Given two sparse vectors, compute their dot product. Implement class SparseVector: SparseVector(nums) Initializes the object with the vector nums dotProduct(vec) Compute the dot product between the instance of SparseVector and vec A sparse vector is a vector that has mostly zero values, you should store the sparse vector efficiently and compute the dot product between two SparseVector. Follow up: What if only one of the vectors is sparse? Example 1: Input: nums1 = [1,0,0,2,3], nums2 = [0,3,0,4,0] Output: 8 Explanation: v1 = SparseVector(nums1) , v2 = SparseVector(nums2) v1.dotProduct(v2) = 1*0 + 0*3 + 0*0 + 2*4 + 3*0 = 8 Example 2: Input: nums1 = [0,1,0,0,0], nums2 = [0,0,0,0,2] Output: 0 Explanation: v1 = SparseVector(nums1) , v2 = SparseVector(nums2) v1.dotProduct(v2) = 0*0 + 1*0 + 0*0 + 0*0 + 0*2 = 0 Example 3: Input: nums1 = [0,1,0,0,2,0,0], nums2 = [1,0,0,0,3,0,4] Output: 6 Constraints: n == nums1.length == nums2.length 1 <= n <= 10^5 0 <= nums1[i], nums2[i] <= 100