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Caffe data layer to MXIter converter (#3103)
* Caffe data layer to MXIter converter * Fix lint problems * Working with CR changes * Remove trailing white space * Caffe plugin in CMakeLists.txt * CR comments * Code review comments addressed * Add some files to ignore * Revert CMakeLists.txt changes * change epoch_size to num_examples * change epoch_size to num_examples * Fix reorder warning for loc_ * addressing CR comments * ignore lib directory * Update Julia Package doc link (#3134) * get latest parameters when switching bucket * Revert "get latest parameters when switching bucket" This reverts commit 0095008. * fix speech demo build error (#2963) * update Julia package doc URL * fix batch norm (#3049) * removed * Fix lint problem * lint fixes * lint fixes * lint
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| Original file line number | Diff line number | Diff line change |
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| /*! | ||
| * Copyright (c) 2015 by Contributors | ||
| * \file caffe_data_iter.cc | ||
| * \brief register mnist iterator | ||
| */ | ||
| #include <sys/time.h> | ||
| #include <caffe/proto/caffe.pb.h> | ||
| #include <dmlc/parameter.h> | ||
| #include <atomic> | ||
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| #include "caffe_common.h" | ||
| #include "caffe_stream.h" | ||
| #include "caffe_fieldentry.h" | ||
| #include "caffe_blob.h" | ||
| #include "../../src/io/inst_vector.h" | ||
| #include "../../src/io/iter_prefetcher.h" | ||
| #include "../../src/operator/cast-inl.h" | ||
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| #define CHECK_NEXT_TIMING | ||
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| #ifdef CHECK_NEXT_TIMING | ||
| #define IF_CHECK_TIMING(__t$) __t$ | ||
| #else | ||
| #define IF_CHECK_TIMING(__t$) | ||
| #endif | ||
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| namespace mxnet { | ||
| namespace io { | ||
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| struct CaffeDataParam : public dmlc::Parameter<CaffeDataParam> { | ||
| /*! \brief protobuf text */ | ||
| ::caffe::LayerParameter prototxt; | ||
| /*! \brief number of iterations per epoch */ | ||
| int num_examples; | ||
| /*! \brief data mode */ | ||
| bool flat; | ||
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| DMLC_DECLARE_PARAMETER(CaffeDataParam) { | ||
| DMLC_DECLARE_FIELD(prototxt).set_default("layer{}") | ||
| .describe("Caffe's layer parameter"); | ||
| DMLC_DECLARE_FIELD(flat).set_default(false) | ||
| .describe("Augmentation Param: Whether to flat the data into 1D."); | ||
| DMLC_DECLARE_FIELD(num_examples).set_lower_bound(1).set_default(10000) | ||
| .describe("Number of examples in the epoch."); | ||
| } | ||
| }; | ||
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| template<typename Dtype> | ||
| class CaffeDataIter : public IIterator<TBlobBatch> { | ||
| public: | ||
| explicit CaffeDataIter(int type_flag) : batch_size_(0), channels_(0), width_(1), height_(1) | ||
| , type_flag_(type_flag), loc_(0) | ||
| {} | ||
| virtual ~CaffeDataIter(void) {} | ||
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| // intialize iterator loads data in | ||
| virtual void Init(const std::vector<std::pair<std::string, std::string> >& kwargs) { | ||
| std::map<std::string, std::string> kmap(kwargs.begin(), kwargs.end()); | ||
| param_.InitAllowUnknown(kmap); | ||
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| // Caffe seems to understand phase inside an "include {}" block | ||
| if (!param_.prototxt.has_phase()) { | ||
