averagePooling3dLayer

3-D average pooling layer

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Description

A 3-D average pooling layer performs downsampling by dividing three-dimensional input into cuboidal pooling regions, then computing the average values of each region.

The dimensions that the layer pools over depends on the layer input:

  • For 3-D image input (data with five dimensions corresponding to pixels in three spatial dimensions, the channels, and the observations), the layer pools over the spatial dimensions.

  • For 3-D image sequence input (data with six dimensions corresponding to the pixels in three spatial dimensions, the channels, the observations, and the time steps), the layer pools over the spatial dimensions.

  • For 2-D image sequence input (data with five dimensions corresponding to the pixels in two spatial dimensions, the channels, the observations, and the time steps), the layer pools over the spatial and time dimensions.

Creation

Syntax

layer = averagePooling3dLayer(poolSize)
layer = averagePooling3dLayer(poolSize,Name=Value)

Description

layer = averagePooling3dLayer(poolSize) creates an average pooling layer and sets the PoolSize property.

layer = averagePooling3dLayer(poolSize,Name=Value) sets the optional Stride and Name properties using name-value arguments. To specify input padding, use the Padding name-value argument. For example, averagePooling3dLayer(2,Stride=2) creates a 3-D average pooling layer with pool size [2 2 2] and stride [2 2 2]. You can specify multiple name-value arguments.

example

Name-Value Arguments

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Specify optional pairs of arguments as Name1=Value1,...,NameN=ValueN, where Name is the argument name and Value is the corresponding value. Name-value arguments must appear after other arguments, but the order of the pairs does not matter.

Before R2021a, use commas to separate each name and value, and enclose Name in quotes.

Example: averagePooling3dLayer(2,Stride=2) creates a 3-D average pooling layer with pool size [2 2 2] and stride [2 2 2].

Input edge padding, specified as one of these values:

  • "same" — Add padding of size calculated by the software at training or prediction time so that the output has the same size as the input when the stride equals 1. If the stride is larger than 1, then the output size is ceil(inputSize/stride), where inputSize is the height, width, or depth of the input and stride is the stride in the corresponding dimension. The software adds the same amount of padding to the top and bottom, to the left and right, and to the front and back, if possible. If the padding in a given dimension has an odd value, then the software adds the extra padding to the input as postpadding. In other words, the software adds extra vertical padding to the bottom, extra horizontal padding to the right, and extra depth padding to the back of the input.

  • Nonnegative integer p — Add padding of size p to all the edges of the input.

  • Three-element vector [a b c] of nonnegative integers — Add padding of size a to the top and bottom, padding of size b to the left and right, and padding of size c to the front and back of the input.

  • 2-by-3 matrix [t l f;b r k] of nonnegative integers — Add padding of size t to the top, b to the bottom, l to the left, r to the right, f to the front, and k to the back of the input. In other words, the top row specifies the prepadding and the second row defines the postpadding in the three dimensions.

Example: Padding=1 adds one row of padding to the top and bottom, one column of padding to the left and right, and one plane of padding to the front and back of the input.

Example: Padding="same" adds padding so that the output has the same size as the input (if the stride equals 1).

Properties

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Average Pooling

Dimensions of the pooling regions, specified as a vector of three positive integers [h w d], where h is the height, w is the width, and d is the depth. When creating the layer, you can specify PoolSize as a scalar to use the same value for all three dimensions.

If the stride dimensions Stride are less than the respective pooling dimensions, then the pooling regions overlap.

The padding dimensions PaddingSize must be less than the pooling region dimensions PoolSize.

Example: [2 1 1] specifies pooling regions of height 2, width 1, and depth 1.

Step size for traversing the input in three dimensions, specified as a vector [a b c] of three positive integers, where a is the vertical step size, b is the horizontal step size, and c is the step size along the depth direction. When creating the layer, you can specify Stride as a scalar to use the same value for step sizes in all three directions.

If the stride dimensions Stride are less than the respective pooling dimensions, then the pooling regions overlap.

The padding dimensions PaddingSize must be less than the pooling region dimensions PoolSize.

Example: [2 3 1] specifies a vertical step size of 2, a horizontal step size of 3, and a step size along the depth of 1.

Size of padding to apply to input borders, specified as 2-by-3 matrix [t l f;b r k] of nonnegative integers, where t and b are the padding applied to the top and bottom in the vertical direction, l and r are the padding applied to the left and right in the horizontal direction, and f and k are the padding applied to the front and back along the depth. In other words, the top row specifies the prepadding and the second row defines the postpadding in the three dimensions.

