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# from __future__ import absolute_import
from __future__ import print_function
from __future__ import division
from keras import backend as K
def softmax(x, axis, mask=None):
if mask is None:
mask = K.constant(True)
mask = K.cast(mask, K.floatx())
if K.ndim(x) is K.ndim(mask) + 1:
mask = K.expand_dims(mask)
m = K.max(x, axis=axis, keepdims=True)
e = K.exp(x - m) * mask
s = K.sum(e, axis=axis, keepdims=True)
s += K.cast(K.cast(s < K.epsilon(), K.floatx()) * K.epsilon(), K.floatx())
return e / s
def compute_mask(x, mask_value=0):
boolean_mask = K.any(K.not_equal(x, mask_value), axis=-1, keepdims=False)
return K.cast(boolean_mask, K.floatx())