Class

MPSRNNSingleGateDescriptor

A description of a simple recurrent block or layer.

Declaration

class MPSRNNSingleGateDescriptor : MPSRNNDescriptor

Overview

The recurrent neural network (RNN) layer initialized with a MPSRNNSingleGateDescriptor transforms the input data (image or matrix) and previous output with a set of filters. Each produces one feature map in the new output data.

You may provide the RNN unit with a single input or a sequence of inputs.

Description of Operation

  1. Let x_j be the input data (at time index t of sequence, j index containing quadruplet: batch index, x,y and feature index (x = y = 0 for matrices)).

  2. Let h0_j be the recurrent input (previous output) data from previous time step (at time index t-1 of sequence).

  3. Let h1_i be the output data produced at this time step.

  4. Let W_ij, U_ij be the weights for input and recurrent input data, respectively.

  5. Let b_i be a bias term.

  6. Let gi(x) be a neuron activation function.

The new output image h1_i data is computed as follows:

h1_i = gi( W_ij * x_j + U_ij * h0_j  + b_i )

The * stands for convolution (see MPSRNNImageInferenceLayer) or matrix-vector/matrix multiplication (see MPSRNNMatrixInferenceLayer).

Summation is over index j (except for the batch index), but there's no summation over repeated index i (the output index).

Note that for validity, all intermediate images must be of same size, and the U matrix must be square (that is, outputFeatureChannels == inputFeatureChannels). Also, the bias terms are scalars with regard to spatial dimensions.

Relationships

Inherits From

Conforms To

See Also

Recurrent Neural Networks

class MPSRNNImageInferenceLayer

A recurrent neural network layer for inference on Metal Performance Shaders images.

class MPSRNNMatrixInferenceLayer

A recurrent neural network layer for inference on Metal Performance Shaders matrices.

class MPSGRUDescriptor

A description of a gated recurrent unit block or layer.

class MPSLSTMDescriptor

A description of a long short-term memory block or layer.

enum MPSRNNSequenceDirection

Directions that a sequence of inputs can be processed by a recurrent neural network layer.

class MPSRNNMatrixTrainingLayer

A layer for training recurrent neural networks on Metal Performance Shaders matrices.

class MPSRNNMatrixTrainingState

A class that holds data from a forward pass to be used in a backward pass.

Beta Software

This documentation contains preliminary information about an API or technology in development. This information is subject to change, and software implemented according to this documentation should be tested with final operating system software.

Learn more about using Apple's beta software