he-021

# HumanEval/21

Implement a file **`solution.py`** that completes the function below. Keep the given name and signature; your file must define it at module level.

```python
from typing import List


def rescale_to_unit(numbers: List[float]) -> List[float]:
    """ Given list of numbers (of at least two elements), apply a linear transform to that list,
    such that the smallest number will become 0 and the largest will become 1
    >>> rescale_to_unit([1.0, 2.0, 3.0, 4.0, 5.0])
    [0.0, 0.25, 0.5, 0.75, 1.0]
    """
```

<!-- imported from OpenAI HumanEval (HumanEval/21) -->

# Auto-generated from OpenAI HumanEval HumanEval/21. Do not edit by hand.
from solution import *  # noqa: F401,F403 (prompt helpers may be referenced by tests)
from solution import rescale_to_unit as candidate

METADATA = {
    'author': 'jt',
    'dataset': 'test'
}


def check(candidate):
    assert candidate([2.0, 49.9]) == [0.0, 1.0]
    assert candidate([100.0, 49.9]) == [1.0, 0.0]
    assert candidate([1.0, 2.0, 3.0, 4.0, 5.0]) == [0.0, 0.25, 0.5, 0.75, 1.0]
    assert candidate([2.0, 1.0, 5.0, 3.0, 4.0]) == [0.25, 0.0, 1.0, 0.5, 0.75]
    assert candidate([12.0, 11.0, 15.0, 13.0, 14.0]) == [0.25, 0.0, 1.0, 0.5, 0.75]


def test_he_021():
    check(candidate)

```python
def rescale_to_unit(numbers: List[float]) -> List[float]:
    """ Given list of numbers (of at least two elements), apply a linear transform to that list,
    such that the smallest number will become 0 and the largest will become 1,
    1.0, 2.0, 3.0, 4.0, 5.0
    """
    return numbers
```