Hi everyone,
i’m approacching RNN and i have a supervised signal recognition task.
I have 7955 different signals, each consisiting of 300 samples.
I proceeded to create a tensor for the signals (7955, 300, 1) and a tensor for the lables (7955, 75) (75 different classes, one hot encoded).
Then i wrapped it up in a dataset using tf.data.dataset.fromtensors().
That lead to my problem, now i’m trying to shuffle and separate this dataset in order to have a train and a test dataset.
I’m trying to use the common .skip() and .take() method, but it doesen’t work out because the cardinality of the dataset seems to be 1.
Any idea to get rid of this?
Thanks in advance and sorry for eventually grammar mistakes.