mirror of
https://github.com/denshooter/gpu_colorization.git
synced 2026-01-21 12:32:57 +01:00
31 lines
1.3 KiB
Python
31 lines
1.3 KiB
Python
import tensorflow as tf
|
|
|
|
class DecoderLayers(tf.keras.Model):
|
|
def __init__(self):
|
|
super(DecoderLayers, self).__init__()
|
|
|
|
self.layer_list = [
|
|
tf.keras.layers.Conv2DTranspose(105, kernel_size=(3,3), strides=2, padding='same', name="Conv2D_Trans_0"),
|
|
tf.keras.layers.BatchNormalization(name="BatchNormalization_0"),
|
|
tf.keras.layers.Activation(tf.nn.tanh, name="tanh_0"),
|
|
|
|
tf.keras.layers.Conv2DTranspose(90, kernel_size=(3,3), strides=2, padding='same', name="Conv2D_Trans_1"),
|
|
tf.keras.layers.BatchNormalization(name="BatchNormalization_1"),
|
|
tf.keras.layers.Activation(tf.nn.tanh, name="tanh_1"),
|
|
|
|
tf.keras.layers.Conv2DTranspose(75, kernel_size=(3,3), strides=2, padding='same', name="Conv2D_Trans_2"),
|
|
tf.keras.layers.BatchNormalization(name="BatchNormalization_2"),
|
|
tf.keras.layers.Activation(tf.nn.tanh, name="tanh_2"),
|
|
|
|
# bottleneck to RGB
|
|
|
|
tf.keras.layers.Conv2DTranspose(2, kernel_size=(1,1), strides=1, padding='same', name="Conv2D_Trans_3"),
|
|
tf.keras.layers.BatchNormalization(name="BatchNormalization_3"),
|
|
tf.keras.layers.Activation(tf.nn.tanh, name="tanh_3"),
|
|
]
|
|
|
|
|
|
def call(self, x):
|
|
for layer in self.layer_list:
|
|
x = layer(x)
|
|
return x |