Fix unused weights warning in coupling flow

vpratz · vpratz · commit 5d4337676934 · 2025-02-26T19:58:57.000Z
The projector weights were created even when no residual connections were required, leading to warnings as their gradients were not present, as they had no influence on the loss. Fixes #331
diff --git a/bayesflow/networks/mlp/hidden_block.py b/bayesflow/networks/mlp/hidden_block.py
@@ -51,7 +51,7 @@ def call(self, inputs: Tensor, training: bool = False, **kwargs) -> Tensor:
     def build(self, input_shape):
         self.dense.build(input_shape)
 
-        if input_shape[-1] != self.units:
+        if input_shape[-1] != self.units and self.residual:
             self.projector = self.add_weight(
                 shape=(input_shape[-1], self.units), initializer="glorot_uniform", trainable=True, name="projector"
             )

Original file line number	Diff line number	Diff line change
`@@ -51,7 +51,7 @@ def call(self, inputs: Tensor, training: bool = False, **kwargs) -> Tensor:`
`51`	`51`	`def build(self, input_shape):`
`52`	`52`	`self.dense.build(input_shape)`
`53`	`53`
`54`		`- if input_shape[-1] != self.units:`
	`54`	`+ if input_shape[-1] != self.units and self.residual:`
`55`	`55`	`self.projector = self.add_weight(`
`56`	`56`	`shape=(input_shape[-1], self.units), initializer="glorot_uniform", trainable=True, name="projector"`
`57`	`57`	`)`