| Class | Description |
|---|---|
| AccuracyParameter | |
| Arena | |
| Arena.Destruct_Pointer | |
| ArenaOptions | |
| ArenaOptions.Block_alloc_long | |
| ArenaOptions.Block_dealloc_Pointer_long | |
| ArenaStringPtr | |
| ArgMaxParameter | |
| AuxillaryParseTableField | |
| AuxillaryParseTableField.enum_aux | |
| AuxillaryParseTableField.EnumValidator | |
| AuxillaryParseTableField.map_aux | |
| AuxillaryParseTableField.map_aux.Parse_map_CodedInputStream_Pointer | |
| AuxillaryParseTableField.message_aux | |
| AuxillaryParseTableField.string_aux | |
| BatchNormParameter | |
| BiasParameter | |
| BlobProto | |
| BlobProtoVector | |
| BlobShape | |
| BoolVector | |
| BoolVector.Iterator | |
| BoolVectorVector | |
| BoolVectorVector.Iterator | |
| BoundedZCIS | |
| Caffe | |
| Caffe.RNG | |
| CelMapReflectionFriend | |
| CodedInputStream | |
| CodedOutputStream | |
| CommandLineInterface | |
| CompareHelper | |
| CompareMapKey | |
| ConcatParameter | |
| ContrastiveLossParameter | |
| ConvolutionParameter | |
| CPUTimer | |
| CropParameter | |
| Cursor | |
| DataParameter | |
| Datum | |
| DatumBlockingQueue | |
| DatumVector | |
| DatumVector.Iterator | |
| DB | |
| DebugStringOptions | |
| Descriptor | |
| Descriptor.ExtensionRange | |
| Descriptor.ReservedRange | |
| DescriptorBuilder | |
| DescriptorDatabase | |
| DescriptorPool | |
| DescriptorPool.ErrorCollector | |
| DescriptorProto | |
| DescriptorProto_ExtensionRange | |
| DescriptorTest | |
| DoubleAbsValLayer | |
| DoubleAccuracyLayer | |
| DoubleAdaDeltaSolver | |
| DoubleAdaGradSolver | |
| DoubleAdamSolver | |
| DoubleArgMaxLayer | |
| DoubleBaseConvolutionLayer | |
| DoubleBaseDataLayer | |
| DoubleBasePrefetchingDataLayer | |
| DoubleBatch | |
| DoubleBatchNormLayer | |
| DoubleBatchReindexLayer | |
| DoubleBilinearFiller | |
| DoubleBlob | |
| DoubleBlobSharedVector | |
| DoubleBlobSharedVector.Iterator | |
| DoubleBlobVector | |
| DoubleBlobVector.Iterator | |
| DoubleBlobVectorVector | |
| DoubleBlobVectorVector.Iterator | |
| DoubleBNLLLayer | |
| DoubleCallbackVector | |
| DoubleCallbackVector.Iterator | |
| DoubleConcatLayer | |
| DoubleConstantFiller | |
| DoubleContrastiveLossLayer | |
| DoubleConvolutionLayer | |
| DoubleCropLayer | |
| DoubleCuDNNConvolutionLayer | |
| DoubleCuDNNLCNLayer | |
| DoubleCuDNNLRNLayer | |
| DoubleCuDNNPoolingLayer | |
| DoubleCuDNNReLULayer | |
| DoubleCuDNNSigmoidLayer | |
| DoubleCuDNNSoftmaxLayer | |
| DoubleCuDNNTanHLayer | |
| DoubleDataLayer | |
| DoubleDataTransformer | |
| DoubleDeconvolutionLayer | |
| DoubleDropoutLayer | |
| DoubleDummyDataLayer | |
| DoubleEltwiseLayer | |
| DoubleEmbedLayer | |
| DoubleEuclideanLossLayer | |
| DoubleExpLayer | |
| DoubleFiller | |
| DoubleFilterLayer | |
| DoubleFlattenLayer | |
| DoubleGaussianFiller | |
| DoubleHDF5DataLayer | |
| DoubleHDF5OutputLayer | |
| DoubleHingeLossLayer | |
| DoubleIm2colLayer | |
| DoubleImageDataLayer | |
| DoubleInfogainLossLayer | |
| DoubleInnerProductLayer | |
| DoubleInputLayer | |
| DoubleLayer | |
| DoubleLayerRegisterer | |
| DoubleLayerRegisterer.Creator_LayerParameter | |
| DoubleLayerRegistry | |
| DoubleLayerRegistry.Creator | |
