Warning: This project is deprecated. Swift for TensorFlow was an experiment in the
next-generation platform for machine learning, incorporating the latest research across
machine learning, compilers, differentiable programming, systems design, and beyond. It was
archived in February 2021.
AvgPool2D
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An average pooling layer for spatial data.
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The size of the sliding reduction window for pooling.
Declaration
@noDerivative
public let poolSize: (Int, Int, Int, Int)
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The strides of the sliding window for each dimension of a 4-D input.
Strides in non-spatial dimensions must be 1
.
Declaration
@noDerivative
public let strides: (Int, Int, Int, Int)
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The padding algorithm for pooling.
Declaration
@noDerivative
public let padding: Padding
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Creates an average pooling layer.
Declaration
public init(poolSize: (Int, Int, Int, Int), strides: (Int, Int, Int, Int), padding: Padding)
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Returns the output obtained from applying the layer to the given input.
Declaration
@differentiable
public func forward(_ input: Tensor<Scalar>) -> Tensor<Scalar>
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Creates an average pooling layer.
Declaration
public init(poolSize: (Int, Int), strides: (Int, Int), padding: Padding = .valid)
Parameters
poolSize
|
Vertical and horizontal factors by which to downscale.
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strides
|
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padding
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Last updated 2021-09-28 UTC.
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