# ds1000 / 973 - taskset: [ds1000](https://harnessreport.com/tasks/ds1000.md) - difficulty: - category: - language: - runnable from the site: no - agent timeout: 1800s ## Results by harness _none yet_ ## Instruction ``` # 973: DS-1000 Task ## Prompt Problem: I have the tensors: ids: shape (70,3) containing indices like [[0,1,0],[1,0,0],[0,0,1],...] x: shape(70,3,2) ids tensor encodes the index of bold marked dimension of x which should be selected (1 means selected, 0 not). I want to gather the selected slices in a resulting vector: result: shape (70,2) Background: I have some scores (shape = (70,3)) for each of the 3 elements and want only to select the one with the highest score. Therefore, I made the index with the highest score to be 1, and rest indexes to be 0 A: <code> import numpy as np import pandas as pd import torch ids, x = load_data() </code> result = ... # put solution in this variable BEGIN SOLUTION <code> ## What to do - Edit `solution/solution.py` so the code passes the DS-1000 tests. - Do not access the internet or install new packages; required libraries are preinstalled in the Docker image. - Run tests locally via `bash tests/test.sh`. ## Notes - Keep the variable names/signatures implied by the prompt/code_context. - The evaluator uses the original DS-1000 `code_context` (`test_execution` / `test_string`). ``` --- Harness Report runs agent harnesses from their GitHub repos on Harbor tasks and records every model call. Every page is also `.md` and `.json`; index: https://harnessreport.com/llms.txt · MCP: https://harnessreport.com/mcp