diff --git a/paddle/gserver/activations/MKLDNNActivation.cpp b/paddle/gserver/activations/MKLDNNActivation.cpp new file mode 100644 index 0000000000000000000000000000000000000000..7fa5a4587c471d5d07b1bf7d8f9b5c6c73e84da8 --- /dev/null +++ b/paddle/gserver/activations/MKLDNNActivation.cpp @@ -0,0 +1,84 @@ +/* Copyright (c) 2017 PaddlePaddle Authors. All Rights Reserve. + +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 "MKLDNNActivation.h" +#include "mkldnn.hpp" +#include "paddle/utils/ClassRegistrar.h" + +namespace paddle { + +static ClassRegistrar gMKLDNNActivationRegistrar; +/** + * @def MKLDNN_ACTIVATION_CLASS_NAME + * @note MKLDNN_ACTIVATION_CLASS_NAME(relu) relu_; + * means mkldnn_reluActivation relu_; + */ +#define MKLDNN_ACTIVATION_CLASS_NAME(ACT_TYPE) mkldnn_##ACT_TYPE##Activation + +/** + * @def DEFINE_MKLDNN_ELTWISE_ACTIVATION + */ +#define DEFINE_MKLDNN_ELTWISE_ACTIVATION(ACT_TYPE, ALPHA) \ + class MKLDNN_ACTIVATION_CLASS_NAME(ACT_TYPE) \ + : public MKLDNNEltwiseActivation { \ + private: \ + static const std::string name; \ + static const float alpha; \ + \ + public: \ + const std::string& getName() const { return name; } \ + float getAlpha() const { return alpha; } \ + }; \ + const std::string MKLDNN_ACTIVATION_CLASS_NAME(ACT_TYPE)::name = \ + "mkldnn_" #ACT_TYPE; \ + const float MKLDNN_ACTIVATION_CLASS_NAME(ACT_TYPE)::alpha = ALPHA; \ + static InitFunction __reg_activation__mkldnn_##ACT_TYPE([] { \ + gMKLDNNActivationRegistrar \ + .registerClass( \ + "mkldnn_" #ACT_TYPE); \ + }); + +/** + * @brief MKLDNN Relu Activation. + * Actually mkldnn_relu is Leaky Relu. + * f(x) = x (x >= 0) + * f(x) = negative_slope * x (x < 0) + * @note the negative_slope should be -0.f + */ +DEFINE_MKLDNN_ELTWISE_ACTIVATION(relu, -0.f) + +/** + * @brief MKLDNN Tanh Activation. + */ +DEFINE_MKLDNN_ELTWISE_ACTIVATION(tanh, 0.f) + +/** + * @brief MKLDNN ELU(Exponential Linear Unit) Activation. + * f(x) = x (x >= 0) + * f(x) = negative_slope * (exp(x) - 1) (x < 0) + */ +DEFINE_MKLDNN_ELTWISE_ACTIVATION(elu, 0.f) + +ActivationFunction* MKLDNNActivation::create(const std::string& type) { + return gMKLDNNActivationRegistrar.createByType(type); +} + +std::vector MKLDNNActivation::getAllRegisteredTypes() { + std::vector types; + gMKLDNNActivationRegistrar.forEachType( + [&](const std::string& type) { types.push_back(type); }); + return types; +} + +} // namespace paddle diff --git a/paddle/gserver/activations/MKLDNNActivation.h b/paddle/gserver/activations/MKLDNNActivation.h new file mode 100644 index 0000000000000000000000000000000000000000..3afab609bec94b03a4d6be445f0dfee09a9ab3f0 --- /dev/null +++ b/paddle/gserver/activations/MKLDNNActivation.h @@ -0,0 +1,144 @@ +/* Copyright (c) 2017 PaddlePaddle Authors. All Rights Reserve. + +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. */ + +#pragma once +#include "ActivationFunction.h" +#include "mkldnn.hpp" +#include "paddle/gserver/layers/MKLDNNBase.h" +#include "paddle/math/MKLDNNMatrix.h" +#include "paddle/parameter/Argument.h" + +namespace paddle { + +/** + * @brief Base class of MKLDNN Activation. + * Common activation function are provieded, + * including mkldnn_relu, mkldnn_elu, mkldnn_tanh, mkldnn_softmax + */ +class MKLDNNActivation : public ActivationFunction { +protected: + // input value element count + size_t