I understand you are facing issue when you train your network on GPU. I can suggest you 2 solutions regarding your query:
1.You can move a categorical array to the GPU, but you need to convert it to a numeric array first.
Convert the categorical array to a numeric array using the "grp2idx" function.
Once you have the numeric array, you can use "gpuArray" to move it to the GPU.
Example code:
numericArray = grp2idx(categoricalArray);
numericArrayGPU = gpuArray(numericArray);
You can refer to this MATLAB documentation and the MATLAB answer mentioned below:
https://www.mathworks.com/help/stats/grp2idx.html
2. You can try by specifying the execution environment as 'auto' in the training options. The Deep Learning toolbox will automatically handle the data movement and computations on the GPU for you. This includes moving the input data to the GPU and converting categorical data as needed. You can train your sequence-to-classification network with categorical arrays on a GPU without explicitly moving the input data to the GPU or converting the categorical data.
Hope this helps!
