<gh_stars>0
import numpy as np

def softmax(x):
    """
    Compute softmax values for each sets of scores in x.
    
    Rows are scores for each class. 
    Columns are predictions (samples).
    """
    scoreMatExp = np.exp(np.asarray(x))
    return scoreMatExp / scoreMatExp.sum(0)
import numpy as np

def softmax(x):
    """
    Compute softmax values for each sets of scores in x.
    
    Rows are scores for each class. 
    Columns are predictions (samples).
    """
    scoreMatExp = np.exp(np.asarray(x))
    return scoreMatExp / scoreMatExp.sum(0)
Compute softmax values for each sets of scores in x.          Rows are scores for each class.      Columns are predictions (samples).