Main Content

Stateful Predict

Predict responses using a trained recurrent neural network

  • Library:
  • Deep Learning Toolbox / Deep Neural Networks

  • Stateful Predict block

Description

The Stateful Predict block predicts responses for the data at the input by using the trained recurrent neural network specified through the block parameter. This block allows loading of a pretrained network into the Simulink® model from a MAT-file or from a MATLAB® function. This block updates the state of the network with every prediction.

Ports

Input

expand all

The input ports of the Stateful Predict block takes the names of the input layers of the network loaded. Based on the network loaded, the input to the predict block can be sequence or time series data.

The dimensions of the numeric arrays containing the sequences depend on the type of data.

InputDescription
Vector sequencesc-by-s matrices, where c is the number of features of the sequences and s is the sequence length.
2-D image sequencesh-by-w-by-c-by-s arrays, where h, w, and c correspond to the height, width, and number of channels of the images, respectively, and s is the sequence length.

Output

expand all

The outputs port of the Stateful Predict block takes the names of the output layers of the network loaded. Based on the network loaded, the output of the Stateful Predict block can represent predicted scores or responses.

For sequence-to-label classification, the output is a N-by-K matrix, where N is the number of observations, and K is the number of classes.

For sequence-to-sequence classification problems, the output is a K-by-S matrix of scores, where K is the number of classes, and S is the total number of time steps in the corresponding input sequence.

Parameters

expand all

Specify the source for the trained recurrent neural network. The trained network must have at least one recurrent layer (for example, an LSTM network). Select one of the following:

  • Network from MAT-file— Import a trained recurrent neural network from a MAT-file containing a SeriesNetwork, DAGNetwork, or dlnetwork object.

  • Network from MATLAB function— Import a pretrained recurrent neural network from a MATLAB function.

This parameter specifies the name of the MAT-file that contains the trained recurrent neural network to load. If the file is not on the MATLAB path, use the Browse button to locate the file.

Dependencies

To enable this parameter, set the Network parameter to Network from MAT-file.

This parameter specifies the name of the MATLAB function for the pretrained recurrent neural network.

Dependencies

To enable this parameter, set the Network parameter to Network from MATLAB function.

Specify the sample time as a value other than -1. For more information, see Specify Sample Time (Simulink).

Extended Capabilities

Introduced in R2021a