diff --git a/paddle/gserver/layers/MKLDNNAddtoLayer.cpp b/paddle/gserver/layers/MKLDNNAddtoLayer.cpp new file mode 100644 index 0000000000000000000000000000000000000000..8eb700723f2cf7dda969739bb5e3d48358d278a0 --- /dev/null +++ b/paddle/gserver/layers/MKLDNNAddtoLayer.cpp @@ -0,0 +1,154 @@ +/* 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 "MKLDNNAddtoLayer.h" + +using namespace mkldnn; // NOLINT + +namespace paddle { + +REGISTER_LAYER(mkldnn_addto, MKLDNNAddtoLayer); + +bool MKLDNNAddtoLayer::init(const LayerMap& layerMap, + const ParameterMap& parameterMap) { + if (!MKLDNNLayer::init(layerMap, parameterMap)) { + return false; + } + + layerSize_ = getSize(); + for (size_t i = 0; i < inputLayers_.size(); i++) { + CHECK_EQ(layerSize_, inputLayers_[i]->getSize()) << "input size must equal"; + } + if (biasParameter_.get() != NULL) { + biases_ = + std::unique_ptr(new Weight(1, layerSize_, biasParameter_, 0)); + } + return true; +} + +void MKLDNNAddtoLayer::reshape( + int& bs, int& ic, int& ih, int& iw, int oc, int& oh, int& ow) { + CHECK_EQ(layerSize_, getSize()) << "this layer size can not be changed"; + reshapeInput(bs, ih, iw); + ic = inputLayers_[0]->getSize() / ih / iw; + CHECK_EQ((size_t)ic * ih * iw, inputLayers_[0]->getSize()); + CHECK_EQ(inputElemenCnt_, (size_t)bs * ic * ih * iw); + for (size_t i = 0; i < inputLayers_.size(); i++) { + CHECK_EQ(int64_t(bs), inputLayers_[i]->getOutput().getBatchSize()); + CHECK_EQ(layerSize_, inputLayers_[i]->getSize()); + } + + oc = ic; + oh = ih; + ow = iw; + reshapeOutput(oh, ow); + resizeOutput(bs, oc * oh * ow); + printSizeInfo(); +} + +void MKLDNNAddtoLayer::resetFwd(std::vector& pipeline, + MKLDNNMatrixPtr& in, + MKLDNNMatrixPtr& wgt, + MKLDNNMatrixPtr& bias, + MKLDNNMatrixPtr& out) { + if (biases_) { + LOG(FATAL) << "not implemented yet"; + } + resetFwdBuffers(inVals_, out); + in = inVals_[0]; + + std::shared_ptr fwdPD; + resetFwdPD(fwdPD, inVals_, out); + + resetFwdPipeline(pipeline, fwdPD, inVals_, out); +} + +void MKLDNNAddtoLayer::resetBwd(std::vector& pipeline, + MKLDNNMatrixPtr& in, + MKLDNNMatrixPtr& wgt, + MKLDNNMatrixPtr& bias, + MKLDNNMatrixPtr& out) { + resetBwdBuffers(inGrads_, out); + in = inGrads_[0]; + + // backward only need share output grad to input grad + for (size_t i = 0; i < inGrads_.size(); i++) { + if (inGrads_[i] != nullptr) { + inGrads_[i] = out; + inputLayers_[i]->getOutputGrad()->setData(inGrads_[i]->getData()); + } + } +} + +void MKLDNNAddtoLayer::updateWeights(const UpdateCallback& callback) { + if (biases_ && biases_->getWGrad()) { + biases_->getParameterPtr()->incUpdate(callback); + } +} + +void MKLDNNAddtoLayer::resetFwdBuffers(std::vector& inputs, + MKLDNNMatrixPtr& out) { + inputs.resize(inputLayers_.size()); + for (size_t i = 0; i < inputs.size(); i++) { + resetInValue(inputs[i], nullptr, i); + CHECK(inputs[i]); + inputs[i]->downSpatial(); + } + for (size_t i = 1; i < inputs.size(); i++) { + CHECK_PRIMITIVE_DESC_EQ(inputs[i], inputs[0]->getPrimitiveDesc()); + } + + resetOutValue(out, inputs[0]->getPrimitiveDesc()); +} + +void MKLDNNAddtoLayer::resetFwdPD(std::shared_ptr& pd, + std::vector& inputs, + MKLDNNMatrixPtr out) { + std::vector scales(inputs.size(), 1.0); + std::vector srcPDs; + for (size_t i = 0; i < inputs.size(); i++) { + srcPDs.push_back(inputs[i]->getPrimitiveDesc()); + } + CHECK(out); + pd.reset(new sum::primitive_desc(out->getMemoryDesc(), scales, srcPDs)); + CHECK_PRIMITIVE_DESC_EQ(out, pd->dst_primitive_desc()); +} + +void