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Merge pull request #10746 from dkurt:dnn_batch_norm_from_nvidia_caffe

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pull/10758/head
Vadim Pisarevsky 7 years ago
parent 42569cfd61 844f1d0281
commit 713ec7be45
4 changed files with 420 additions and 342 deletions
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  1. 708
      modules/dnn/misc/caffe/opencv-caffe.pb.cc
  2. 46
      modules/dnn/misc/caffe/opencv-caffe.pb.h
  3. 2
      modules/dnn/src/caffe/opencv-caffe.proto
  4. 6
      modules/dnn/src/layers/batch_norm_layer.cpp

708
modules/dnn/misc/caffe/opencv-caffe.pb.cc
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@ -2538,9 +2538,11 @@ const ::google::protobuf::uint32 TableStruct::offsets[] GOOGLE_PROTOBUF_ATTRIBUT
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(::opencv_caffe::BatchNormParameter, use_global_stats_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(::opencv_caffe::BatchNormParameter, moving_average_fraction_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(::opencv_caffe::BatchNormParameter, eps_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(::opencv_caffe::BatchNormParameter, scale_bias_),
0,
1,
2,
3,
1,
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(::opencv_caffe::BiasParameter, _has_bits_),
GOOGLE_PROTOBUF_GENERATED_MESSAGE_FIELD_OFFSET(::opencv_caffe::BiasParameter, _internal_metadata_),
~0u, // no _extensions_
@ -3363,56 +3365,56 @@ static const ::google::protobuf::internal::MigrationSchema schemas[] GOOGLE_PROT
{ 490, 498, sizeof(::opencv_caffe::AccuracyParameter)},
{ 501, 509, sizeof(::opencv_caffe::ArgMaxParameter)},
{ 512, 519, sizeof(::opencv_caffe::ConcatParameter)},
{ 521, 529, sizeof(::opencv_caffe::BatchNormParameter)},
{ 532, 540, sizeof(::opencv_caffe::BiasParameter)},
{ 543, 550, sizeof(::opencv_caffe::ContrastiveLossParameter)},
{ 552, 575, sizeof(::opencv_caffe::ConvolutionParameter)},
{ 593, 600, sizeof(::opencv_caffe::CropParameter)},
{ 602, 617, sizeof(::opencv_caffe::DataParameter)},
{ 627, 635, sizeof(::opencv_caffe::NonMaximumSuppressionParameter)},
{ 638, 649, sizeof(::opencv_caffe::SaveOutputParameter)},
{ 655, 662, sizeof(::opencv_caffe::DropoutParameter)},
{ 664, 675, sizeof(::opencv_caffe::DummyDataParameter)},
{ 681, 689, sizeof(::opencv_caffe::EltwiseParameter)},
{ 692, 698, sizeof(::opencv_caffe::ELUParameter)},
{ 699, 709, sizeof(::opencv_caffe::EmbedParameter)},
{ 714, 722, sizeof(::opencv_caffe::ExpParameter)},
{ 725, 732, sizeof(::opencv_caffe::FlattenParameter)},
{ 734, 742, sizeof(::opencv_caffe::HDF5DataParameter)},
{ 745, 751, sizeof(::opencv_caffe::HDF5OutputParameter)},
{ 752, 758, sizeof(::opencv_caffe::HingeLossParameter)},
{ 759, 776, sizeof(::opencv_caffe::ImageDataParameter)},
{ 788, 794, sizeof(::opencv_caffe::InfogainLossParameter)},
{ 795, 806, sizeof(::opencv_caffe::InnerProductParameter)},
{ 812, 818, sizeof(::opencv_caffe::InputParameter)},
{ 819, 827, sizeof(::opencv_caffe::LogParameter)},
{ 830, 841, sizeof(::opencv_caffe::LRNParameter)},
{ 847, 856, sizeof(::opencv_caffe::MemoryDataParameter)},
{ 860, 868, sizeof(::opencv_caffe::MVNParameter)},
{ 871, 877, sizeof(::opencv_caffe::ParameterParameter)},
{ 878, 896, sizeof(::opencv_caffe::PoolingParameter)},
{ 909, 917, sizeof(::opencv_caffe::PowerParameter)},
{ 920, 929, sizeof(::opencv_caffe::PythonParameter)},
{ 933, 943, sizeof(::opencv_caffe::RecurrentParameter)},
