MyCaffe.layers.beta Namespace Reference

The MyCaffe.layers.beta namespace contains all beta stage layers. More...

Classes
class	AccuracyDecodeLayer
	The AccuracyDecodeLayer compares the labels output by the DecodeLayer with the expected labels output by the DataLayer. This layer is initialized with the MyCaffe.param.AccuracyParameter. More...
class	AccuracyEncodingLayer
	The AccuracyEncodingLayer computes the classification accuracy for an encoding used in a classification task that uses a Siamese Network or similar type of net that creates an encoding mapped to a label. This layer is initialized with the MyCaffe.param.AccuracyParameter. More...
class	ConvolutionOctaveLayer
	The ConvolutionOctaveLayer processes high and low frequency portions of images using convolution. More...
class	DataSequenceLayer
	DataSequence Layer - this caches inputs by label and then outputs data item tuplets that include an 'anchor', optionally a 'positive' match, and at least one 'negative' match. More...
class	DecodeLayer
	The DecodeLayer decodes the label of a classification for an encoding produced by a Siamese Network or similar type of net that creates an encoding mapped to a set of distances where the smallest distance indicates the label for which the encoding belongs. More...
class	GatherLayer
	The GatherLayer extracts (gathers) data from specified indices along a given axis from the input and returns it as the output. The indices are passed in as the second bottom blob. More...
class	GlobResNormLayer
	The GRNLayer performs an L2 normalization over the input data. More...
class	InterpLayer
	The InterpLayer changes the spatial resolution by bi-linear interpolation. More...
class	KnnLayer
class	LayerFactory
	The LayerFactor is responsible for creating all layers implemented in the MyCaffe.layers.ssd namespace. More...
class	MeanErrorLossLayer
	The MeanErrorLossLayer computes losses based on various different Mean Error methods as shown below. This layer is used to solve regression problems such as time-series predictions. More...
class	MergeLayer
	The MergeLayer merges two bottom blobs with a specified copy pattern and outputs a single blob result. More...
class	MishLayer
	The MishLayer provides a novel activation function that tends to work better than ReLU. This layer is initialized with the MyCaffe.param.MishParameter. More...
class	ModelDataLayer
	The ModelDataLayer loads data from RawImageResults table for an encoder/decoder type model. More...
class	Normalization1Layer
	The Normalization1Layer performs an L2 normalization over the input data. This layer is initialized with the MyCaffe.param.Normalization1Parameter. More...
class	SerfLayer
	The SerfLayer provides a novel activation function that tends to work better than ReLU. More...
class	SqueezeLayer
	The SqueezeLayer performs a squeeze operation where all single dimensions are removed. More...
class	TextDataLayer
	The TextDataLayer loads data from text data files for an encoder/decoder type model. This layer is initialized with the MyCaffe.param.TextDataParameter. More...
class	TransposeLayer
	The TransposeLayer performs a permute and transpose operation similar to numpy.transpose. More...
class	TripletLossLayer
	TripletLoss Layer - this is the triplet loss layer used to calculate the triplet loss and gradients using the triplet loss method of learning. The triplet loss method involves image triplets using the following format: Anchor (A), Positives (P) and Negatives (N) More...
class	UnPoolingLayer
class	UnPoolingLayer1
class	UnsqueezeLayer
	The UnsqueezeLayer performs an unsqueeze operation where a single dimension is inserted at each index specified. More...

Detailed Description

The MyCaffe.layers.beta namespace contains all beta stage layers.