fix: bug in variables ordering in NormalizedReluBounding (ecmwf#98)

This bug is fixed by making sure that self.norm_min_val follows the same order as self.data_index.

---------

Reviewed-by: @sahahner

Author: lzampier

models/src/anemoi/models/layers/bounding.py

@@ -135,6 +135,8 @@ def __init__(
                 "The length of the min_val list must match the number of variables in NormalizedReluBounding."
             )
 
+        # Compute normalized min values
+        self.data_index = [name_to_index[var] for var in variables]
         self.norm_min_val = torch.zeros(len(variables))
         for ii, variable in enumerate(variables):
             stat_index = self.name_to_index_stats[variable]

models/tests/layers/test_bounding.py

@@ -67,7 +67,6 @@ def test_normalized_relu_bounding(config, name_to_index, name_to_index_stats, in
         name_to_index_stats=name_to_index_stats,
     )
     output = bounding(input_tensor.clone())
-    # breakpoint()
     expected_output = torch.tensor([[2.0, 2.0, 3.0], [4.0, 0.1111, 6.0], [2.0, 0.5, 0.5]])
     assert torch.allclose(output, expected_output, atol=1e-4)