def process_state(self, state):
x = torch.tensor(data=state, dtype=torch.float, device=device)
# Change color channel position from (210, 160, 3) to (1, 210, 160)
x = x.permute(2, 0, 1)
# From color to gray
x = rgb_to_grayscale(x)
# Resize from (1, 210, 160) to (1, 80, 80)
x = Resize([80, 80])(x)
# Reduce size 1 dimension
x = x.squeeze(0)
return x
def process_state(self, state):
x = torch.tensor(data=state, dtype=torch.float, device=self.device)
# Change color channel position from (210, 160, 3) to (1, 210, 160)
x = x.permute(2, 0, 1)
# From color to gray
x = rgb_to_grayscale(x)
# Resize from (1, 210, 160) to (1, 84, 84)
x = Resize([RESIZE, RESIZE])(x)
# Reduce size 1 dimension
x = x.squeeze(0)
# Normalize input 0 to i
x = x.div(255)
return x.detach().cpu().numpy()