Package ai.djl.nn.convolutional

Class Conv3d

java.lang.Object

ai.djl.nn.AbstractBaseBlock

ai.djl.nn.AbstractBlock

ai.djl.nn.convolutional.Convolution

ai.djl.nn.convolutional.Conv3d

All Implemented Interfaces:

Block

public class Conv3d
extends Convolution

Conv3d layer behaves just as Convolution does, with the distinction being it operates of 3-dimensional data such as medical images or video data. The traversal of each filter begins from LayoutType.WIDTH then to LayoutType.HEIGHT, and lastly across each LayoutType.DEPTH in the specified depth size of the data.

The utilization of Conv3d layer allows deeper analysis of visual data such as those in medical images, or even analysis on temporal data such as video data as a whole instead of processing each frame with a Conv2d layer, despite this being a common practice in computer vision researches. The benefit of utilizing this kind of layer is the maintaining of serial data across 2-dimensional data, hence could be beneficial for research focus on such as object tracking. The drawback is that this kind of layer is more costly compared to other convolution layer types since dot product operation is performed on all three dimensions.

The input to a Conv3d is an NDList with a single 5-D NDArray. The layout of the NDArray must be "NCDHW". The shapes are

• data: (batch_size, channel, depth, height, width)
• weight: (num_filter, channel, kernel[0], kernel[1], kernel[2])
• bias: (num_filter,)
• out: (batch_size, num_filter, out_depth, out_height, out_width)
out_depth = f(depth, kernel[0], pad[0], stride[0], dilate[0])
out_height = f(height, kernel[1], pad[1], stride[1], dilate[1])
out_width = f(width, kernel[2], pad[2], stride[2], dilate[2])
where f(x, k, p, s, d) = floor((x + 2 * p - d * (k - 1) - 1)/s) + 1

Both weight and bias are learn-able parameters.

See Also:

Convolution

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	Conv3d.Builder	The Builder to construct a Conv3d type of Block.

Nested classes/interfaces inherited from class ai.djl.nn.convolutional.Convolution

Convolution.ConvolutionBuilder<T extends Convolution.ConvolutionBuilder>

Field Summary

Fields inherited from class ai.djl.nn.convolutional.Convolution

bias, dilation, filters, groups, includeBias, kernelShape, padding, stride, weight

Fields inherited from class ai.djl.nn.AbstractBlock

children, parameters

Fields inherited from class ai.djl.nn.AbstractBaseBlock

inputNames, inputShapes, outputDataTypes, version

Method Summary

Modifier and Type	Method	Description
static Conv3d.Builder	builder()	Creates a builder to build a Conv3d.
static NDList	conv3d(NDArray input, NDArray weight)	Applies 3D convolution over an input signal composed of several input planes.
static NDList	conv3d(NDArray input, NDArray weight, NDArray bias)	Applies 3D convolution over an input signal composed of several input planes.
static NDList	conv3d(NDArray input, NDArray weight, NDArray bias, Shape stride)	Applies 3D convolution over an input signal composed of several input planes.
static NDList	conv3d(NDArray input, NDArray weight, NDArray bias, Shape stride, Shape padding)	Applies 3D convolution over an input signal composed of several input planes.
static NDList	conv3d(NDArray input, NDArray weight, NDArray bias, Shape stride, Shape padding, Shape dilation)	Applies 3D convolution over an input signal composed of several input planes.
static NDList	conv3d(NDArray input, NDArray weight, NDArray bias, Shape stride, Shape padding, Shape dilation, int groups)	Applies 3D convolution over an input signal composed of several input planes.
protected LayoutType[]	getExpectedLayout()	Returns the expected layout of the input.
protected java.lang.String	getStringLayout()	Returns the string representing the layout of the input.
protected int	numDimensions()	Returns the number of dimensions of the input.

Methods inherited from class ai.djl.nn.convolutional.Convolution

beforeInitialize, forwardInternal, getDilation, getFilters, getGroups, getKernelShape, getOutputShapes, getPadding, getStride, isIncludeBias, loadMetadata, prepare

Methods inherited from class ai.djl.nn.AbstractBlock

addChildBlock, addChildBlock, addChildBlockSingleton, addParameter, getChildren, getDirectParameters

Methods inherited from class ai.djl.nn.AbstractBaseBlock

cast, clear, describeInput, forward, forward, forwardInternal, getInputShapes, getOutputDataTypes, getParameters, initialize, initializeChildBlocks, isInitialized, loadParameters, readInputShapes, saveInputShapes, saveMetadata, saveParameters, setInitializer, setInitializer, setInitializer, toString

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface ai.djl.nn.Block

forward, freezeParameters, freezeParameters, getOutputShapes

Method Detail

getExpectedLayout

protected LayoutType[] getExpectedLayout()

Returns the expected layout of the input.

