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dvgodoy/truncated_normal.py

Created June 10, 2018 15:17
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truncated_normal.py
import numpy as np
from keras import backend as K
from keras.initializers import VarianceScaling
fan_in = fan_out = 100
stddev = np.sqrt(1. / fan_in)
normal_values = K.eval(K.random_normal(shape=(fan_in, fan_out), stddev=stddev)).ravel()
truncated_values = K.eval(K.truncated_normal(shape=(fan_in, fan_out), stddev=stddev)).ravel()
var_scaling_values = K.eval(VarianceScaling(mode='fan_in')(shape=(fan_in, fan_out))).ravel()
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