diff --git a/core/leras/layers/Conv2D.py b/core/leras/layers/Conv2D.py
index 7d4d444..a5febf0 100644
--- a/core/leras/layers/Conv2D.py
+++ b/core/leras/layers/Conv2D.py
@@ -55,8 +55,8 @@ class Conv2D(nn.LayerBase):
             if kernel_initializer is None:
                 kernel_initializer = tf.initializers.random_normal(0, 1.0, dtype=self.dtype)
 
-        if kernel_initializer is None:
-            kernel_initializer = nn.initializers.ca()
+        #if kernel_initializer is None:
+        #    kernel_initializer = nn.initializers.ca()
 
         self.weight = tf.get_variable("weight", (self.kernel_size,self.kernel_size,self.in_ch,self.out_ch), dtype=self.dtype, initializer=kernel_initializer, trainable=self.trainable )
 
diff --git a/core/leras/layers/Conv2DTranspose.py b/core/leras/layers/Conv2DTranspose.py
index 937d624..a2e97dc 100644
--- a/core/leras/layers/Conv2DTranspose.py
+++ b/core/leras/layers/Conv2DTranspose.py
@@ -38,8 +38,8 @@ class Conv2DTranspose(nn.LayerBase):
             if kernel_initializer is None:
                 kernel_initializer = tf.initializers.random_normal(0, 1.0, dtype=self.dtype)
 
-        if kernel_initializer is None:
-            kernel_initializer = nn.initializers.ca()
+        #if kernel_initializer is None:
+        #    kernel_initializer = nn.initializers.ca()
         self.weight = tf.get_variable("weight", (self.kernel_size,self.kernel_size,self.out_ch,self.in_ch), dtype=self.dtype, initializer=kernel_initializer, trainable=self.trainable )
 
         if self.use_bias:
diff --git a/core/leras/layers/DepthwiseConv2D.py b/core/leras/layers/DepthwiseConv2D.py
index 98f3a0a..2916f01 100644
--- a/core/leras/layers/DepthwiseConv2D.py
+++ b/core/leras/layers/DepthwiseConv2D.py
@@ -68,8 +68,8 @@ class DepthwiseConv2D(nn.LayerBase):
             if kernel_initializer is None:
                 kernel_initializer = tf.initializers.random_normal(0, 1.0, dtype=self.dtype)
 
-        if kernel_initializer is None:
-            kernel_initializer = nn.initializers.ca()
+        #if kernel_initializer is None:
+        #    kernel_initializer = nn.initializers.ca()
 
         self.weight = tf.get_variable("weight", (self.kernel_size,self.kernel_size,self.in_ch,self.depth_multiplier), dtype=self.dtype, initializer=kernel_initializer, trainable=self.trainable )