| DoubleLayerSharedVector | |
| DoubleLayerSharedVector.Iterator | |
| DoubleLossLayer | |
| DoubleLRNLayer | |
| DoubleLSTMLayer | |
| DoubleMemoryDataLayer | |
| DoubleMSRAFiller | |
| DoubleMultinomialLogisticLossLayer | |
| DoubleMVNLayer | |
| DoubleNesterovSolver | |
| DoubleNet | |
| DoubleNet.Callback | |
| DoubleNetSharedVector | |
| DoubleNetSharedVector.Iterator | |
| DoubleNeuronLayer | |
| DoubleParameterLayer | |
| DoublePoolingLayer | |
| DoublePositiveUnitballFiller | |
| DoublePowerLayer | |
| DoublePReLULayer | |
| DoubleRecurrentLayer | |
| DoubleReductionLayer | |
| DoubleRegistry | |
| DoubleRegistry.Iterator | |
| DoubleReLULayer | |
| DoubleReshapeLayer | |
| DoubleRMSPropSolver | |
| DoubleRNNLayer | |
| DoubleSGDSolver | |
| DoubleSigmoidCrossEntropyLossLayer | |
| DoubleSigmoidLayer | |
| DoubleSilenceLayer | |
| DoubleSliceLayer | |
| DoubleSoftmaxLayer | |
| DoubleSoftmaxWithLossLayer | |
| DoubleSolver | |
| DoubleSolver.Callback | |
| DoubleSolverRegisterer | |
| DoubleSolverRegisterer.Creator_SolverParameter | |
| DoubleSolverRegistry | |
| DoubleSolverRegistry.Creator | |
| DoubleSplitLayer | |
| DoubleSPPLayer | |
| DoubleTanHLayer | |
| DoubleThresholdLayer | |
| DoubleTileLayer | |
| DoubleUniformFiller | |
| DoubleWindowDataLayer | |
| DoubleXavierFiller | |
| DropoutParameter | |
| DummyDataParameter | |
| EltwiseParameter | |
| ELUParameter | |
| EmbedParameter | |
| EnumDescriptor | |
| EnumDescriptor.ReservedRange | |
| EnumDescriptorProto | |
| EnumOptions | |
| EnumValueDescriptor | |
| EnumValueDescriptorProto | |
| EnumValueOptions | |
| ExpParameter | |
| ExtensionRangeOptions | |
| F_Pointer | |
| FatalException | |
| FieldDescriptor | |
| FieldDescriptorProto | |
| FieldDescriptorVector | |
| FieldDescriptorVector.Iterator | |
| FieldOptions | |
| FileDescriptor | |
| FileDescriptorProto | |
| FileDescriptorTables | |
| FileOptions | |
| FillerParameter | |
| FlattenParameter | |
| FloatAbsValLayer |
\brief Computes
y = |x| |
| FloatAccuracyLayer |
\brief Computes the classification accuracy for a one-of-many
classification task.
|
| FloatAdaDeltaSolver | |
| FloatAdaGradSolver | |
| FloatAdamSolver |
\brief AdamSolver, an algorithm for first-order gradient-based optimization
of stochastic objective functions, based on adaptive estimates of
lower-order moments.
|
| FloatArgMaxLayer |
\brief Compute the index of the
K max values for each datum across
all dimensions (C \times H \times W) . |
| FloatBaseConvolutionLayer |
\brief Abstract base class that factors out the BLAS code common to
ConvolutionLayer and DeconvolutionLayer.
|
| FloatBaseDataLayer |
\brief Provides base for data layers that feed blobs to the Net.
|
| FloatBasePrefetchingDataLayer | |
| FloatBatch | |
| FloatBatchNormLayer |
\brief Normalizes the input to have 0-mean and/or unit (1) variance across
the batch.
|
| FloatBatchReindexLayer |
\brief Index into the input blob along its first axis.
|
| FloatBilinearFiller |
\brief Fills a Blob with coefficients for bilinear interpolation.
|
| FloatBlob |
\brief A wrapper around SyncedMemory holders serving as the basic
computational unit through which Layer%s, Net%s, and Solver%s
interact.
