From 153af166fada1f9b1892d95a9264ec43086be927 Mon Sep 17 00:00:00 2001
From: frostedoyster <bigi.f@libero.it>
Date: Thu, 8 Feb 2024 06:53:22 +0100
Subject: [PATCH] Remove static functions

---
 examples/power_spectrum.py         |  5 ++++-
 torch_spex/radial_basis.py         |  5 ++++-
 torch_spex/spherical_expansions.py | 10 ++++++++--
 3 files changed, 16 insertions(+), 4 deletions(-)

diff --git a/examples/power_spectrum.py b/examples/power_spectrum.py
index c7a185b..2deb87c 100644
--- a/examples/power_spectrum.py
+++ b/examples/power_spectrum.py
@@ -35,7 +35,10 @@ def forward(self, spex: TensorMap):
                 values=ps_values_ai,
                 samples=spex.block({"lam": 0, "a_i": a_i}).samples,
                 components=[],
-                properties=Labels.range("property", ps_values_ai.shape[-1])
+                properties=Labels(
+                    "property",
+                    torch.range(ps_values_ai.shape[-1], device=ps_values_ai.device).reshape(-1, 1)
+                )
             )
             keys.append([a_i])
             blocks.append(block)
diff --git a/torch_spex/radial_basis.py b/torch_spex/radial_basis.py
index 09ca8bc..e3cebf8 100644
--- a/torch_spex/radial_basis.py
+++ b/torch_spex/radial_basis.py
@@ -56,7 +56,10 @@ def __init__(self, hypers, all_species) -> None:
             self.is_alchemical = False
             self.n_pseudo_species = 0  # dummy for torchscript
             self.combination_matrix = torch.nn.Linear(1, 1)  # dummy for torchscript
-            self.species_neighbor_labels = Labels.empty("dummy")
+            self.species_neighbor_labels = Labels(
+                names=["dummy"],
+                values=torch.empty((0, 1), dtype=torch.int)
+            )
         
         self.apply_mlp = False
         if hypers["mlp"]:
diff --git a/torch_spex/spherical_expansions.py b/torch_spex/spherical_expansions.py
index cafa789..82d7378 100644
--- a/torch_spex/spherical_expansions.py
+++ b/torch_spex/spherical_expansions.py
@@ -356,7 +356,10 @@ def forward(self,
                     )
                 )
             else:
-                properties = Labels.range("n", n_max_l)
+                properties = Labels(
+                    names=["n"],
+                    values = torch.range(n_max_l, device=vector_expansion_l.device).reshape(n_max_l, 1)
+                )
             vector_expansion_blocks.append(
                 TensorBlock(
                     values = vector_expansion_l.reshape(vector_expansion_l.shape[0], 2*l+1, -1),
@@ -420,7 +423,10 @@ def get_cartesian_vectors(positions, cells, species, cell_shifts, centers, pairs
                 values = torch.tensor([-1, 0, 1], dtype=torch.int32, device=direction_vectors.device).reshape((-1, 1))
             )
         ],
-        properties = Labels.single().to(direction_vectors.device)
+        properties = Labels(
+            names=["_"],
+            values=torch.zeros((1, 1), device=direction_vectors.device)
+        )
     )
 
     return block