def test_softmax():
from keras.activations import softmax as s
# Test using a reference implementation of softmax
def softmax(values):
m = max(values)
values = numpy.array(values)
e = numpy.exp(values - m)
dist = list(e / numpy.sum(e))
return dist
x = T.vector()
exp = s(x)
f = theano.function([x], exp)
test_values=get_standard_values()
result = f(test_values)
expected = softmax(test_values)
print(str(result))
print(str(expected))
list_assert_equal(result, expected)
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