| if (param_.prototxt.include().size()) { | ||
| if (param_.prototxt.include(0).has_phase()) { | ||
| param_.prototxt.set_phase(param_.prototxt.include(0).phase()); | ||
| } | ||
| } | ||
| } | ||
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| std::string type = param_.prototxt.type(); | ||
| caffe_data_layer_ = caffe::LayerRegistry<Dtype>::CreateLayer(param_.prototxt); | ||
| CHECK(caffe_data_layer_ != nullptr) << "Failed creating caffe data layer"; | ||
| const size_t top_size = param_.prototxt.top_size(); | ||
| if (top_size > 0) { | ||
| if (top_size > NR_SUPPORTED_TOP_ITEMS) { | ||
| LOG(WARNING) | ||
| << "Too may \"top\" items, only two (one data, one label) are currently supported"; | ||
| } | ||
| top_.reserve(top_size); | ||
| for (size_t x = 0; x < top_size; ++x) { | ||
| ::caffe::Blob<Dtype> *blob = new ::caffe::Blob<Dtype>(); | ||
| cleanup_blobs_.push_back(std::unique_ptr<::caffe::Blob<Dtype>>(blob)); | ||
| top_.push_back(blob); | ||
| } | ||
| caffe_data_layer_->SetUp(bottom_, top_); | ||
| const std::vector<int> &shape = top_[DATA]->shape(); | ||
| const size_t shapeDimCount = shape.size(); | ||
| if (shapeDimCount > 0) { | ||
| batch_size_ = shape[0]; | ||
| if (shapeDimCount > 1) { | ||
| channels_ = shape[1]; | ||
| if (shapeDimCount > 2) { | ||
| width_ = shape[2]; | ||
| if (shapeDimCount > 3) { | ||
| height_ = shape[3]; | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| if (top_size > DATA) { | ||
| if (param_.flat) { | ||
| batch_data_ = TBlob(nullptr, mshadow::Shape2(batch_size_, width_ * height_), | ||
| cpu::kDevCPU, type_flag_); | ||
| } else { | ||
| batch_data_ = TBlob(nullptr, mxnet::TShape(top_[DATA]->shape().begin(), | ||
| top_[DATA]->shape().end()), | ||
| cpu::kDevCPU, type_flag_); | ||
| } | ||
| } | ||
| out_.data.clear(); | ||
| if (top_size > LABEL) { | ||
| batch_label_ = TBlob(nullptr, mxnet::TShape(top_[LABEL]->shape().begin(), | ||
| top_[LABEL]->shape().end()), | ||
| cpu::kDevCPU, type_flag_); | ||
| } | ||
| out_.batch_size = batch_size_; | ||
| } | ||
| } | ||
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| virtual void BeforeFirst(void) { | ||
| loc_ = 0; | ||
| } | ||
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| virtual bool Next(void) { | ||
| // MxNet iterator is expected to return CPU-accessible memory | ||
| if (::caffe::Caffe::mode() != ::caffe::Caffe::CPU) { | ||
| ::caffe::Caffe::set_mode(::caffe::Caffe::CPU); | ||
| CHECK_EQ(::caffe::Caffe::mode(), ::caffe::Caffe::CPU); | ||
| } | ||
| caffe_data_layer_->Forward(bottom_, top_); | ||
| CHECK_GT(batch_size_, 0) << "batch size must be greater than zero"; | ||
| CHECK_EQ(out_.batch_size, batch_size_) << "Internal Error: batch size mismatch"; | ||
|
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| if (loc_ + batch_size_ <= param_.num_examples) { | ||
| batch_data_.dptr_ = top_[DATA]->mutable_cpu_data(); | ||
| batch_label_.dptr_ = top_[LABEL]->mutable_cpu_data(); | ||
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| out_.data.clear(); | ||
| out_.data.push_back(batch_data_); | ||
| out_.data.push_back(batch_label_); | ||
| loc_ += batch_size_; | ||
| return true; | ||
| } | ||
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| return false; | ||
| } | ||
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| virtual const TBlobBatch &Value(void) const { | ||
| return out_; | ||
| } | ||
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| private: | ||
| /*! \brief indexes into top_ */ | ||
| enum { DATA = 0, LABEL, NR_SUPPORTED_TOP_ITEMS }; | ||
|
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| /*! \brief MNISTCass iter params */ | ||
