Value Clipping

题面

Implement a GPU program that performs clipping on 1D input vectors. Given an input tensor of shape [N] where N is the number of elements, compute the output by clipping each element to a specified range [lo, hi]. The input and output tensor must be of type float32.

Clipping is defined as:

• For each element x in the input tensor, "clip" the element so that it falls within the allowed range [lo, hi].
• This operation ensures all values are within the specified range and is commonly used in ML for activation stabilization and pre-quantization.

Implementation Requirements

• Use only native features (external libraries are not permitted)
• The solve function signature must remain unchanged
• The final result must be stored in the output tensor

Examples

Example 1:

Input:  [1.5, -2.0, 3.0, 4.5], lo = 0.0, hi = 3.5
Output: [1.5, 0.0, 3.0, 3.5]

Example 2:

Input:  [-1.0, 2.0, 5.0], lo = -0.5, hi = 2.5
Output: [-0.5, 2.0, 2.5]

Constraints

• 1 ≤ N ≤ 100,000
• -10^6 ≤ input[i] ≤ 10^6
• lo ≤ hi
• Performance is measured with N = 100,000