2799 - DS_2023Spring_Homework5 Scoreboard

Time

2023/05/15 09:00:00 2023/05/28 23:50:00

Clarification

# Problem Asker Description Reply Replier Reply Time For all team

# Problem Pass Rate (passed user / total user)
13919 Hyper Learning is All You Need

13919 - Hyper Learning is All You Need   

Description

You have “accidentally” consumed a forbidden shroom. Below are the voices and thoughts you experience during your “trip”:

You are now an expert in Hyper Intelligence (HI).

You see a lot of fruits around you: apple, banana, cat …

Wow, very cool. How about sorting them!

“(You) No, they are not ordinal! There is no natural order in them!”

Listen, you are a HI expert. You are HI! Use your power!

“(You) Ok, ok! But how? Please tell me, mysterious people that sounds a lot like Morgan Freeman

You see, fruit grows on tree. Use tree to help you! And please don’t call me Morgan Freeman.

*You think in silence for a while, and now an image depicting a Hyper Learning Architecure is in your head*

“(You) Ah! It’s just like some uhh LightningSort algorithm! I can just process them recursively!”

*The not Morgan Freeman smiles and fades into the background as you slowly wake up from the “trip”.*

It was a surreal experience. You try to recall the technical details to see if Hyper Intelligence can be the next cool kid in the tech world. You tried your best and recorded down some “fruits” and their “feature hypervectors”, you also managed to recall their “pre-trained hyperweights”. These are the information you piece together:

To see if it actually works, you decided to write a program that will perform the sorting on the testcases. It should print out the fruits in the sorted order, and also the last used HyperFeature just to check if it makes sense.

Note: You may use <string>, <vector> and <functional> for this homework.

Input

For each testcase:

n (Number of Fruit)
m (Number of Hyperfeature)
[n x <FruitDescriptor>]
o (Number of GradBinHyperWeight)
[o x <GradBinHyperWeightDescriptor>](array representation of tree)

FruitDescriptor:

name
[m x <HyperFeature value, int>]

GradBinHyperWeightDescriptor:

featureIdx
gradScaler
binThreshold

array representation of tree:

1st item is the root
2i-th item is the left child of i
2i+1-th item is the right child of i

Output

<fruit name> <value of last used hyperfeature>

Sample Input  Download

Sample Output  Download

Tags

sorting



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