| CaffeDataParam param_; | ||
| /*! \brief Shape scalar values */ | ||
| index_t batch_size_, channels_, width_, height_; | ||
| /*! \brief Caffe data layer */ | ||
| boost::shared_ptr<caffe::Layer<Dtype> > caffe_data_layer_; | ||
| /*! \brief batch data blob */ | ||
| mxnet::TBlob batch_data_; | ||
| /*! \brief batch label blob */ | ||
| mxnet::TBlob batch_label_; | ||
| /*! \brief Output blob data for this iteration */ | ||
| TBlobBatch out_; | ||
| /*! \brief Bottom and top connection-point blob data */ | ||
| std::vector<::caffe::Blob<Dtype>*> bottom_, top_; | ||
| /*! \brief Cleanup these blobs on exit */ | ||
| std::list<std::unique_ptr<::caffe::Blob<Dtype>>> cleanup_blobs_; | ||
| /*! \brief type flag of the tensor blob */ | ||
| const int type_flag_; | ||
| /*! \brief Blobs done so far */ | ||
| std::atomic<size_t> loc_; | ||
| }; // class CaffeDataIter | ||
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| class CaffeDataIterWrapper : public PrefetcherIter { | ||
| public: | ||
| CaffeDataIterWrapper() : PrefetcherIter(NULL), next_time_(0) {} | ||
| virtual ~CaffeDataIterWrapper() { | ||
| IF_CHECK_TIMING( | ||
| if (next_time_.load() > 0) { | ||
| LOG(WARNING) << "Caffe data loader was blocked for " | ||
| << next_time_.load() | ||
| << " ms waiting for incoming data"; | ||
| } | ||
| ) | ||
| } | ||
| virtual void Init(const std::vector<std::pair<std::string, std::string> >& kwargs) { | ||
| // We need to init prefetcher args in order to get dtype | ||
| this->param_.InitAllowUnknown(kwargs); | ||
| switch (this->param_.dtype) { | ||
| case mshadow::kFloat32: | ||
| this->loader_.reset(new CaffeDataIter<float>(this->param_.dtype)); | ||
| break; | ||
| case mshadow::kFloat64: | ||
| this->loader_.reset(new CaffeDataIter<double>(this->param_.dtype)); | ||
| break; | ||
| case mshadow::kFloat16: | ||
| LOG(FATAL) << "float16 layer is not supported by caffe"; | ||
| return; | ||
| default: | ||
| LOG(FATAL) << "Unsupported type " << this->param_.dtype; | ||
| return; | ||
| } | ||
| PrefetcherIter::Init(kwargs); | ||
| this->param_.prefetch_buffer = 1; | ||
| } | ||
| virtual void BeforeFirst(void) { | ||
| return PrefetcherIter::BeforeFirst(); | ||
| } | ||
| virtual bool Next(void) { | ||
| IF_CHECK_TIMING( | ||
| const uint64_t start_time = GetTickCountMS(); | ||
| ) | ||
| const bool rc = PrefetcherIter::Next(); | ||
| IF_CHECK_TIMING( | ||
| const uint64_t diff_time = GetTickCountMS() - start_time; | ||
| next_time_.fetch_add(diff_time); | ||
| ) | ||
| return rc; | ||
| } | ||
|
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| protected: | ||
| IF_CHECK_TIMING( | ||
| static uint64_t GetTickCountMS() { | ||
| struct timeval tv; | ||
| gettimeofday(&tv, 0); | ||
| return uint64_t( tv.tv_sec ) * 1000 + tv.tv_usec / 1000; | ||
| } | ||
| ) | ||
|
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| /*! \brief milliseconds spent in Next() */ | ||
| std::atomic<uint64_t> next_time_; | ||
| }; // class CaffeDataIterWrapper | ||
|
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| DMLC_REGISTER_PARAMETER(CaffeDataParam); | ||
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| MXNET_REGISTER_IO_ITER(CaffeDataIter) | ||
| .describe("Create MxNet iterator for a Caffe data layer.") | ||
| .add_arguments(CaffeDataParam::__FIELDS__()) | ||
| .add_arguments(PrefetcherParam::__FIELDS__()) | ||
| .set_body([]() { | ||
| return new CaffeDataIterWrapper(); | ||
| }); | ||
|
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| } // namespace io | ||
| } // namespace mxnet | ||
|
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