Rename kernel to multi_kernel

n3fit/src/n3fit/backends/keras_backend/multi_dense.py

@@ -56,7 +56,7 @@ def __init__(
 
     def build(self, input_shape):
         input_dim = input_shape[-1]
-        self.kernel = self.add_weight(
+        self.multi_kernel = self.add_weight(
             name="kernel",
             shape=(self.replicas, input_dim, self.units),
             initializer=self.kernel_initializer,
@@ -80,15 +80,15 @@ def build(self, input_shape):
         # TODO: benchmark against the replica-agnostic einsum below and make that default
         # see https://github.com/NNPDF/nnpdf/pull/1905#discussion_r1489344081
         if self.replicas == 1:
-            matmul = lambda inputs: tf.tensordot(inputs, self.kernel[0], [[-1], [0]])
+            matmul = lambda inputs: tf.tensordot(inputs, self.multi_kernel[0], [[-1], [0]])
             if self.is_first_layer:
                 # Manually add replica dimension
                 self.matmul = lambda x: tf.expand_dims(matmul(x), axis=1)
             else:
                 self.matmul = matmul
         else:
             einrule = "bnf,rfg->brng" if self.is_first_layer else "brnf,rfg->brng"
-            self.matmul = lambda inputs: tf.einsum(einrule, inputs, self.kernel)
+            self.matmul = lambda inputs: tf.einsum(einrule, inputs, self.multi_kernel)
 
     def call(self, inputs):
         """