Leetcode题目 039. 组合总和

    net.eval()  # 须增加这行代码，固定住batch normalization 和 drop out
    with torch.no_grad():
        outputs = net(images)
        _, predictions = torch.max(outputs, 1)

class Solution:
    def combinationSum(self, candidates: List[int], target: int) -> List[List[int]]:
        # candidates.sort()
        def dfs(candidates, begin, path, target):
            if target==1 or target < 0: # 根据条件 2 <= candidates[i] <= 40，target==1 时也无解
                return
            if target == 0: # 满足条件， 各candi 之和 为最初的target
                res.append(path)
                return

            for index in range(begin, size):
                candi = candidates[index]
                dfs(candidates, index, path + [candi],target - candi)  # 递归 和 剪枝（begin 不从0开始）

        size = len(candidates)
        if size == 0:
            return []
        path = []
        res = []
        dfs(candidates, 0, path,target)
        return res