|
| FloatBlobSharedVector | |
| FloatBlobSharedVector.Iterator | |
| FloatBlobVector | |
| FloatBlobVector.Iterator | |
| FloatBlobVectorVector | |
| FloatBlobVectorVector.Iterator | |
| FloatBNLLLayer |
\brief Computes
y = x + \log(1 + \exp(-x)) if x > 0 ;
y = \log(1 + \exp(x)) otherwise. |
| FloatCallbackVector | |
| FloatCallbackVector.Iterator | |
| FloatConcatLayer |
\brief Takes at least two Blob%s and concatenates them along either the num
or channel dimension, outputting the result.
|
| FloatConstantFiller |
\brief Fills a Blob with constant values
x = 0 . |
| FloatContrastiveLossLayer |
\brief Computes the contrastive loss
E = \frac{1}{2N} \sum\limits_{n=1}^N \left(y\right) d^2 +
\left(1-y\right) \max \left(margin-d, 0\right)^2
where d = \left| \left| a_n - b_n \right| \right|_2 . |
| FloatConvolutionLayer |
\brief Convolves the input image with a bank of learned filters,
and (optionally) adds biases.
|
| FloatCropLayer |
\brief Takes a Blob and crop it, to the shape specified by the second input
Blob, across all dimensions after the specified axis.
|
| FloatCuDNNConvolutionLayer | |
| FloatCuDNNLCNLayer | |
| FloatCuDNNLRNLayer | |
| FloatCuDNNPoolingLayer | |
| FloatCuDNNReLULayer |
\brief CuDNN acceleration of ReLULayer.
|
| FloatCuDNNSigmoidLayer |
\brief CuDNN acceleration of SigmoidLayer.
|
| FloatCuDNNSoftmaxLayer |
\brief cuDNN implementation of SoftmaxLayer.
|
| FloatCuDNNTanHLayer |
\brief CuDNN acceleration of TanHLayer.
|
| FloatDataLayer | |
| FloatDataTransformer |
\brief Applies common transformations to the input data, such as
scaling, mirroring, substracting the image mean...
|
| FloatDeconvolutionLayer |
\brief Convolve the input with a bank of learned filters, and (optionally)
add biases, treating filters and convolution parameters in the
opposite sense as ConvolutionLayer.
|
| FloatDropoutLayer |
\brief During training only, sets a random portion of
x to 0, adjusting
the rest of the vector magnitude accordingly. |
| FloatDummyDataLayer |
\brief Provides data to the Net generated by a Filler.
|
| FloatEltwiseLayer |
\brief Compute elementwise operations, such as product and sum,
along multiple input Blobs.
|
| FloatEmbedLayer |
\brief A layer for learning "embeddings" of one-hot vector input.
|
| FloatEuclideanLossLayer |
\brief Computes the Euclidean (L2) loss
E = \frac{1}{2N} \sum\limits_{n=1}^N \left| \left| \hat{y}_n - y_n
\right| \right|_2^2 for real-valued regression tasks. |
| FloatExpLayer |
\brief Computes
y = \gamma ^ {\alpha x + \beta} ,
as specified by the scale \alpha , shift \beta ,
and base \gamma . |
| FloatFiller |
\brief Fills a Blob with constant or randomly-generated data.
|
| FloatFilterLayer |
\brief Takes two+ Blobs, interprets last Blob as a selector and
filter remaining Blobs accordingly with selector data (0 means that
the corresponding item has to be filtered, non-zero means that corresponding
item needs to stay).
|
| FloatFlattenLayer |
\brief Reshapes the input Blob into flat vectors.
|
| FloatGaussianFiller |
\brief Fills a Blob with Gaussian-distributed values
x = a . |
| FloatHDF5DataLayer |
\brief Provides data to the Net from HDF5 files.
|
| FloatHDF5OutputLayer |
\brief Write blobs to disk as HDF5 files.
|
| FloatHingeLossLayer |
\brief Computes the hinge loss for a one-of-many classification task.
|
| FloatIm2colLayer |
\brief A helper for image operations that rearranges image regions into
column vectors.
|
| FloatImageDataLayer |
\brief Provides data to the Net from image files.
|
| FloatInfogainLossLayer |
\brief A generalization of MultinomialLogisticLossLayer that takes an
"information gain" (infogain) matrix specifying the "value" of all label
pairs.
|
| FloatInnerProductLayer |
\brief Also known as a "fully-connected" layer, computes an inner product
with a set of learned weights, and (optionally) adds biases.
|
| FloatInputLayer |
\brief Provides data to the Net by assigning tops directly.
|
| FloatLayer |
\brief An interface for the units of computation which can be composed into a
Net.
