Spaces:
Runtime error
Runtime error
File size: 1,339 Bytes
c873df0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 |
import tensorflow as tf
from tensorflow.keras.layers import Layer, Dense
def sin_activation(x, omega=30):
return tf.math.sin(omega * x)
class AdaIN(Layer):
def __init__(self, **kwargs):
super(AdaIN, self).__init__(**kwargs)
def build(self, input_shapes):
x_shape = input_shapes[0]
w_shape = input_shapes[1]
self.w_channels = w_shape[-1]
self.x_channels = x_shape[-1]
self.dense_1 = Dense(self.x_channels)
self.dense_2 = Dense(self.x_channels)
def call(self, inputs):
x, w = inputs
ys = tf.reshape(self.dense_1(w), (-1, 1, 1, self.x_channels))
yb = tf.reshape(self.dense_2(w), (-1, 1, 1, self.x_channels))
return ys * x + yb
def get_config(self):
config = {
#'w_channels': self.w_channels,
#'x_channels': self.x_channels
}
base_config = super(AdaIN, self).get_config()
return dict(list(base_config.items()) + list(config.items()))
class AdaptiveAttention(Layer):
def __init__(self, **kwargs):
super(AdaptiveAttention, self).__init__(**kwargs)
def call(self, inputs):
m, a, i = inputs
return (1 - m) * a + m * i
def get_config(self):
base_config = super(AdaptiveAttention, self).get_config()
return base_config
|