def collate_batch(self, batch): b = collate_batch(batch) for i in range(len(self.args)): x = b[i] if jt.is_var(self.args[i]) and self.args[i].ndim == 1: x.assign(x.squeeze(-1)) return b
def collate_batch(self, batch): ''' Puts each data field into a tensor with outer dimension batch size. Args:: [in] batch(list): A list of variables, such as jt.var, Image.Image, np.ndarray, int, float, str and so on. ''' return collate_batch(batch)
def collate_batch(self, batch): return collate_batch(batch)
def test_collate_batch(self): from jittor.dataset.utils import collate_batch batch = collate_batch([(1, 1), (1, 2), (1, 3)]) assert isinstance(batch[0], np.ndarray) assert isinstance(batch[1], np.ndarray)