|
| FloatLayerRegisterer | |
| FloatLayerRegisterer.Creator_LayerParameter | |
| FloatLayerRegistry | |
| FloatLayerRegistry.Creator | |
| FloatLayerSharedVector | |
| FloatLayerSharedVector.Iterator | |
| FloatLossLayer |
\brief An interface for Layer%s that take two Blob%s as input -- usually
(1) predictions and (2) ground-truth labels -- and output a
singleton Blob representing the loss.
|
| FloatLRNLayer |
\brief Normalize the input in a local region across or within feature maps.
|
| FloatLSTMLayer |
\brief Processes sequential inputs using a "Long Short-Term Memory" (LSTM)
[1] style recurrent neural network (RNN).
|
| FloatMemoryDataLayer |
\brief Provides data to the Net from memory.
|
| FloatMSRAFiller |
\brief Fills a Blob with values
x \sim N(0, \sigma^2) where
\sigma^2 is set inversely proportional to number of incoming
nodes, outgoing nodes, or their average. |
| FloatMultinomialLogisticLossLayer |
\brief Computes the multinomial logistic loss for a one-of-many
classification task, directly taking a predicted probability
distribution as input.
|
| FloatMVNLayer |
\brief Normalizes the input to have 0-mean and/or unit (1) variance.
|
| FloatNesterovSolver | |
| FloatNet |
\brief Connects Layer%s together into a directed acyclic graph (DAG)
specified by a NetParameter.
|
| FloatNet.Callback | |
| FloatNetSharedVector | |
| FloatNetSharedVector.Iterator | |
| FloatNeuronLayer |
\brief An interface for layers that take one blob as input (
x )
and produce one equally-sized blob as output (y ), where
each element of the output depends only on the corresponding input
element. |
| FloatParameterLayer | |
| FloatPoolingLayer |
\brief Pools the input image by taking the max, average, etc.
|
| FloatPositiveUnitballFiller |
\brief Fills a Blob with values
x \in [0, 1]
such that \forall i \sum_j x_{ij} = 1 . |
| FloatPowerLayer |
\brief Computes
y = (\alpha x + \beta) ^ \gamma ,
as specified by the scale \alpha , shift \beta ,
and power \gamma . |
| FloatPReLULayer |
\brief Parameterized Rectified Linear Unit non-linearity
y_i = \max(0, x_i) + a_i \min(0, x_i)
. |
| FloatRecurrentLayer |
\brief An abstract class for implementing recurrent behavior inside of an
unrolled network.
|
| FloatReductionLayer |
\brief Compute "reductions" -- operations that return a scalar output Blob
for an input Blob of arbitrary size, such as the sum, absolute sum,
and sum of squares.
|
| FloatRegistry | |
| FloatRegistry.Iterator | |
| FloatReLULayer |
\brief Rectified Linear Unit non-linearity
y = \max(0, x) . |
| FloatReshapeLayer | |
| FloatRMSPropSolver | |
| FloatRNNLayer |
\brief Processes time-varying inputs using a simple recurrent neural network
(RNN).
|
| FloatSGDSolver |
\brief Optimizes the parameters of a Net using
stochastic gradient descent (SGD) with momentum.
|
| FloatSigmoidCrossEntropyLossLayer |
\brief Computes the cross-entropy (logistic) loss
E = \frac{-1}{n} \sum\limits_{n=1}^N \left[
p_n \log \hat{p}_n +
(1 - p_n) \log(1 - \hat{p}_n)
\right]
, often used for predicting targets interpreted as probabilities. |
| FloatSigmoidLayer |
\brief Sigmoid function non-linearity
y = (1 + \exp(-x))^{-1}
, a classic choice in neural networks. |
| FloatSilenceLayer |
\brief Ignores bottom blobs while producing no top blobs.
|
| FloatSliceLayer |
\brief Takes a Blob and slices it along either the num or channel dimension,
outputting multiple sliced Blob results.
|
| FloatSoftmaxLayer |
\brief Computes the softmax function.
|
| FloatSoftmaxWithLossLayer |
\brief Computes the multinomial logistic loss for a one-of-many
classification task, passing real-valued predictions through a
softmax to get a probability distribution over classes.
|
| FloatSolver |
\brief An interface for classes that perform optimization on Net%s.
