hi

5 files changed, 7 insertions, 5 deletions

diff --git a/__pycache__/hyperparameters.cpython-38.pyc b/__pycache__/hyperparameters.cpython-38.pyc
index 99d18197..40cba873 100644
--- a/__pycache__/hyperparameters.cpython-38.pyc
+++ b/__pycache__/hyperparameters.cpython-38.pyc
diff --git a/__pycache__/losses.cpython-38.pyc b/__pycache__/losses.cpython-38.pyc
index a642b379..ff01b5a7 100644
--- a/__pycache__/losses.cpython-38.pyc
+++ b/__pycache__/losses.cpython-38.pyc
diff --git a/hyperparameters.py b/hyperparameters.py
index 73f4b497..fedd4dd7 100644
--- a/hyperparameters.py
+++ b/hyperparameters.py
@@ -9,7 +9,7 @@ Number of epochs. If you experiment with more complex networks you
 might need to increase this. Likewise if you add regularization that
 slows training.
 """
-num_epochs = 5000
+num_epochs = 150
 
 """
 A critical parameter that can dramatically affect whether training
@@ -20,6 +20,6 @@ learning_rate = 1e-2
 
 momentum = 0.01
 
-alpha = 1e-2
+alpha = 1e1
 
-beta = 1e-4
+beta = 1e2
diff --git a/losses.py b/losses.py
index 5564ca33..4c7b5750 100644
--- a/losses.py
+++ b/losses.py
@@ -34,7 +34,7 @@ class YourModel(tf.keras.Model):
 
         #print(self.content_image.shape, self.style_image.shape)
 
-        self.optimizer = tf.keras.optimizers.Adam()
+        self.optimizer = tf.keras.optimizers.Adam(1e-2)
 
         self.vgg16 = [
             # Block 1
@@ -112,6 +112,8 @@ class YourModel(tf.keras.Model):
        content_l = self.content_loss(self.photo_layers, input_layers)
        style_l = self.style_loss(self.art_layers, input_layers)
         # Equation 7
+       print('style_loss', style_l) 
+       print('content_loss', content_l) 
        return (self.alpha * content_l) + (self.beta * style_l)
         
     def content_loss(self, photo_layers, input_layers):
@@ -164,7 +166,7 @@ class YourModel(tf.keras.Model):
         for i in range(len(art_layers)):
             art_layer = art_layers[i]
             input_layer = input_layers[i]
-            L_style = tf.math.add(L_style, self.layer_loss(art_layer, input_layer))
+            L_style = tf.math.add(L_style, self.layer_loss(art_layer, input_layer)*(1/5))
         #print('style loss', L_style)
         return L_style
             
diff --git a/save.jpg b/save.jpg
index 5a6d6522..a77ce43c 100644
--- a/save.jpg
+++ b/save.jpg