When you create a layer, use the Padding name-value argument to specify the padding size.

Example: [1 2 4; 1 2 4] adds one row of padding to the top and bottom, two columns of padding to the left and right, and four planes of padding to the front and back of the input.

Method to determine padding size, specified as "manual" or "same".

The software automatically sets the value of PaddingMode based on the Padding argument value you specify when creating a layer.

  • If you set the Padding argument to a scalar or a vector of nonnegative integers, then the software automatically sets PaddingMode to "manual".

  • If you set the Padding argument to "same", then the software automatically sets PaddingMode to "same" and calculates the size of the padding at training time so that the output has the same size as the input when the stride equals 1. If the stride is larger than 1, then the output size is ceil(inputSize/stride), where inputSize is the height, width, or depth of the input and stride is the stride in the corresponding dimension. The software adds the same amount of padding to the top and bottom, to the left and right, and to the front and back, if possible. If the padding in a given dimension has an odd value, then the software adds the extra padding to the input as postpadding. In other words, the software adds extra vertical padding to the bottom, extra horizontal padding to the right, and extra depth padding to the back of the input.

The AveragePooling3DLayer object stores this property as a character vector.

Value used to pad input, specified as 0 or "mean".

When you use the Padding option to add padding to the input, the value of the padding applied can be one of the following:

  • 0 — Input is padded with zeros at the positions specified by the Padding property. The padded areas are included in the calculation of the average value of the pooling regions along the edges.

  • "mean" — Input is padded with the mean of the pooling region at the positions specified by the Padding option. The padded areas are effectively excluded from the calculation of the average value of each pooling region.

Layer

Layer name, specified as a character vector or a string scalar. For Layer array input, the trainnet and dlnetwork functions automatically assign names to unnamed layers.

The AveragePooling3DLayer object stores this property as a character vector.

Data Types: char | string

This property is read-only.

Number of inputs to the layer, stored as 1. This layer accepts a single input only.

Data Types: double

This property is read-only.

Input names, stored as {'in'}. This layer accepts a single input only.

Data Types: cell

This property is read-only.

Number of outputs from the layer, stored as 1. This layer has a single output only.

Data Types: double

This property is read-only.

Output names, stored as {'out'}. This layer has a single output only.

Data Types: cell

Examples

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Open Live Script

Create a 3-D average pooling layer with nonoverlapping pooling regions that downsamples by a factor of 2.

layer = averagePooling3dLayer(2,Stride=2)
layer = 
  AveragePooling3DLayer with properties:

            Name: ''

   Hyperparameters
        PoolSize: [2 2 2]
          Stride: [2 2 2]
     PaddingMode: 'manual'
     PaddingSize: [2×3 double]
    PaddingValue: 0

Include a 3-D average pooling layer in a Layer array.

layers = [ ...
    image3dInputLayer([28 28 28 3])
    convolution3dLayer(5,20)
    reluLayer
    averagePooling3dLayer(2,Stride=2)
    fullyConnectedLayer(10)
    softmaxLayer]
layers = 
  6×1 Layer array with layers:

     1   ''   3-D Image Input       28×28×28×3 images with 'zerocenter' normalization
     2   ''   3-D Convolution       20 5×5×5 convolutions with stride [1  1  1] and padding [0  0  0; 0  0  0]
     3   ''   ReLU                  ReLU
     4   ''   3-D Average Pooling   2×2×2 average pooling with stride [2  2  2] and padding [0  0  0; 0  0  0]
     5   ''   Fully Connected       10 fully connected layer
     6   ''   Softmax               softmax
Open Live Script

Create a 3-D average pooling layer with overlapping pooling regions and padding for the top and bottom of the input.

layer = averagePooling3dLayer([3 2 2],Stride=2,Padding=[1 0 0])
layer = 
  AveragePooling3DLayer with properties:

            Name: ''

   Hyperparameters
        PoolSize: [3 2 2]
          Stride: [2 2 2]
     PaddingMode: 'manual'
     PaddingSize: [2×3 double]
    PaddingValue: 0

This layer creates pooling regions of size 3-by-2-by-2 and takes the average of the twelve elements in each region. The stride is 2 in all dimensions. The pooling regions overlap because there are stride dimensions Stride that are less than the respective pooling dimensions PoolSize.

Algorithms

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Version History

Introduced in R2019a

See Also

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Topics