API Reference - PoolingLayers
Constructors
FastAveragePooling1D
PoolingLayers.FastAveragePooling1D{tensor: tensor, kernelDimensionSize: number, strideDimensionSize: number}: AutomaticDifferentiationTensor
Parameters:
-
tensor: The tensor that will be used as inputs.
-
kernelDimensionSize: The dimension size for the kernel. [Default: 2]
-
strideDimensionSize: The dimension size for the stride. [Default: 1]
Returns:
- AutomaticDifferentiationTensor: The automatic differentiation tensor that is created as a result of calling this function.
FastAveragePooling2D
PoolingLayers.FastAveragePooling2D{tensor: tensor, kernelDimensionSize: {number}, strideDimensionSizeArray: {number}}: AutomaticDifferentiationTensor
Parameters:
-
tensor: The tensor that will be used as inputs.
-
kernelDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {2, 2}]
-
strideDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {1, 1}]
Returns:
- AutomaticDifferentiationTensor: The automatic differentiation tensor that is created as a result of calling this function.
FastAveragePooling3D
PoolingLayers.FastAveragePooling3D{tensor: tensor, kernelDimensionSizeArray: {number}, strideDimensionSizeArray: {number}}: AutomaticDifferentiationTensor
Parameters:
-
tensor: The tensor that will be used as inputs.
-
kernelDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {2, 2, 2}]
-
strideDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {1, 1, 1}]
Returns:
- AutomaticDifferentiationTensor: The automatic differentiation tensor that is created as a result of calling this function.
FastMaximumPooling1D
PoolingLayers.FastMaximumPooling1D{tensor: tensor, kernelDimensionSize: number, strideDimensionSize: number}: AutomaticDifferentiationTensor
Parameters:
-
tensor: The tensor that will be used as inputs.
-
kernelDimensionSize: The dimension size for the kernel. [Default: 2]
-
strideDimensionSize: The dimension size for the stride. [Default: 1]
Returns:
- AutomaticDifferentiationTensor: The automatic differentiation tensor that is created as a result of calling this function.
FastMaximumPooling2D
PoolingLayers.FastMaximumPooling2D{tensor: tensor, kernelDimensionSize: {number}, strideDimensionSizeArray: {number}}: AutomaticDifferentiationTensor
Parameters:
-
tensor: The tensor that will be used as inputs.
-
kernelDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {2, 2}]
-
strideDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {1, 1}]
Returns:
- AutomaticDifferentiationTensor: The automatic differentiation tensor that is created as a result of calling this function.
FastMaximumPooling3D
PoolingLayers.FastMaximumPooling3D{tensor: tensor, kernelDimensionSizeArray: {number}, strideDimensionSizeArray: {number}}: AutomaticDifferentiationTensor
Parameters:
-
tensor: The tensor that will be used as inputs.
-
kernelDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {2, 2, 2}]
-
strideDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {1, 1, 1}]
Returns:
- AutomaticDifferentiationTensor: The automatic differentiation tensor that is created as a result of calling this function.
FastMinimumPooling1D
PoolingLayers.FastMinimumPooling1D{tensor: tensor, kernelDimensionSize: number, strideDimensionSize: number}: AutomaticDifferentiationTensor
Parameters:
-
tensor: The tensor that will be used as inputs.
-
kernelDimensionSize: The dimension size for the kernel. [Default: 2]
-
strideDimensionSize: The dimension size for the stride. [Default: 1]
Returns:
- AutomaticDifferentiationTensor: The automatic differentiation tensor that is created as a result of calling this function.
FastMinimumPooling2D
PoolingLayers.FastMinimumPooling2D{tensor: tensor, kernelDimensionSize: {number}, strideDimensionSizeArray: {number}}: AutomaticDifferentiationTensor
Parameters:
-
tensor: The tensor that will be used as inputs.
-
kernelDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {2, 2}]
-
strideDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {1, 1}]
Returns:
- AutomaticDifferentiationTensor: The automatic differentiation tensor that is created as a result of calling this function.
FastMinimumPooling3D
PoolingLayers.FastMinimumPooling3D{tensor: tensor, kernelDimensionSizeArray: {number}, strideDimensionSizeArray: {number}}: AutomaticDifferentiationTensor
Parameters:
-
tensor: The tensor that will be used as inputs.
-
kernelDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {2, 2, 2}]
-
strideDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {1, 1, 1}]
Returns:
- AutomaticDifferentiationTensor: The automatic differentiation tensor that is created as a result of calling this function.
FastMaximumUnpoolingPooling1D
PoolingLayers.FastMaximumUnpoolingPooling1D{tensor: tensor, kernelDimensionSize: number, strideDimensionSize: number, unpoolingMethod: string}: AutomaticDifferentiationTensor
Parameters:
-
tensor: The tensor that will be used as inputs.
-
kernelDimensionSize: The dimension size for the kernel. [Default: 2]
-
strideDimensionSize: The dimension size for the stride. [Default: 1]
-
unpoolingMethod: The unpooling method that determines how the transformed tensor is generated. Available options are:
-
NearestNeighbour (Default)
-
BedOfNails
-
Returns:
- AutomaticDifferentiationTensor: The automatic differentiation tensor that is created as a result of calling this function.
FastMaximumUnpoolingPooling2D
PoolingLayers.FastMaximumUnpoolingPooling2D{tensor: tensor, kernelDimensionSize: {number}, strideDimensionSizeArray: {number}: unpoolingMethod: string}: AutomaticDifferentiationTensor
Parameters:
-
tensor: The tensor that will be used as inputs.
-
kernelDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {2, 2}]
-
strideDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {1, 1}]
-
unpoolingMethod: The unpooling method that determines how the transformed tensor is generated. Available options are:
-
NearestNeighbour (Default)
-
BedOfNails
-
Returns:
- AutomaticDifferentiationTensor: The automatic differentiation tensor that is created as a result of calling this function.
FastMaximumUnpoolingPooling3D
PoolingLayers.FastMaximumUnpoolingPooling3D{tensor: tensor, kernelDimensionSizeArray: {number}, strideDimensionSizeArray: {number}, unpoolingMethod: string}: AutomaticDifferentiationTensor
Parameters:
-
tensor: The tensor that will be used as inputs.
-
kernelDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {2, 2, 2}]
-
strideDimensionSizeArray: The dimension size for the stride. The index of the array represents the dimension and the value represents the size for that particular dimension. [Default: {1, 1, 1}]
-
unpoolingMethod: The unpooling method that determines how the transformed tensor is generated. Available options are:
-
NearestNeighbour (Default)
-
BedOfNails
-
Returns:
- AutomaticDifferentiationTensor: The automatic differentiation tensor that is created as a result of calling this function.