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.
Dropout
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A dropout layer.
Dropout consists in randomly setting a fraction of input units to 0
at each update during
training time, which helps prevent overfitting.
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-
Declaration
@noDerivative
public let probability: Double
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Creates a dropout layer.
Precondition
probability must be a value between 0 and 1 (inclusive).
Declaration
public init(probability: Double)
Parameters
probability
|
The probability of a node dropping out.
|
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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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Last updated 2021-09-28 UTC.
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