MKLDNNAddtoLayer::resetFwdPipeline( + std::vector& pipeline, + std::shared_ptr& pd, + std::vector& inputs, + MKLDNNMatrixPtr& out) { + std::vector srcs; + for (size_t i = 0; i < inputs.size(); i++) { + srcs.push_back(*(inputs[i])); + } + fwd_.reset(new sum(*pd, srcs, *out)); + pipeline.push_back(*fwd_); +} + +void MKLDNNAddtoLayer::resetBwdBuffers(std::vector& inputs, + MKLDNNMatrixPtr& out) { + CHECK(outVal_); + resetOutGrad(out, outVal_->getPrimitiveDesc()); + CHECK(out); + + inputs.resize(inputLayers_.size()); + for (size_t i = 0; i < inputs.size(); i++) { + resetInGrad(inputs[i], inVal_->getPrimitiveDesc(), i); + CHECK_PRIMITIVE_DESC_EQ(inputs[i], out->getPrimitiveDesc()); + } +} + +} // namespace paddle diff --git a/paddle/gserver/layers/MKLDNNAddtoLayer.h b/paddle/gserver/layers/MKLDNNAddtoLayer.h new file mode 100644 index 0000000000000000000000000000000000000000..15f74ec5bdf3d1e4ae5e09051be6be418590a67a --- /dev/null +++ b/paddle/gserver/layers/MKLDNNAddtoLayer.h @@ -0,0 +1,110 @@ +/* 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 "MKLDNNLayer.h" +#include "mkldnn.hpp" + +namespace paddle { + +/** + * @brief A subclass of MKLDNNLayer Addto layer. + * + * The config file api is mkldnn_addto + */ +class MKLDNNAddtoLayer : public MKLDNNLayer { +protected: + std::vector inVals_; + std::vector inGrads_; + + // layer size == ic * ih * iw == oc * oh *ow, and can not be changed + size_t layerSize_; + + // TODO(TJ): this part has not been optimized by MKL-DNN + std::unique_ptr biases_; + +public: + explicit MKLDNNAddtoLayer(const LayerConfig& config) : MKLDNNLayer(config) {} + + ~MKLDNNAddtoLayer() {} + + bool init(const LayerMap& layerMap, + const ParameterMap& parameterMap) override; + + void reshape( + int& bs, int& ic, int& ih, int& iw, int oc, int& oh, int& ow) override; + + void resetFwd(std::vector& pipeline, + MKLDNNMatrixPtr& in, + MKLDNNMatrixPtr& wgt, + MKLDNNMatrixPtr& bias, + MKLDNNMatrixPtr& out) override; + + void resetBwd(std::vector& pipeline, + MKLDNNMatrixPtr& in, + MKLDNNMatrixPtr& wgt, + MKLDNNMatrixPtr& bias, + MKLDNNMatrixPtr& out) override; + + void updateWeights(const UpdateCallback& callback) override; + + void printValueFormat() override { + for (size_t i = 0; i < inVals_.size(); ++i) { + VLOG(MKLDNN_FMTS) << i << " input: " << inVals_[i]->getFormat() << " >>>"; + } + if (outVal_) { + VLOG(MKLDNN_FMTS) << outVal_->getFormat() << " >>> "; + } + if (extOutVal_) { + VLOG(MKLDNN_FMTS) << extOutVal_->getFormat(); + } + } + + void printGradFormat() override { + if (extOutGrad_) { + VLOG(MKLDNN_FMTS) << extOutGrad_->getFormat(); + } + if (outGrad_) { + VLOG(MKLDNN_FMTS) << outGrad_->getFormat() << " <<< "; + } + for (size_t i = 0; i < inGrads_.size(); ++i) { + VLOG(MKLDNN_FMTS) << i << " input: " << inGrads_[i]->getFormat() << "<<<"; + } + } + +protected: + /** + * Forward functions: reset buffers(inputs, output, bias), + * reset primitive descriptor, + * reset pipeline. + */ + void resetFwdBuffers(std::vector& inputs, + MKLDNNMatrixPtr& out); + void resetFwdPD(std::shared_ptr& pd, + std::vector& inputs, + MKLDNNMatrixPtr out); + void resetFwdPipeline(std::vector& pipeline, + std::shared_ptr& pd, + std::vector& inputs, + MKLDNNMatrixPtr& out); + + /** + * Backward functions: reset buffers(inputs, output, bias) + */ + void resetBwdBuffers(std::vector& inputs, + MKLDNNMatrixPtr& out); +}; + +} // namespace paddle