{ 948, 956, sizeof(::opencv_caffe::ReductionParameter)},
{ 959, 966, sizeof(::opencv_caffe::ReLUParameter)},
{ 968, 976, sizeof(::opencv_caffe::ReshapeParameter)},
{ 979, 989, sizeof(::opencv_caffe::ScaleParameter)},
{ 994, 1000, sizeof(::opencv_caffe::SigmoidParameter)},
{ 1001, 1009, sizeof(::opencv_caffe::SliceParameter)},
{ 1012, 1019, sizeof(::opencv_caffe::SoftmaxParameter)},
{ 1021, 1027, sizeof(::opencv_caffe::TanHParameter)},
{ 1028, 1035, sizeof(::opencv_caffe::TileParameter)},
{ 1037, 1043, sizeof(::opencv_caffe::ThresholdParameter)},
{ 1044, 1062, sizeof(::opencv_caffe::WindowDataParameter)},
{ 1075, 1083, sizeof(::opencv_caffe::SPPParameter)},
{ 1086, 1134, sizeof(::opencv_caffe::V1LayerParameter)},
{ 1177, 1220, sizeof(::opencv_caffe::V0LayerParameter)},
{ 1258, 1265, sizeof(::opencv_caffe::PReLUParameter)},
{ 1267, 1280, sizeof(::opencv_caffe::NormalizedBBox)},
{ 1288, 1296, sizeof(::opencv_caffe::ROIPoolingParameter)},
{ 1299, 1312, sizeof(::opencv_caffe::ProposalParameter)},
{ 1320, 1328, sizeof(::opencv_caffe::PSROIPoolingParameter)},
{ 521, 530, sizeof(::opencv_caffe::BatchNormParameter)},
{ 534, 542, sizeof(::opencv_caffe::BiasParameter)},
{ 545, 552, sizeof(::opencv_caffe::ContrastiveLossParameter)},
{ 554, 577, sizeof(::opencv_caffe::ConvolutionParameter)},
{ 595, 602, sizeof(::opencv_caffe::CropParameter)},
{ 604, 619, sizeof(::opencv_caffe::DataParameter)},
{ 629, 637, sizeof(::opencv_caffe::NonMaximumSuppressionParameter)},
{ 640, 651, sizeof(::opencv_caffe::SaveOutputParameter)},
{ 657, 664, sizeof(::opencv_caffe::DropoutParameter)},
{ 666, 677, sizeof(::opencv_caffe::DummyDataParameter)},
{ 683, 691, sizeof(::opencv_caffe::EltwiseParameter)},
{ 694, 700, sizeof(::opencv_caffe::ELUParameter)},
{ 701, 711, sizeof(::opencv_caffe::EmbedParameter)},
{ 716, 724, sizeof(::opencv_caffe::ExpParameter)},
{ 727, 734, sizeof(::opencv_caffe::FlattenParameter)},
{ 736, 744, sizeof(::opencv_caffe::HDF5DataParameter)},
{ 747, 753, sizeof(::opencv_caffe::HDF5OutputParameter)},
{ 754, 760, sizeof(::opencv_caffe::HingeLossParameter)},
{ 761, 778, sizeof(::opencv_caffe::ImageDataParameter)},
{ 790, 796, sizeof(::opencv_caffe::InfogainLossParameter)},
{ 797, 808, sizeof(::opencv_caffe::InnerProductParameter)},
{ 814, 820, sizeof(::opencv_caffe::InputParameter)},
{ 821, 829, sizeof(::opencv_caffe::LogParameter)},
{ 832, 843, sizeof(::opencv_caffe::LRNParameter)},
{ 849, 858, sizeof(::opencv_caffe::MemoryDataParameter)},
{ 862, 870, sizeof(::opencv_caffe::MVNParameter)},
{ 873, 879, sizeof(::opencv_caffe::ParameterParameter)},
{ 880, 898, sizeof(::opencv_caffe::PoolingParameter)},
{ 911, 919, sizeof(::opencv_caffe::PowerParameter)},
{ 922, 931, sizeof(::opencv_caffe::PythonParameter)},
{ 935, 945, sizeof(::opencv_caffe::RecurrentParameter)},
{ 950, 958, sizeof(::opencv_caffe::ReductionParameter)},
{ 961, 968, sizeof(::opencv_caffe::ReLUParameter)},
{ 970, 978, sizeof(::opencv_caffe::ReshapeParameter)},
{ 981, 991, sizeof(::opencv_caffe::ScaleParameter)},
{ 996, 1002, sizeof(::opencv_caffe::SigmoidParameter)},
{ 1003, 1011, sizeof(::opencv_caffe::SliceParameter)},
{ 1014, 1021, sizeof(::opencv_caffe::SoftmaxParameter)},
{ 1023, 1029, sizeof(::opencv_caffe::TanHParameter)},
{ 1030, 1037, sizeof(::opencv_caffe::TileParameter)},
{ 1039, 1045, sizeof(::opencv_caffe::ThresholdParameter)},
{ 1046, 1064, sizeof(::opencv_caffe::WindowDataParameter)},
