Implement Softmax Function | Dataford Interview Questions

Implement the softmax function based on the provided mathematical formula.

Given a non-empty list of real-valued logits, return a list of probabilities in the same order. Use a numerically stable implementation that avoids overflow for large logits. The output probabilities should sum to approximately 1, within normal floating-point tolerance.

Function signature: def softmax(logits): Input is list[float]; output is list[float].

Constraints

1 <= len(logits) <= 1000
Each element of logits is a finite real number
Return values in the same order as the input
Results are evaluated with floating-point tolerance

Function Signature

def softmax(logits):

Your question is Implement Softmax Function. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Implement the softmax function based on the provided mathematical formula.

Function signature: def softmax(logits): Input is list[float]; output is list[float].

Constraints

1 <= len(logits) <= 1000
Each element of logits is a finite real number
Return values in the same order as the input
Results are evaluated with floating-point tolerance

Function Signature

def softmax(logits):

Your question is Implement Softmax Function. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.