org.bytedeco.caffe

Class FloatConvolutionLayer

java.lang.Object

org.bytedeco.javacpp.Pointer

org.bytedeco.caffe.FloatLayer

org.bytedeco.caffe.FloatBaseConvolutionLayer

org.bytedeco.caffe.FloatConvolutionLayer

All Implemented Interfaces:

AutoCloseable

Direct Known Subclasses:

FloatCuDNNConvolutionLayer

@Name(value="caffe::ConvolutionLayer<float>")
 @Properties(inherit=caffe.class)
public class FloatConvolutionLayer
extends FloatBaseConvolutionLayer

\brief Convolves the input image with a bank of learned filters, and (optionally) adds biases. Caffe convolves by reduction to matrix multiplication. This achieves high-throughput and generality of input and filter dimensions but comes at the cost of memory for matrices. This makes use of efficiency in BLAS. The input is "im2col" transformed to a channel K' x H x W data matrix for multiplication with the N x K' x H x W filter matrix to yield a N' x H x W output matrix that is then "col2im" restored. K' is the input channel * kernel height * kernel width dimension of the unrolled inputs so that the im2col matrix has a column for each input region to be filtered. col2im restores the output spatial structure by rolling up the output channel N' columns of the output matrix.

Nested Class Summary

Nested classes/interfaces inherited from class org.bytedeco.javacpp.Pointer

Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter

Field Summary

Fields inherited from class org.bytedeco.javacpp.Pointer

address, capacity, limit, position

Constructor Summary

Constructors

Constructor and Description
FloatConvolutionLayer(LayerParameter param)
FloatConvolutionLayer(Pointer p) Pointer cast constructor.

Method Summary

Modifier and Type	Method and Description
protected void	Backward_cpu(FloatBlobVector top, BoolVector propagate_down, FloatBlobVector bottom)
protected void	Backward_gpu(FloatBlobVector top, BoolVector propagate_down, FloatBlobVector bottom)
protected void	compute_output_shape()
protected void	Forward_cpu(FloatBlobVector bottom, FloatBlobVector top)
protected void	Forward_gpu(FloatBlobVector bottom, FloatBlobVector top)
protected boolean	reverse_dimensions()
BytePointer	type() \brief Returns the layer type.

Methods inherited from class org.bytedeco.caffe.FloatBaseConvolutionLayer

EqualNumBottomTopBlobs, LayerSetUp, MinBottomBlobs, MinTopBlobs, Reshape

Methods inherited from class org.bytedeco.caffe.FloatLayer

AllowForceBackward, AutoTopBlobs, Backward, blobs, CheckBlobCounts, ExactNumBottomBlobs, ExactNumTopBlobs, Forward, layer_param, loss, MaxBottomBlobs, MaxTopBlobs, param_propagate_down, set_loss, set_param_propagate_down, SetUp, ToProto

Methods inherited from class org.bytedeco.javacpp.Pointer

address, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, hashCode, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, parseBytes, physicalBytes, position, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, toString, totalBytes, totalPhysicalBytes, withDeallocator, zero

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

FloatConvolutionLayer

public FloatConvolutionLayer(Pointer p)

Pointer cast constructor. Invokes Pointer.Pointer(Pointer).

FloatConvolutionLayer

public FloatConvolutionLayer(@Const @ByRef
                             LayerParameter param)

Parameters:

param - provides ConvolutionParameter convolution_param, with ConvolutionLayer options: - num_output. The number of filters. - kernel_size / kernel_h / kernel_w. The filter dimensions, given by kernel_size for square filters or kernel_h and kernel_w for rectangular filters. - stride / stride_h / stride_w (\b optional, default 1). The filter stride, given by stride_size for equal dimensions or stride_h and stride_w for different strides. By default the convolution is dense with stride 1. - pad / pad_h / pad_w (\b optional, default 0). The zero-padding for convolution, given by pad for equal dimensions or pad_h and pad_w for different padding. Input padding is computed implicitly instead of actually padding. - dilation (\b optional, default 1). The filter dilation, given by dilation_size for equal dimensions for different dilation. By default the convolution has dilation 1. - group (\b optional, default 1). The number of filter groups. Group convolution is a method for reducing parameterization by selectively connecting input and output channels. The input and output channel dimensions must be divisible by the number of groups. For group \geq 1 , the convolutional filters' input and output channels are separated s.t. each group takes 1 / group of the input channels and makes 1 / group of the output channels. Concretely 4 input channels, 8 output channels, and 2 groups separate input channels 1-2 and output channels 1-4 into the first group and input channels 3-4 and output channels 5-8 into the second group. - bias_term (\b optional, default true). Whether to have a bias. - engine: convolution has CAFFE (matrix multiplication) and CUDNN (library kernels + stream parallelism) engines.

Method Detail

type

@Virtual
 @Const(value={false,false,true})
 @Cast(value="const char*")
public BytePointer type()

Description copied from class: FloatLayer

\brief Returns the layer type.

Overrides:

type in class FloatLayer

Forward_cpu

@Virtual
protected void Forward_cpu(@Const @ByRef
                                    FloatBlobVector bottom,
                                    @Const @ByRef
                                    FloatBlobVector top)

Overrides:

Forward_cpu in class FloatLayer

Forward_gpu

@Virtual
protected void Forward_gpu(@Const @ByRef
                                    FloatBlobVector bottom,
                                    @Const @ByRef
                                    FloatBlobVector top)

Overrides:

Forward_gpu in class FloatLayer

Backward_cpu

@Virtual
protected void Backward_cpu(@Const @ByRef
                                     FloatBlobVector top,
                                     @Const @ByRef
                                     BoolVector propagate_down,
                                     @Const @ByRef
                                     FloatBlobVector bottom)

Overrides:

Backward_cpu in class FloatLayer

Backward_gpu

@Virtual
protected void Backward_gpu(@Const @ByRef
                                     FloatBlobVector top,
                                     @Const @ByRef
                                     BoolVector propagate_down,
                                     @Const @ByRef
                                     FloatBlobVector bottom)

Overrides:

Backward_gpu in class FloatLayer

reverse_dimensions

@Virtual
 @Cast(value="bool")
protected boolean reverse_dimensions()

Overrides:

reverse_dimensions in class FloatBaseConvolutionLayer

compute_output_shape

@Virtual
protected void compute_output_shape()

Overrides:

compute_output_shape in class FloatBaseConvolutionLayer