Specified by:

getExpectedLayout in class Convolution

Returns:

the expected layout of the input

getStringLayout

protected java.lang.String getStringLayout()

Returns the string representing the layout of the input.

Specified by:

getStringLayout in class Convolution

Returns:

the string representing the layout of the input

numDimensions

protected int numDimensions()

Returns the number of dimensions of the input.

Specified by:

numDimensions in class Convolution

Returns:

the number of dimensions of the input

conv3d

public static NDList conv3d(NDArray input,
                            NDArray weight)

Applies 3D convolution over an input signal composed of several input planes.

Parameters:

input - the input NDArray of shape (batchSize, inputChannel, depth, height, width)

weight - filters NDArray of shape (outChannel, inputChannel/groups, depth, height, width)

Returns:

the output of the conv3d operation

conv3d

public static NDList conv3d(NDArray input,
                            NDArray weight,
                            NDArray bias)

Applies 3D convolution over an input signal composed of several input planes.

Parameters:

input - the input NDArray of shape (batchSize, inputChannel, depth, height, width)

weight - filters NDArray of shape (outChannel, inputChannel/groups, depth, height, width)

bias - bias NDArray of shape (outChannel)

Returns:

the output of the conv3d operation

conv3d

public static NDList conv3d(NDArray input,
                            NDArray weight,
                            NDArray bias,
                            Shape stride)

Applies 3D convolution over an input signal composed of several input planes.

Parameters:

input - the input NDArray of shape (batchSize, inputChannel, depth, height, width)

weight - filters NDArray of shape (outChannel, inputChannel/groups, depth, height, width)

bias - bias NDArray of shape (outChannel)

stride - the stride of the convolving kernel: Shape(depth, height, width)

Returns:

the output of the conv3d operation

conv3d

public static NDList conv3d(NDArray input,
                            NDArray weight,
                            NDArray bias,
                            Shape stride,
                            Shape padding)

Applies 3D convolution over an input signal composed of several input planes.

Parameters:

input - the input NDArray of shape (batchSize, inputChannel, depth, height, width)

weight - filters NDArray of shape (outChannel, inputChannel/groups, depth, height, width)

bias - bias NDArray of shape (outChannel)

stride - the stride of the convolving kernel: Shape(depth, height, width)

padding - implicit paddings on both sides of the input: Shape(depth, height, width)

Returns:

the output of the conv3d operation

conv3d

public static NDList conv3d(NDArray input,
                            NDArray weight,
                            NDArray bias,
                            Shape stride,
                            Shape padding,
                            Shape dilation)

Applies 3D convolution over an input signal composed of several input planes.

Parameters:

input - the input NDArray of shape (batchSize, inputChannel, depth, height, width)

weight - filters NDArray of shape (outChannel, inputChannel/groups, depth, height, width)

bias - bias NDArray of shape (outChannel)

stride - the stride of the convolving kernel: Shape(depth, height, width)

padding - implicit paddings on both sides of the input: Shape(depth, height, width)

dilation - the spacing between kernel elements: Shape(depth, height, width)

Returns:

the output of the conv3d operation

conv3d

public static NDList conv3d(NDArray input,
                            NDArray weight,
                            NDArray bias,
                            Shape stride,
                            Shape padding,
                            Shape dilation,
                            int groups)

Applies 3D convolution over an input signal composed of several input planes.

Parameters:

input - the input NDArray of shape (batchSize, inputChannel, depth, height, width)

weight - filters NDArray of shape (outChannel, inputChannel/groups, depth, height, width)

bias - bias NDArray of shape (outChannel)

stride - the stride of the convolving kernel: Shape(depth, height, width)

padding - implicit paddings on both sides of the input: Shape(depth, height, width)

dilation - the spacing between kernel elements: Shape(depth, height, width)

groups - split input into groups: input channel(input.size(1)) should be divisible by the number of groups

Returns:

the output of the conv3d operation

builder

public static Conv3d.Builder builder()

Creates a builder to build a Conv3d.

Returns:

a new builder