commit all

auto_encoder.py

@@ -124,7 +124,7 @@ class Bottleneck(tf.keras.Model):
                        layer_scale_init_value=1e-6, prefix=f'bottleneck{j}') for j in range(5)]
             )
 
-    def call(self, inputs, training=None):
+    def call(self, inputs, training):
         x = inputs
 
         x = self.bottleneck(x, training=training)
@@ -145,7 +145,7 @@ class AutoEncoder(tf.keras.Model):
         self.decoder = ConvNeXtReverse(depths=list(reversed([3, 3, 9, 3])), dims=list(reversed([bottleneck_size, 128, 64, 16])))
 
 
-    def call(self, inputs, training=None):
+    def call(self, inputs, training):
         x, uv_mask = inputs
 
         x = tf.transpose(x, [0,2,3,1])
@@ -328,7 +328,7 @@ if __name__ == '__main__':
 
 
     factory = DatasetFactory()
-    signature_dynamic = { 'id': (),
+    signature_dynamic = { 'id': (), 'frame_nr': (),
                           'pose_shape': (72 + 11,),
                         #   'uv_posed': (3, 512, 256,),
                           'uv_body_posed': (3, 512, 256,),