calculate fibonacci sphere points only once

alphafold3_pytorch/alphafold3.py

@@ -5288,6 +5288,7 @@ def __init__(
         contact_mask_threshold: float = 8.0,
         is_fine_tuning: bool = False,
         weight_dict_config: dict = None,
+        fibonacci_sphere_n = 200, # more points equal better approximation at cost of compute
     ):
         super().__init__()
         self.compute_confidence_score = ComputeConfidenceScore(eps=eps)
@@ -5301,6 +5302,8 @@ def __init__(
         self.register_buffer("dist_breaks", dist_breaks)
         self.register_buffer('lddt_thresholds', torch.tensor([0.5, 1.0, 2.0, 4.0]))
 
+        # for rsa calculation
+
         atom_type_radii = tensor([
             1.65,    # 0 - nitrogen
             1.87,    # 1 - carbon alpha
@@ -5319,6 +5322,31 @@ def __init__(
 
         self.register_buffer('atom_radii', atom_type_radii, persistent = False)
 
+        # constitute the fibonacci sphere
+
+        num_surface_dots = fibonacci_sphere_n * 2 + 1
+        golden_ratio = 1. + sqrt(5.) / 2
+        weight = (4. * pi) / num_surface_dots
+
+        arange = torch.arange(-fibonacci_sphere_n, fibonacci_sphere_n + 1, device = self.device) # for example, N = 3 -> [-3, -2, -1, 0, 1, 2, 3]
+
+        lat = torch.asin((2. * arange) / num_surface_dots)
+        lon = torch.fmod(arange, golden_ratio) * 2 * pi / golden_ratio
+
+        # ein:
+        # sd - surface dots
+        # c - coordinate (3)
+        # i, j - source and target atom
+
+        unit_surface_dots: Float['sd 3'] = torch.stack((
+            lon.sin() * lat.cos(),
+            lon.cos() * lat.cos(),
+            lat.sin()
+        ), dim = -1)
+
+        self.register_buffer('unit_surface_dots', unit_surface_dots)
+        self.surface_weight = weight
+
     @property
     def device(self):
         return self.atom_radii.device
@@ -5651,7 +5679,6 @@ def calc_atom_access_surface_score(
         atom_pos: Float['m 3'],
         atom_type: Int['m'],
         molecule_atom_lens: Int['n'] | None = None,
-        fibonacci_sphere_n = 200, # more points equal better approximation at cost of compute
         atom_distance_min_thres = 1e-4
     ) -> Float['m'] | Float['n']:
 
@@ -5666,28 +5693,6 @@ def calc_atom_access_surface_score(
 
         # write custom RSA function here
 
-        # first constitute the fibonacci sphere
-
-        num_surface_dots = fibonacci_sphere_n * 2 + 1
-        golden_ratio = 1. + sqrt(5.) / 2
-        weight = (4. * pi) / num_surface_dots
-
-        arange = torch.arange(-fibonacci_sphere_n, fibonacci_sphere_n + 1, device = self.device) # for example, N = 3 -> [-3, -2, -1, 0, 1, 2, 3]
-
-        lat = torch.asin((2. * arange) / num_surface_dots)
-        lon = torch.fmod(arange, golden_ratio) * 2 * pi / golden_ratio
-
-        # ein:
-        # sd - surface dots
-        # c - coordinate (3)
-        # i, j - source and target atom
-
-        unit_surface_dots: Float['sd 3'] = torch.stack((
-            lon.sin() * lat.cos(),
-            lon.cos() * lat.cos(),
-            lat.sin()
-        ), dim = -1)
-
         # get atom relative positions + distance
         # for determining whether to include pairs of atom in calculation for the `free` adjective
 
@@ -5715,7 +5720,7 @@ def calc_atom_access_surface_score(
 
         # overall logic
 
-        surface_dots = einx.multiply('m, sd c -> m sd c', atom_radii, unit_surface_dots)
+        surface_dots = einx.multiply('m, sd c -> m sd c', atom_radii, self.unit_surface_dots)
 
         dist_from_surface_dots_sq = einx.subtract('i j c, i sd c -> i sd j c', atom_rel_pos, surface_dots).pow(2).sum(dim = -1)
 
@@ -5725,7 +5730,7 @@ def calc_atom_access_surface_score(
 
         is_free = reduce(target_atom_close_or_not_included, 'i sd j -> i sd', 'all') # basically the most important line, calculating whether an atom is free by some distance measure
 
-        score = reduce(is_free.float() * weight, 'm sd -> m', 'sum')
+        score = reduce(is_free.float() * self.surface_weight, 'm sd -> m', 'sum')
 
         per_atom_access_surface_score = score * atom_radii_sq
 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "alphafold3-pytorch"
-version = "0.5.55"
+version = "0.5.56"
 description = "Alphafold 3 - Pytorch"
 authors = [
     { name = "Phil Wang", email = "[email protected]" },