@Name(value="caffe::ConvolutionLayer<double>") @Properties(inherit=caffe.class) public class DoubleConvolutionLayer extends DoubleBaseConvolutionLayer
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator, Pointer.ReferenceCounter| Constructor and Description |
|---|
DoubleConvolutionLayer(LayerParameter param) |
DoubleConvolutionLayer(Pointer p)
Pointer cast constructor.
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| Modifier and Type | Method and Description |
|---|---|
protected void |
Backward_cpu(DoubleBlobVector top,
BoolVector propagate_down,
DoubleBlobVector bottom) |
protected void |
Backward_gpu(DoubleBlobVector top,
BoolVector propagate_down,
DoubleBlobVector bottom) |
protected void |
compute_output_shape() |
protected void |
Forward_cpu(DoubleBlobVector bottom,
DoubleBlobVector top) |
protected void |
Forward_gpu(DoubleBlobVector bottom,
DoubleBlobVector top) |
protected boolean |
reverse_dimensions() |
BytePointer |
type()
\brief Returns the layer type.
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EqualNumBottomTopBlobs, LayerSetUp, MinBottomBlobs, MinTopBlobs, ReshapeAllowForceBackward, AutoTopBlobs, Backward, blobs, CheckBlobCounts, ExactNumBottomBlobs, ExactNumTopBlobs, Forward, layer_param, loss, MaxBottomBlobs, MaxTopBlobs, param_propagate_down, set_loss, set_param_propagate_down, SetUp, ToProtoaddress, asBuffer, asByteBuffer, availablePhysicalBytes, calloc, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, formatBytes, free, getPointer, getPointer, getPointer, getPointer, hashCode, isNull, isNull, limit, limit, malloc, maxBytes, maxPhysicalBytes, memchr, memcmp, memcpy, memmove, memset, offsetAddress, offsetof, offsetof, parseBytes, physicalBytes, position, position, put, realloc, referenceCount, releaseReference, retainReference, setNull, sizeof, sizeof, toString, totalBytes, totalCount, totalPhysicalBytes, withDeallocator, zeropublic DoubleConvolutionLayer(Pointer p)
Pointer(Pointer).public DoubleConvolutionLayer(@Const @ByRef LayerParameter param)
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.@Virtual @Const(value={false,false,true}) @Cast(value="const char*") public BytePointer type()
DoubleLayertype in class DoubleLayer@Virtual protected void Forward_cpu(@Const @ByRef DoubleBlobVector bottom, @Const @ByRef DoubleBlobVector top)
Forward_cpu in class DoubleLayer@Virtual protected void Forward_gpu(@Const @ByRef DoubleBlobVector bottom, @Const @ByRef DoubleBlobVector top)
Forward_gpu in class DoubleLayer@Virtual protected void Backward_cpu(@Const @ByRef DoubleBlobVector top, @Const @ByRef BoolVector propagate_down, @Const @ByRef DoubleBlobVector bottom)
Backward_cpu in class DoubleLayer@Virtual protected void Backward_gpu(@Const @ByRef DoubleBlobVector top, @Const @ByRef BoolVector propagate_down, @Const @ByRef DoubleBlobVector bottom)
Backward_gpu in class DoubleLayer@Virtual @Cast(value="bool") protected boolean reverse_dimensions()
reverse_dimensions in class DoubleBaseConvolutionLayer@Virtual protected void compute_output_shape()
compute_output_shape in class DoubleBaseConvolutionLayerCopyright © 2021. All rights reserved.