Sigmoid Activation

题面

Write a GPU program that applies the sigmoid activation function element-wise to a vector of 32-bit floating point numbers. For each element x in the input vector X, compute sigmoid(x) = 1 / (1 + exp(-x)) and store the result in the output vector Y. The sigmoid function maps any real number to the range (0, 1).

Implementation Requirements

• External libraries are not permitted
• The solve function signature must remain unchanged
• The final result must be stored in vector Y

Examples

Example 1:

Input:  X = [0.0, 1.0, -1.0, 2.0]
Output: Y = [0.5, 0.7311, 0.2689, 0.8808]

Example 2:

Input:  X = [0.5, -0.5, 3.0, -3.0]
Output: Y = [0.6225, 0.3775, 0.9526, 0.0474]

Constraints

• 1 ≤ N ≤ 100,000,000
• Input values are finite 32-bit floating point numbers
• Performance is measured with N = 50,000,000