{ 1077, 1085, sizeof(::opencv_caffe::SPPParameter)},
{ 1088, 1136, sizeof(::opencv_caffe::V1LayerParameter)},
{ 1179, 1222, sizeof(::opencv_caffe::V0LayerParameter)},
{ 1260, 1267, sizeof(::opencv_caffe::PReLUParameter)},
{ 1269, 1282, sizeof(::opencv_caffe::NormalizedBBox)},
{ 1290, 1298, sizeof(::opencv_caffe::ROIPoolingParameter)},
{ 1301, 1314, sizeof(::opencv_caffe::ProposalParameter)},
{ 1322, 1330, sizeof(::opencv_caffe::PSROIPoolingParameter)},
};
static ::google::protobuf::Message const * const file_default_instances[] = {
@ -3709,282 +3711,282 @@ void AddDescriptorsImpl() {
"abel\030\003 \001(\005\"M\n\017ArgMaxParameter\022\032\n\013out_max"
"_val\030\001 \001(\010:\005false\022\020\n\005top_k\030\002 \001(\r:\0011\022\014\n\004a"
"xis\030\003 \001(\005\"9\n\017ConcatParameter\022\017\n\004axis\030\002 \001"
"(\005:\0011\022\025\n\nconcat_dim\030\001 \001(\r:\0011\"j\n\022BatchNor"
"mParameter\022\030\n\020use_global_stats\030\001 \001(\010\022&\n\027"
"moving_average_fraction\030\002 \001(\002:\0050.999\022\022\n\003"
"eps\030\003 \001(\002:\0051e-05\"d\n\rBiasParameter\022\017\n\004axi"
"s\030\001 \001(\005:\0011\022\023\n\010num_axes\030\002 \001(\005:\0011\022-\n\006fille"
"r\030\003 \001(\0132\035.opencv_caffe.FillerParameter\"L"
"\n\030ContrastiveLossParameter\022\021\n\006margin\030\001 \001"
"(\002:\0011\022\035\n\016legacy_version\030\002 \001(\010:\005false\"\221\004\n"
"\024ConvolutionParameter\022\022\n\nnum_output\030\001 \001("
"\r\022\027\n\tbias_term\030\002 \001(\010:\004true\022\013\n\003pad\030\003 \003(\r\022"
"\023\n\013kernel_size\030\004 \003(\r\022\016\n\006stride\030\006 \003(\r\022\020\n\010"
"dilation\030\022 \003(\r\022\020\n\005pad_h\030\t \001(\r:\0010\022\020\n\005pad_"
"w\030\n \001(\r:\0010\022\020\n\010kernel_h\030\013 \001(\r\022\020\n\010kernel_w"
"\030\014 \001(\r\022\020\n\010stride_h\030\r \001(\r\022\020\n\010stride_w\030\016 \001"
"(\r\022\020\n\005group\030\005 \001(\r:\0011\0224\n\rweight_filler\030\007 "
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"is\030\020 \001(\005:\0011\022\036\n\017force_nd_im2col\030\021 \001(\010:\005fa"
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"\005CUDNN\020\002\"0\n\rCropParameter\022\017\n\004axis\030\001 \001(\005:"
"\0012\022\016\n\006offset\030\002 \003(\r\"\253\002\n\rDataParameter\022\016\n\006"
"source\030\001 \001(\t\022\022\n\nbatch_size\030\004 \001(\r\022\024\n\trand"
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"_caffe.DataParameter.DB:\007LEVELDB\022\020\n\005scal"
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"rce_encoded_color\030\t \001(\010:\005false\022\023\n\010prefet"
"ch\030\n \001(\r:\0014\"\033\n\002DB\022\013\n\007LEVELDB\020\000\022\010\n\004LMDB\020\001"
"\"[\n\036NonMaximumSuppressionParameter\022\032\n\rnm"
"s_threshold\030\001 \001(\002:\0030.3\022\r\n\005top_k\030\002 \001(\005\022\016\n"
"\003eta\030\003 \001(\002:\0011\"\252\001\n\023SaveOutputParameter\022\030\n"
"\020output_directory\030\001 \001(\t\022\032\n\022output_name_p"
"refix\030\002 \001(\t\022\025\n\routput_format\030\003 \001(\t\022\026\n\016la"
"bel_map_file\030\004 \001(\t\022\026\n\016name_size_file\030\005 \001"
"(\t\022\026\n\016num_test_image\030\006 \001(\r\"I\n\020DropoutPar"
"ameter\022\032\n\rdropout_ratio\030\001 \001(\002:\0030.5\022\031\n\013sc"
"ale_train\030\002 \001(\010:\004true\"\256\001\n\022DummyDataParam"
