# Normalize Scores and Count High Achievers per Subject

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Given a 2D list `StudentScores` where each row represents a student's scores in different subjects, and subjects are represented by columns, normalize the scores for each subject using the softmax function. Return a one-dimensional tensor representing how many students achieved a normalized score greater than 0.3 for each subject.

For each subject (column), apply the softmax function to normalize the scores. Then count the number of students for each column (subject) who achieved a normalized score greater than 0.3. Note: Softmax is a mathematical function that converts a vector of real numbers into a vector of probabilities, where the probabilities are proportional to the exponentials of the input numbers and sum up to 1. Check 'Implement Softmax Function' problem to see the formula and to practice implementing it.### Examples:

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