support kv3 parsed batchnorm

Author: calad0i

hls4ml/model/layers.py

@@ -1018,16 +1018,21 @@ def initialize(self):
         dims = inp.dim_names
         self.add_output_variable(shape, dims)
 
-        gamma = self.get_attr('gamma_data')
-        beta = self.get_attr('beta_data')
-        mean = self.get_attr('mean_data')
-        var = self.get_attr('variance_data')
-
-        scale = gamma / np.sqrt(var + self.get_attr('epsilon'))
-        bias = beta - scale * mean
+        if self.get_attr('scale_data') is None:
+            gamma = self.get_attr('gamma_data')
+            var = self.get_attr('variance_data')
+            scale = gamma / np.sqrt(var + self.get_attr('epsilon'))
+            self.add_weights_variable(name='scale', var_name='s{index}', data=scale)
+        else:
+            self.add_weights_variable(name='scale', var_name='s{index}')
 
-        self.add_weights_variable(name='scale', var_name='s{index}', data=scale)
-        self.add_weights_variable(name='bias', var_name='b{index}', data=bias)
+        if self.get_attr('bias_data') is None:
+            beta = self.get_attr('beta_data')
+            mean = self.get_attr('mean_data')
+            bias = beta - scale * mean
+            self.add_weights_variable(name='bias', var_name='b{index}', data=bias)
+        else:
+            self.add_weights_variable(name='bias', var_name='b{index}')
 
 
 # TODO:  discuss whether this should be renamed to soemthing more descriptive, and whether the class hierarchy makes sense