cnt_; + // mkldnn matrix, primitive, stream and pipeline + MKLDNNMatrixPtr val_; + MKLDNNMatrixPtr grad_; + std::shared_ptr stream_; + std::shared_ptr fwd_; + std::shared_ptr bwd_; + std::vector pipelineFwd_; + std::vector pipelineBwd_; + +public: + MKLDNNActivation() : cnt_(0) {} + ~MKLDNNActivation() {} + static ActivationFunction* create(const std::string& type); + static std::vector getAllRegisteredTypes(); + virtual const std::string& getName() const = 0; + virtual Error __must_check forward(Argument& act) = 0; + virtual Error __must_check backward(Argument& act) = 0; +}; + +/** + * @brief Base class of MKLDNN Eltwise Activation, + * includes mkldnn_relu, mkldnn_elu and mkldnn_tanh. + */ +class MKLDNNEltwiseActivation : public MKLDNNActivation { + typedef mkldnn::eltwise_forward eltwise_fwd; + typedef mkldnn::eltwise_backward eltwise_bwd; + +public: + MKLDNNEltwiseActivation() {} + + ~MKLDNNEltwiseActivation() {} + + virtual const std::string& getName() const = 0; + virtual float getAlpha() const = 0; + virtual float getBeta() const { return 0.f; } + + /** + * reshape and reset the forward and backward primitives + */ + void resetPrimitives(Argument& act) { + if (cnt_ == act.value->getElementCnt()) { + return; + } + cnt_ = act.value->getElementCnt(); + stream_.reset(new MKLDNNStream()); + auto eng = CPUEngine::Instance().getEngine(); + + // get algo setting + mkldnn::algorithm algo; + if (this->getName() == "mkldnn_relu") { + algo = mkldnn::algorithm::eltwise_relu; + } else if (this->getName() == "mkldnn_tanh") { + algo = mkldnn::algorithm::eltwise_tanh; + } else if (this->getName() == "mkldnn_elu") { + algo = mkldnn::algorithm::eltwise_elu; + } else { + LOG(FATAL) << "Unkown eltwise activation type: " << this->getName(); + } + // note: alpha represents the NegativeSlope when used in relu. + float alpha = getAlpha(); + float beta = getBeta(); + + /// forward + val_ = std::dynamic_pointer_cast(act.value); + if (val_ == nullptr) { + int bs = act.getBatchSize(); + int ih = act.getFrameHeight() > 0 ? act.getFrameHeight() : 1; + int iw = act.getFrameWidth() > 0 ? act.getFrameWidth() : 1; + int ic = cnt_ / bs / ih / iw; + CHECK_EQ(cnt_, (size_t)bs * ic * ih * iw); + val_ = MKLDNNMatrix::create( + act.value, {bs, ic, ih, iw}, mkldnn::memory::format::nchw, eng); + CHECK(val_); + } + auto fwdDesc = eltwise_fwd::desc(mkldnn::prop_kind::forward_training, + algo, + val_->getMemoryDesc(), + alpha, + beta); + auto fwdPD = eltwise_fwd::primitive_desc(fwdDesc, eng); + // inplace buffer, dst = src + fwd_.reset(new eltwise_fwd(fwdPD, *val_, *val_)); + pipelineFwd_.clear(); + pipelineFwd_.push_back(*fwd_); + + /// backward + if (act.grad == nullptr) { + grad_ = nullptr; + return; + } + grad_ = MKLDNNMatrix::create(act.grad, val_->getPrimitiveDesc()); + auto bwdDesc = eltwise_bwd::desc( + algo, grad_->getMemoryDesc(), val_->getMemoryDesc(), alpha, beta); + auto bwdPD = eltwise_bwd::primitive_desc(bwdDesc, eng, fwdPD); + bwd_.reset(new eltwise_bwd(bwdPD, *val_, *grad_, *grad_)); + pipelineBwd_.clear(); + pipelineBwd_.push_back(*bwd_); + } + + Error __must_check forward(Argument& act) { + resetPrimitives(act); + stream_->submit(pipelineFwd_); + return Error(); + } + + Error __must_check backward(Argument& act) { + stream_->submit(pipelineBwd_); + return Error(); + } +}; + +} // namespace paddle