|
| FloatSolver.Callback | |
| FloatSolverRegisterer | |
| FloatSolverRegisterer.Creator_SolverParameter | |
| FloatSolverRegistry | |
| FloatSolverRegistry.Creator | |
| FloatSplitLayer |
\brief Creates a "split" path in the network by copying the bottom Blob
into multiple top Blob%s to be used by multiple consuming layers.
|
| FloatSPPLayer |
\brief Does spatial pyramid pooling on the input image
by taking the max, average, etc.
|
| FloatTanHLayer |
\brief TanH hyperbolic tangent non-linearity
y = \frac{\exp(2x) - 1}{\exp(2x) + 1}
, popular in auto-encoders. |
| FloatThresholdLayer |
\brief Tests whether the input exceeds a threshold: outputs 1 for inputs
above threshold; 0 otherwise.
|
| FloatTileLayer |
\brief Copy a Blob along specified dimensions.
|
| FloatUniformFiller |
\brief Fills a Blob with uniformly distributed values
x\sim U(a, b) . |
| FloatWindowDataLayer |
\brief Provides data to the Net from windows of images files, specified
by a window data file.
|
| FloatXavierFiller |
\brief Fills a Blob with values
x \sim U(-a, +a) where a is
set inversely proportional to number of incoming nodes, outgoing
nodes, or their average. |
| Func | |
| GeneratedMessageReflection | |
| HDF5DataParameter | |
| HDF5OutputParameter | |
| HingeLossParameter | |
| ImageDataParameter | |
| InfogainLossParameter | |
| InnerProductParameter | |
| InputParameter | |
| InternalThread |
Virtual class encapsulate boost::thread for use in base class
The child class will acquire the ability to run a single thread,
by reimplementing the virtual function InternalThreadEntry.
|
| LayerParameter | |
| LazyDescriptor | |
| LazyField | |
| LevelDB | |
| LevelDBCursor | |
| LevelDBTransaction | |
| LMDB | |
| LMDBCursor | |
| LMDBTransaction | |
| LogParameter | |
| LongLongPair | |
| LossParameter | |
| LRNParameter | |
| MapFieldBase | |
| MapFieldPrinterHelper | |
| MapFieldReflectionTest | |
| MapIterator | |
| MapKey | |
| MapKeySorter | |
| MapReflectionFriend | |
| MapReflectionTester | |
| MapValueRef | |
| MemoryDataParameter | |
| Message | |
| MessageFactory | |
| MessageLite | |
| MessageOptions | |
| Metadata | |
| MethodDescriptor | |
| MethodDescriptorProto | |
| MethodOptions | |
| MVNParameter | |
| NetParameter | |
| NetState | |
| NetStateRule | |
| OneofDescriptor | |
| OneofDescriptorProto | |
| OneofOptions | |
| ParameterParameter | |
| ParamSpec | |
| ParseTable | |
| ParseTableField | |
| PoolingParameter | |
| PowerParameter | |
| PReLUParameter | |
| Printer | |
| PythonParameter | |
| RecurrentParameter | |
| ReductionParameter | |
| Reflection | |
| ReflectionAccessor | |
| ReflectionOps | |
| ReLUParameter | |
| RepeatedFieldAccessor | |
| RepeatedPtrFieldBase | |
| ReshapeParameter | |
| ScaleParameter | |
| ServiceDescriptor | |
| ServiceDescriptorProto | |
| ServiceOptions | |
| SigmoidParameter | |
| SliceParameter | |
| SoftmaxParameter | |
| SolverParameter | |
| SolverState | |
| SourceCodeInfo | |
| SourceLocation | |
| SPPParameter | |
| StringIntMap | |
| StringIntMap.Iterator | |
| StringPiece | |
| StringVector | |
| StringVector.Iterator | |
| Symbol | |
| SyncedMemory |
\brief Manages memory allocation and synchronization between the host (CPU)
and device (GPU).
|
| TanHParameter | |
| thread |
Forward declare boost::thread instead of including boost/thread.hpp
to avoid a boost/NVCC issues (#1009, #1010) on OSX.
|
| ThresholdParameter | |
| TileParameter | |
| Timer | |
| Transaction | |
| TransformationParameter | |
| UninterpretedOption | |
| UnknownField | |
| UnknownFieldSet | |
| V0LayerParameter | |
| V1LayerParameter | |
| WeakFieldMap | |
| WindowDataParameter | |
| WireFormat | |
| WireFormatLite | |
| ZeroCopyInputStream | |
| ZeroCopyOutputStream |
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