@lanpa  the sizes are as below:
inputs:  torch.Size([32, 3, 32, 32])
outputs:  torch.Size([32, 10])
targets:  torch.Size([32])
I got my code working, I think the issue was with the “_out.data”
    dataiter = iter(testloader)
    img, lbl = dataiter.next()
    _out = net(Variable(img))
    _, predicted = torch.max(_out,1)


    #GroundTruth
    print('GroundTruth: ', ' '.join('%9s' % classes[lbl[j]] for j in range(9)))
    #Predicted
    print('Predicted: ', ' '.join('%9s' % classes[predicted[j]]for j in range(9)))

    #Embeddings
    lbl = [classes[i] for i in lbl]
    writer.add_embedding(_out.data,metadata=lbl,label_img=img.data, global_step=epoch)

Thank you and do let me know if you have any more suggestions.