kaixin:

from torch.utils.data import Dataset class WeatherData(Dataset): def getitem(self, idx): return {‘inputs’: [self.temp[i] for i in range(idx + 4)], ‘target’: self.water[idx + 3]}


Thank you.
if possible could you clarify this issue please:
if I want the network to update the weights based on the entire year data (365 days data) like a regression problem, should not I feed the whole training set at once like this:
Input nodes = 4 (feeding the network 4 days measurements)
output nodes = 1 (expecting 1 output)
batch size = 365-3 = 362 (I have 362 training example to cover the whole year)
input shape = 365 x 4 (as you mentioned)
output shape = 365 x 1
thank you in advance