I read data from RAM. (dataload = np.load(‘data.npz’), dtl = torch.from_numpy(data[‘arr_0’])
I made timings on every line of my code. Time is spent only on forward pass and backward.
Since I have reinforcement learning, I do forward pass first, get action and reward, then load the data into the second dataload, then forward pass and backward again. But it bothers me that changing batch does not speed things up. I think this is related to the size of my network.