Bug fixing

Author: JanMarcelKezmann

tensorflow_advanced_segmentation_models/__version__.py

@@ -1,3 +1,3 @@
-VERSION = (0, 4, 8)
+VERSION = (0, 4, 9)
 
 __version__ = ".".join(map(str, VERSION))

tensorflow_advanced_segmentation_models/models/_custom_layers_and_blocks.py

@@ -941,7 +941,7 @@ def __init__(self, filters, scale=1.0, dropout=0.1):
         axis = 3 if K.image_data_format() == "channels_last" else 1
         self.concat = tf.keras.layers.Concatenate(axis=axis)
         self.conv1x1_bn_relu = ConvolutionBnActivation(filters, (1, 1))
-        self.dropout = tf.keras.layers.Layer(dropout)
+        self.dropout = tf.keras.layers.Dropout(dropout)
 
     def call(self, features, ocr_context, training=None):
         # features-dim: (BS, H, W, C) & ocr_context-dim: (BS, C, C2) (if K.image_data_format() == "channels_last")
@@ -975,7 +975,7 @@ def __init__(self, filters, scale=1, dropout=0.1, dilations=(12, 24, 36)):
         self.concat = tf.keras.layers.Concatenate(axis=self.axis)
 
         self.conv1x1_bn_relu_2 = ConvolutionBnActivation(filters, (1, 1))
-        self.dropout = tf.keras.layers.Layer(dropout)
+        self.dropout = tf.keras.layers.Dropout(dropout)
 
     def call(self, x, probabilities, training=None):
         feat1 = self.conv3x3_bn_relu_1(x, training=training)