added a dataset, tried testing (unsuccessfully)

1 files changed, 8 insertions, 8 deletions

diff --git a/losses.py b/losses.py
index 542aa144..851b50b3 100644
--- a/losses.py
+++ b/losses.py
@@ -1,6 +1,6 @@
 import tensorflow as tf
 from tensorflow.keras.layers import \
-    Conv2D, MaxPool2D, Dropout, Flatten, Dense, AveragePool2D
+    Conv2D, MaxPool2D, Dropout, Flatten, Dense, AveragePooling2D
 
 import numpy as np
 
@@ -28,13 +28,13 @@ class YourModel(tf.keras.Model):
                    activation="relu", name="block1_conv1"),
             Conv2D(64, 3, 1, padding="same",
                    activation="relu", name="block1_conv2"),
-            AveragePool2D(2, name="block1_pool"),
+            AveragePooling2D(2, name="block1_pool"),
             # Block 2
             Conv2D(128, 3, 1, padding="same",
                    activation="relu", name="block2_conv1"),
             Conv2D(128, 3, 1, padding="same",
                    activation="relu", name="block2_conv2"),
-            AveragePool2D(2, name="block2_pool"),
+            AveragePooling2D(2, name="block2_pool"),
             # Block 3
             Conv2D(256, 3, 1, padding="same",
                    activation="relu", name="block3_conv1"),  
@@ -42,7 +42,7 @@ class YourModel(tf.keras.Model):
                    activation="relu", name="block3_conv2"),
             Conv2D(256, 3, 1, padding="same",
                    activation="relu", name="block3_conv3"),
-            AveragePool2D(2, name="block3_pool"),
+            AveragePooling2D(2, name="block3_pool"),
             # Block 4
             Conv2D(512, 3, 1, padding="same",
                    activation="relu", name="block4_conv1"),
@@ -50,7 +50,7 @@ class YourModel(tf.keras.Model):
                    activation="relu", name="block4_conv2"),
             Conv2D(512, 3, 1, padding="same",
                    activation="relu", name="block4_conv3"),
-            AveragePool2D(2, name="block4_pool"),
+            AveragePooling2D(2, name="block4_pool"),
             # Block 5
             Conv2D(512, 3, 1, padding="same",
                    activation="relu", name="block5_conv1"),
@@ -58,7 +58,7 @@ class YourModel(tf.keras.Model):
                    activation="relu", name="block5_conv2"),
             Conv2D(512, 3, 1, padding="same",
                    activation="relu", name="block5_conv3"),
-            AveragePool2D(2, name="block5_pool"),
+            AveragePooling2D(2, name="block5_pool"),
         ]
         for layer in self.vgg16:
                layer.trainable = False
@@ -71,7 +71,7 @@ class YourModel(tf.keras.Model):
         for layer in self.vgg16.layers:
             # pass the x through
             x = layer(x)
-            print("Sotech117 is so so sus")
+       #      print("Sotech117 is so so sus")
 
             # save the output of each layer if it is in the desired list
             if layer.name in self.desired:
@@ -126,7 +126,7 @@ class YourModel(tf.keras.Model):
         return L_style
             
     def train_step(self):
-       with tf.GradientTape as tape:
+       with tf.GradientTape() as tape:
               loss = self.loss_fn(self.content_image, self.style_image, self.x)
        gradients = tape.gradient(loss, self.x)
        self.optimizer.apply_gradients(zip(gradients, self.x))