# ds1000 / 968 - 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 ``` # 968: DS-1000 Task ## Prompt Problem: I have the following torch tensor: tensor([[-0.2, 0.3], [-0.5, 0.1], [-0.4, 0.2]]) and the following numpy array: (I can convert it to something else if necessary) [1 0 1] I want to get the following tensor: tensor([0.3, -0.5, 0.2]) i.e. I want the numpy array to index each sub-element of my tensor. Preferably without using a loop. Thanks in advance A: <code> import numpy as np import pandas as pd import torch t, idx = load_data() assert type(t) == torch.Tensor assert type(idx) == np.ndarray </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