dataset.py 文件源码

def __iter__(self):
        n_batch = len(self) // self.batch_size
        tail = len(self) % self.batch_size
        index = torch.LongTensor(len(self)).fill_(0)
        for i in range(n_batch):
            random_start = random.randint(0, len(self) - self.batch_size)
            batch_index = random_start + torch.range(0, self.batch_size - 1)
            index[i * self.batch_size:(i + 1) * self.batch_size] = batch_index
        # deal with tail
        if tail:
            random_start = random.randint(0, len(self) - self.batch_size)
            tail_index = random_start + torch.range(0, tail - 1)
            index[(i + 1) * self.batch_size:] = tail_index

        return iter(index)