorithmParameters::Quantize_output_dtype);
auto granularity = _options->param(Options::AlgorithmParameters::Quantize_granularity);
if (!in_array(to_lower_case(input_dtype), fakeq_supported_input_dtype))
throw std::runtime_error("Unsupported input type. List of supported input type: " +
to_string(fakeq_supported_input_dtype));
if (!in_array(to_lower_case(output_dtype), fakeq_supported_output_dtype))
throw std::runtime_error("Unsupported output type. List of supported output type: " +
to_string(fakeq_supported_output_dtype));
if (!in_array(to_lower_case(granularity), fakeq_supported_granularity))
throw std::runtime_error("Unsupported granularity. List of supported granularity: " +
to_string(fakeq_supported_granularity));
luci::QuantizeDequantizeWeightsPass fake_quantizer(
str_to_dtype(input_dtype), str_to_dtype(output_dtype), str_to_granularity(granularity));
fake_quantizer.run(g);
}
// Actual quantization of weights, bias, and activation
if (_options->query(Options::Algorithm::QuantizeWithMinMax))
{
static const std::vector<std::string> qwmm_supported_input_dtype{"float32"};
static const std::vector<std::string> qwmm_supported_output_dtype{"uint8"};
static const std::vector<std::string> qwmm_supported_granularity{"layer"};
auto input_dtype = _options->param(Options::AlgorithmParameters::Quantize_input_dtype);
auto output_dtype = _options->param(Options::AlgorithmParameters::Quantize_output_dtype);
auto granularity = _options->param(Options::AlgorithmParameters::Quantize_granularity);
if (!in_array(to_lower_case(input_dtype), qwmm_supported_input_dtype))
throw std::runtime_error("Unsupported input type. List of supported input types: " +
to_string(qwmm_supported_input_dtype));
if (!in_array(to_lower_case(output_dtype), qwmm_supported_output_dtype))
throw std::runtime_error("Unsupported output type. List of supported output types: " +
to_string(qwmm_supported_output_dtype));
if (!in_array(to_lower_case(granularity), qwmm_supported_granularity))
throw std::runtime_error("Unsupported granularity. List of supported granularity: " +
to_string(qwmm_supported_granularity));
luci::QuantizeWithMinMaxPass quantizer(str_to_dtype(input_dtype), str_to_dtype(output_dtype),
str_to_granularity(granularity));
quantizer.run(g);
}
logo::Phase phase;
// Do Shape/Type inference
phase.emplace_back(std::make_unique<luci::ShapeInferencePass>());
phase.emplace_back(std::make_unique<luci::TypeInferencePass>());
ProgressReporter prog(g, logo::PhaseStrategy::Saturate);
logo::PhaseRunner<logo::PhaseStrategy::Saturate> phase_runner{g};
phase_runner.attach(&prog);
phase_runner.run(phase);
}
} // namespace luci
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