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".FillerParameter\022&\n\005shape\030\006 \003(\0132\027.opencv"
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"s\030\003 \003(\r\022\016\n\006height\030\004 \003(\r\022\r\n\005width\030\005 \003(\r\"\254"
"\001\n\020EltwiseParameter\022@\n\toperation\030\001 \001(\0162("
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" \001(\002:\0011\"\272\001\n\016EmbedParameter\022\022\n\nnum_output"
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"\005 \001(\0132\035.opencv_caffe.FillerParameter\"D\n\014"
"ExpParameter\022\020\n\004base\030\001 \001(\002:\002-1\022\020\n\005scale\030"
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"size\030\004 \001(\r:\0011\022\024\n\trand_skip\030\007 \001(\r:\0010\022\026\n\007s"
"huffle\030\010 \001(\010:\005false\022\025\n\nnew_height\030\t \001(\r:"
"\0010\022\024\n\tnew_width\030\n \001(\r:\0010\022\026\n\010is_color\030\013 \001"
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"\003 \001(\t\022\024\n\tcrop_size\030\005 \001(\r:\0010\022\025\n\006mirror\030\006 "
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"ogainLossParameter\022\016\n\006source\030\001 \001(\t\"\331\001\n\025I"
"nnerProductParameter\022\022\n\nnum_output\030\001 \001(\r"
"\022\027\n\tbias_term\030\002 \001(\010:\004true\0224\n\rweight_fill"
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"2\n\013bias_filler\030\004 \001(\0132\035.opencv_caffe.Fill"
"erParameter\022\017\n\004axis\030\005 \001(\005:\0011\022\030\n\ttranspos"
"e\030\006 \001(\010:\005false\"8\n\016InputParameter\022&\n\005shap"
"e\030\001 \003(\0132\027.opencv_caffe.BlobShape\"D\n\014LogP"
"arameter\022\020\n\004base\030\001 \001(\002:\002-1\022\020\n\005scale\030\002 \001("
"\002:\0011\022\020\n\005shift\030\003 \001(\002:\0010\"\306\002\n\014LRNParameter\022"
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"\022\022\n\004beta\030\003 \001(\002:\0040.75\022K\n\013norm_region\030\004 \001("
"\0162%.opencv_caffe.LRNParameter.NormRegion"
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"ne:\007DEFAULT\"5\n\nNormRegion\022\023\n\017ACROSS_CHAN"
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"ethod:\003MAX\022\016\n\003pad\030\004 \001(\r:\0010\022\020\n\005pad_h\030\t \001("
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"\021\n\006stride\030\003 \001(\r:\0011\022\020\n\010stride_h\030\007 \001(\r\022\020\n\010"
"stride_w\030\010 \001(\r\022>\n\006engine\030\013 \001(\0162%.opencv_"
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"\n\016global_pooling\030\014 \001(\010:\005false\022\027\n\tceil_mo"
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"ULT\020\000\022\t\n\005CAFFE\020\001\022\t\n\005CUDNN\020\002\"F\n\016PowerPara"
"meter\022\020\n\005power\030\001 \001(\002:\0011\022\020\n\005scale\030\002 \001(\002:\001"
"1\022\020\n\005shift\030\003 \001(\002:\0010\"g\n\017PythonParameter\022\016"
"\n\006module\030\001 \001(\t\022\r\n\005layer\030\002 \001(\t\022\023\n\tparam_s"
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"cv_caffe.FillerParameter\0222\n\013bias_filler\030"
"\003 \001(\0132\035.opencv_caffe.FillerParameter\022\031\n\n"
"debug_info\030\004 \001(\010:\005false\022\034\n\rexpose_hidden"
"\030\005 \001(\010:\005false\"\264\001\n\022ReductionParameter\022D\n\t"
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"\rReLUParameter\022\031\n\016negative_slope\030\001 \001(\002:\001"
