Does the input size of sequenceInputLayer have to be set 1?

i followed the example https://ww2.mathworks.cn/help/textanalytics/ug/classify-text-data-using-deep-learning.html.

The network is as follows:

inputSize = 1;

embeddingDimension = 50;

numHiddenUnits = 80;

numWords = enc.NumWords;

numClasses = numel(categories(YTrain));

layers = [ ...

sequenceInputLayer(inputSize)

wordEmbeddingLayer(embeddingDimension,numWords)

lstmLayer(numHiddenUnits,'OutputMode','last')

fullyConnectedLayer(numClasses)

softmaxLayer

classificationLayer]

I only tried to change inputSize = 2, then the network can not be trained with the error:

Does the input size of sequenceInputLayer have to be set 1?

Answer 1

[Zhiyu WANG]

Becasue the input sequence data is a 1 by 10 double.It menas each time you take 1 token out of the sequence.