Hi all,
I am working on a time series dataset where 30 days of data are given to the model during training for each batch. The shape of the tensor is  [5,9,30,10] (batch_size, time_steps, #days, features).
I want to pass this tensor to a conv2d layer to transform it to a shape [5,1,30,10] and do squeeze(1) to finally get a shape of [5,30,10]. What I want to do is to summarise the time steps for each day.
I am having a hard time understanding if the order of the tensor’s dimensions is correct, and how they should be passed to the conv2d function.
The RGB channels equivalent for my case is the time_steps or the #days dimension?