Update model.py

model.py

@@ -1,13 +1,13 @@
 import tensorflow as tf
 
 
-CAP = 3501 # Cap for the number of notes
+_CAP = 3501 # Cap for the number of notes
 
 class Encoder_Z(tf.keras.layers.Layer):
 
   def __init__(self, dim_z, name="encoder", **kwargs):
     super(Encoder_Z, self).__init__(name=name, **kwargs)
-    self.dim_x = (3, CAP, 1)
+    self.dim_x = (3, _CAP, 1)
     self.dim_z = dim_z
 
   def build(self):
@@ -45,8 +45,8 @@ class Decoder_X(tf.keras.layers.Layer):
     layers.append(tf.keras.layers.Dense(2000))
     layers.append(tf.keras.layers.ReLU())
 
-    layers.append(tf.keras.layers.Dense((CAP - 1) / 2 * 32, activation=None))
-    layers.append(tf.keras.layers.Reshape((1, int((CAP - 1) / 2), 32)))
+    layers.append(tf.keras.layers.Dense((_CAP - 1) / 2 * 32, activation=None))
+    layers.append(tf.keras.layers.Reshape((1, int((_CAP - 1) / 2), 32)))
 
     layers.append(tf.keras.layers.Conv2DTranspose(
         filters=64, kernel_size=3, strides=2, padding='valid'))