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"\035.opencv_caffe.FillerParameter\022\030\n\tbias_t"
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"\016SliceParameter\022\017\n\004axis\030\003 \001(\005:\0011\022\023\n\013slic"
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"SoftmaxParameter\022>\n\006engine\030\001 \001(\0162%.openc"
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};
::google::protobuf::DescriptorPool::InternalAddGeneratedFile(
descriptor, 18805);
descriptor, 18833);
::google::protobuf::MessageFactory::InternalRegisterGeneratedFile(
"opencv-caffe.proto", &protobuf_RegisterTypes);
}
@ -18451,6 +18453,7 @@ void BatchNormParameter::InitAsDefaultInstance() {
const int BatchNormParameter::kUseGlobalStatsFieldNumber;
const int BatchNormParameter::kMovingAverageFractionFieldNumber;
const int BatchNormParameter::kEpsFieldNumber;
const int BatchNormParameter::kScaleBiasFieldNumber;
#endif // !defined(_MSC_VER) || _MSC_VER >= 1900
BatchNormParameter::BatchNormParameter()
@ -18475,7 +18478,9 @@ BatchNormParameter::BatchNormParameter(const BatchNormParameter& from)
void BatchNormParameter::SharedCtor() {
_cached_size_ = 0;
use_global_stats_ = false;
::memset(&use_global_stats_, 0, static_cast<size_t>(
reinterpret_cast<char*>(&scale_bias_) -
reinterpret_cast<char*>(&use_global_stats_)) + sizeof(scale_bias_));
moving_average_fraction_ = 0.999f;
eps_ = 1e-05f;
}
@ -18517,9 +18522,11 @@ void BatchNormParameter::Clear() {
// Prevent compiler warnings about cached_has_bits being unused
(void) cached_has_bits;
::memset(&use_global_stats_, 0, static_cast<size_t>(
reinterpret_cast<char*>(&scale_bias_) -
reinterpret_cast<char*>(&use_global_stats_)) + sizeof(scale_bias_));
cached_has_bits = _has_bits_[0];
if (cached_has_bits & 7u) {
use_global_stats_ = false;
if (cached_has_bits & 12u) {
moving_average_fraction_ = 0.999f;
eps_ = 1e-05f;
}
@ -18579,6 +18586,20 @@ bool BatchNormParameter::MergePartialFromCodedStream(
break;
}
// optional bool scale_bias = 7 [default = false];
case 7: {
if (static_cast< ::google::protobuf::uint8>(tag) ==
static_cast< ::google::protobuf::uint8>(56u /* 56 & 0xFF */)) {
set_has_scale_bias();
DO_((::google::protobuf::internal::WireFormatLite::ReadPrimitive<
bool, ::google::protobuf::internal::WireFormatLite::TYPE_BOOL>(
input, &scale_bias_)));
} else {
goto handle_unusual;
}
break;
}
default: {
handle_unusual:
if (tag == 0) {
@ -18612,15 +18633,20 @@ void BatchNormParameter::SerializeWithCachedSizes(
}
// optional float moving_average_fraction = 2 [default = 0.999];
if (cached_has_bits & 0x00000002u) {
if (cached_has_bits & 0x00000004u) {
::google::protobuf::internal::WireFormatLite::WriteFloat(2, this->moving_average_fraction(), output);
}
// optional float eps = 3 [default = 1e-05];
if (cached_has_bits & 0x00000004u) {
if (cached_has_bits & 0x00000008u) {
::google::protobuf::internal::WireFormatLite::WriteFloat(3, this->eps(), output);
}
// optional bool scale_bias = 7 [default = false];
if (cached_has_bits & 0x00000002u) {
::google::protobuf::internal::WireFormatLite::WriteBool(7, this->scale_bias(), output);
}
if (_internal_metadata_.have_unknown_fields()) {
::google::protobuf::internal::WireFormat::SerializeUnknownFields(
_internal_metadata_.unknown_fields(), output);
@ -18642,15 +18668,20 @@ void BatchNormParameter::SerializeWithCachedSizes(
}
// optional float moving_average_fraction = 2 [default = 0.999];
if (cached_has_bits & 0x00000002u) {
