Structures

The following structures are available globally.

  • A pandas-inspired dataframe. Dataframe is a tabular data representation. This particular Dataframe implementation is most useful to implement data feeder pipeline. You need some transformations so some text or images can be transformed into tensors for a model to consume. Dataframe can be used to implement that pipeline.

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    Declaration

    Swift

    public struct DataFrame
  • Undocumented

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    Declaration

    Swift

    public struct DataSeriesIterator<S> : IteratorProtocol where S : DataSeries
  • Hint are parameters to these operations that changes shape from input to output. It given proper stride / padding parameters for these operations.

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    Declaration

    Swift

    public struct Hint
  • Softmax cross-entropy loss. This combines softmax with cross-entropy loss to maximize numerical stability.

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    Declaration

    Swift

    public struct SoftmaxCrossEntropyLoss : Loss
  • Sigmoid cross-entropy loss. This combines sigmoid with binary cross-entropy loss to maximize numerical stability.

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    Declaration

    Swift

    public struct SigmoidBinaryCrossEntropyLoss : Loss
  • Binary cross-entropy loss.

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    Declaration

    Swift

    public struct BinaryCrossEntropyLoss : Loss
  • Multi-class cross-entropy loss.

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    Declaration

    Swift

    public struct CategoricalCrossEntropyLoss : Loss
  • Smooth L1 loss (for object detection).

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    Declaration

    Swift

    public struct SmoothL1Loss : Loss
  • Stochastic gradient descent optimizer.

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    Declaration

    Swift

    public struct SGDOptimizer : Optimizer, OptimizerAddons
  • Adam optimizer.

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    Declaration

    Swift

    public struct AdamOptimizer : Optimizer, OptimizerAddons
  • Basic tensor type.

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    Declaration

    Swift

    public struct Tensor<Element> : AnyTensor where Element : TensorNumeric
    extension Tensor: CustomStringConvertible