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@bryanlimy
Created May 20, 2019 15:08
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class PositionalEncoding(tf.keras.layers.Layer):
def __init__(self, position, d_model):
super(PositionalEncoding, self).__init__()
self.pos_encoding = self.positional_encoding(position, d_model)
def get_angles(self, position, i, d_model):
angles = 1 / tf.pow(10000, (2 * (i // 2)) / tf.cast(d_model, tf.float32))
return position * angles
def positional_encoding(self, position, d_model):
angle_rads = self.get_angles(
position=tf.range(position, dtype=tf.float32)[:, tf.newaxis],
i=tf.range(d_model, dtype=tf.float32)[tf.newaxis, :],
d_model=d_model)
# apply sin to even index in the array
sines = tf.math.sin(angle_rads[:, 0::2])
# apply cos to odd index in the array
cosines = tf.math.cos(angle_rads[:, 1::2])
pos_encoding = tf.concat([sines, cosines], axis=-1)
pos_encoding = pos_encoding[tf.newaxis, ...]
return tf.cast(pos_encoding, tf.float32)
def call(self, inputs):
return inputs + self.pos_encoding[:, :tf.shape(inputs)[1], :]
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