if (cached_has_bits & 0x00000004u) {
target = ::google::protobuf::internal::WireFormatLite::WriteFloatToArray(2, this->moving_average_fraction(), target);
}
// optional float eps = 3 [default = 1e-05];
if (cached_has_bits & 0x00000004u) {
if (cached_has_bits & 0x00000008u) {
target = ::google::protobuf::internal::WireFormatLite::WriteFloatToArray(3, this->eps(), target);
}
// optional bool scale_bias = 7 [default = false];
if (cached_has_bits & 0x00000002u) {
target = ::google::protobuf::internal::WireFormatLite::WriteBoolToArray(7, this->scale_bias(), target);
}
if (_internal_metadata_.have_unknown_fields()) {
target = ::google::protobuf::internal::WireFormat::SerializeUnknownFieldsToArray(
_internal_metadata_.unknown_fields(), target);
@ -18668,12 +18699,17 @@ size_t BatchNormParameter::ByteSizeLong() const {
::google::protobuf::internal::WireFormat::ComputeUnknownFieldsSize(
_internal_metadata_.unknown_fields());
}
if (_has_bits_[0 / 32] & 7u) {
if (_has_bits_[0 / 32] & 15u) {
// optional bool use_global_stats = 1;
if (has_use_global_stats()) {
total_size += 1 + 1;
}
// optional bool scale_bias = 7 [default = false];
if (has_scale_bias()) {
total_size += 1 + 1;
}
// optional float moving_average_fraction = 2 [default = 0.999];
if (has_moving_average_fraction()) {
total_size += 1 + 4;
@ -18715,14 +18751,17 @@ void BatchNormParameter::MergeFrom(const BatchNormParameter& from) {
(void) cached_has_bits;
cached_has_bits = from._has_bits_[0];
if (cached_has_bits & 7u) {
if (cached_has_bits & 15u) {
if (cached_has_bits & 0x00000001u) {
use_global_stats_ = from.use_global_stats_;
}
if (cached_has_bits & 0x00000002u) {
moving_average_fraction_ = from.moving_average_fraction_;
scale_bias_ = from.scale_bias_;
}
if (cached_has_bits & 0x00000004u) {
moving_average_fraction_ = from.moving_average_fraction_;
}
if (cached_has_bits & 0x00000008u) {
eps_ = from.eps_;
}
_has_bits_[0] |= cached_has_bits;
@ -18754,6 +18793,7 @@ void BatchNormParameter::Swap(BatchNormParameter* other) {
void BatchNormParameter::InternalSwap(BatchNormParameter* other) {
using std::swap;
swap(use_global_stats_, other->use_global_stats_);
swap(scale_bias_, other->scale_bias_);
swap(moving_average_fraction_, other->moving_average_fraction_);
swap(eps_, other->eps_);
swap(_has_bits_[0], other->_has_bits_[0]);

46
modules/dnn/misc/caffe/opencv-caffe.pb.h
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@ -5958,6 +5958,13 @@ class BatchNormParameter : public ::google::protobuf::Message /* @@protoc_insert
bool use_global_stats() const;
void set_use_global_stats(bool value);
// optional bool scale_bias = 7 [default = false];
bool has_scale_bias() const;
void clear_scale_bias();
static const int kScaleBiasFieldNumber = 7;
bool scale_bias() const;
void set_scale_bias(bool value);
// optional float moving_average_fraction = 2 [default = 0.999];
bool has_moving_average_fraction() const;
void clear_moving_average_fraction();
@ -5980,11 +5987,14 @@ class BatchNormParameter : public ::google::protobuf::Message /* @@protoc_insert
void clear_has_moving_average_fraction();
void set_has_eps();
void clear_has_eps();
void set_has_scale_bias();
void clear_has_scale_bias();
::google::protobuf::internal::InternalMetadataWithArena _internal_metadata_;
::google::protobuf::internal::HasBits<1> _has_bits_;
mutable int _cached_size_;
bool use_global_stats_;
bool scale_bias_;
float moving_average_fraction_;
float eps_;
