# ds1000 / 953

- 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

```
# 953: DS-1000 Task

## Prompt
Problem:

How to batch convert sentence lengths to masks in PyTorch?
For example, from

lens = [3, 5, 4]
we want to get

mask = [[0, 0, 1, 1, 1],
        [1, 1, 1, 1, 1],
        [0, 1, 1, 1, 1]]
Both of which are torch.LongTensors.


A:

<code>
import numpy as np
import pandas as pd
import torch
lens = load_data()
</code>
mask = ... # 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`).
```
---
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