Created
June 25, 2017 18:34
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"""Softmax.""" | |
scores = [3.0, 1.0, 0.2] | |
import numpy as np | |
def softmax(x): | |
"""Compute softmax values for each sets of scores in x.""" | |
pass # TODO: Compute and return softmax(x) | |
return np.exp(x) / np.sum(np.exp(x), axis=0) | |
print(softmax(scores)) | |
# Plot softmax curves | |
import matplotlib.pyplot as plt | |
x = np.arange(-2.0, 6.0, 0.1) | |
scores = np.vstack([x, np.ones_like(x), 0.2 * np.ones_like(x)]) | |
plt.plot(x, softmax(scores).T, linewidth=2) | |
plt.show() |
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