Update the face stylizer config to match the latest encoder and detector config.

PiperOrigin-RevId: 527637477

mediapipe/model_maker/python/vision/face_stylizer/face_stylizer.py

@@ -178,7 +178,7 @@ class FaceStylizer(object):
       with tf.GradientTape() as tape:
         outputs = self._decoder(
             {'inputs': in_latent + self.w_avg},
-            training=False,
+            training=True,
         )
         gen_img = outputs['image'][-1]
 

mediapipe/model_maker/python/vision/face_stylizer/hyperparameters.py

@@ -31,7 +31,7 @@ class HParams(hp.BaseHParams):
   """
 
   # Parameters from BaseHParams class.
-  learning_rate: float = 5e-5
+  learning_rate: float = 8e-4
   batch_size: int = 4
   epochs: int = 100
   # Parameters for face stylizer.

mediapipe/model_maker/python/vision/face_stylizer/model_options.py

@@ -21,7 +21,7 @@ from mediapipe.model_maker.python.core.utils import loss_functions
 
 def _default_perceptual_quality_loss_weight():
   """Default perceptual quality loss weight for face stylizer."""
-  return loss_functions.PerceptualLossWeight(l1=2.0, content=20.0, style=10.0)
+  return loss_functions.PerceptualLossWeight(l1=0.5, content=4.0, style=1.0)
 
 
 # TODO: Add more detailed instructions about hyperparameter tuning.
@@ -32,18 +32,21 @@ class FaceStylizerModelOptions:
   Attributes:
     swap_layers: The layers of feature to be interpolated between encoding
       features and StyleGAN input features.
-    alpha: Weighting coefficient for swapping layer interpolation.
+    alpha: Weighting coefficient of style latent for swapping layer
+      interpolation. Its valid range is [0, 1]. The greater weight means
+      stronger style is applied to the output image. Expect to set it to a small
+      value, i.e. < 0.1.
     perception_loss_weight: Weighting coefficients of image perception quality
       loss.
     adv_loss_weight: Weighting coeffcieint of adversarial loss versus image
-      perceptual quality loss.
+      perceptual quality loss. It expects a small value, i.e. < 0.2.
   """
 
   swap_layers: Sequence[int] = dataclasses.field(
-      default_factory=lambda: [4, 5, 6, 7, 8, 9, 10, 11]
+      default_factory=lambda: [4, 5, 10, 11]
   )
-  alpha: float = 1.0
+  alpha: float = 0.1
   perception_loss_weight: loss_functions.PerceptualLossWeight = (
       dataclasses.field(default_factory=_default_perceptual_quality_loss_weight)
   )
-  adv_loss_weight: float = 1.0
+  adv_loss_weight: float = 0.2