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.
BasicRNNCell
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Declaration
public var weight: Tensor<Scalar>
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Declaration
public var bias: Tensor<Scalar>
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Declaration
public typealias State = Tensor<Scalar>
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Declaration
public typealias TimeStepInput = Tensor<Scalar>
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Declaration
public typealias TimeStepOutput = State
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Creates a SimpleRNNCell
with the specified input size and hidden state size.
Parameters
inputSize
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The number of features in 2-D input tensors.
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hiddenSize
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The number of features in 2-D hidden states.
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seed
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The random seed for initialization. The default value is random.
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Returns a zero-valued state with shape compatible with the provided input.
Declaration
public func zeroState(for input: Tensor<Scalar>) -> State
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Returns the output obtained from applying the layer to the given input.
Declaration
@differentiable
public func callAsFunction(_ input: Input) -> Output
Return Value
The hidden state.
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Last updated 2021-09-28 UTC.
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