friend struct ::protobuf_opencv_2dcaffe_2eproto::TableStruct;
@ -22720,13 +22730,13 @@ inline void BatchNormParameter::set_use_global_stats(bool value) {
// optional float moving_average_fraction = 2 [default = 0.999];
inline bool BatchNormParameter::has_moving_average_fraction() const {
return (_has_bits_[0] & 0x00000002u) != 0;
return (_has_bits_[0] & 0x00000004u) != 0;
}
inline void BatchNormParameter::set_has_moving_average_fraction() {
_has_bits_[0] |= 0x00000002u;
_has_bits_[0] |= 0x00000004u;
}
inline void BatchNormParameter::clear_has_moving_average_fraction() {
_has_bits_[0] &= ~0x00000002u;
_has_bits_[0] &= ~0x00000004u;
}
inline void BatchNormParameter::clear_moving_average_fraction() {
moving_average_fraction_ = 0.999f;
@ -22744,13 +22754,13 @@ inline void BatchNormParameter::set_moving_average_fraction(float value) {
// optional float eps = 3 [default = 1e-05];
inline bool BatchNormParameter::has_eps() const {
return (_has_bits_[0] & 0x00000004u) != 0;
return (_has_bits_[0] & 0x00000008u) != 0;
}
inline void BatchNormParameter::set_has_eps() {
_has_bits_[0] |= 0x00000004u;
_has_bits_[0] |= 0x00000008u;
}
inline void BatchNormParameter::clear_has_eps() {
_has_bits_[0] &= ~0x00000004u;
_has_bits_[0] &= ~0x00000008u;
}
inline void BatchNormParameter::clear_eps() {
eps_ = 1e-05f;
@ -22766,6 +22776,30 @@ inline void BatchNormParameter::set_eps(float value) {
// @@protoc_insertion_point(field_set:opencv_caffe.BatchNormParameter.eps)
}
// optional bool scale_bias = 7 [default = false];
inline bool BatchNormParameter::has_scale_bias() const {
return (_has_bits_[0] & 0x00000002u) != 0;
}
inline void BatchNormParameter::set_has_scale_bias() {
_has_bits_[0] |= 0x00000002u;
}
inline void BatchNormParameter::clear_has_scale_bias() {
_has_bits_[0] &= ~0x00000002u;
}
inline void BatchNormParameter::clear_scale_bias() {
scale_bias_ = false;
clear_has_scale_bias();
}
inline bool BatchNormParameter::scale_bias() const {
// @@protoc_insertion_point(field_get:opencv_caffe.BatchNormParameter.scale_bias)
return scale_bias_;
}
inline void BatchNormParameter::set_scale_bias(bool value) {
set_has_scale_bias();
scale_bias_ = value;
// @@protoc_insertion_point(field_set:opencv_caffe.BatchNormParameter.scale_bias)
}
// -------------------------------------------------------------------
// BiasParameter

2
modules/dnn/src/caffe/opencv-caffe.proto
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@ -672,6 +672,8 @@ message BatchNormParameter {
// Small value to add to the variance estimate so that we don't divide by
// zero.
optional float eps = 3 [default = 1e-5];
// It true, scale and add biases. Source: https://github.com/NVIDIA/caffe/
optional bool scale_bias = 7 [default = false];
}
message BiasParameter {

6
modules/dnn/src/layers/batch_norm_layer.cpp
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@ -32,6 +32,8 @@ public:
hasWeights = params.get<bool>("has_weight", false);
hasBias = params.get<bool>("has_bias", false);
if(params.get<bool>("scale_bias", false))
hasWeights = hasBias = true;
epsilon = params.get<float>("eps", 1E-5);
size_t n = blobs[0].total();
@ -47,8 +49,8 @@ public:
varMeanScale = 1/varMeanScale;
}
const int weightsBlobIndex = 2;
const int biasBlobIndex = weightsBlobIndex + hasWeights;
const int biasBlobIndex = blobs.size() - 1;
const int weightsBlobIndex = biasBlobIndex - hasBias;
if( hasWeights )
{

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