diff --git a/src/fairchem/core/preprocessing/atoms_to_graphs.py b/src/fairchem/core/preprocessing/atoms_to_graphs.py
index fa679a262..27dc664a3 100644
--- a/src/fairchem/core/preprocessing/atoms_to_graphs.py
+++ b/src/fairchem/core/preprocessing/atoms_to_graphs.py
@@ -185,14 +185,14 @@ def convert(self, atoms: ase.Atoms, sid=None):
         cell = np.array(atoms.get_cell(complete=True), copy=True)
         positions = wrap_positions(positions, cell, pbc=pbc, eps=0)
 
-        atomic_numbers = torch.Tensor(atoms.get_atomic_numbers())
+        atomic_numbers = torch.tensor(atoms.get_atomic_numbers(), dtype=torch.uint8)
         positions = torch.from_numpy(positions).float()
         cell = torch.from_numpy(cell).view(1, 3, 3).float()
         natoms = positions.shape[0]
 
         # initialized to torch.zeros(natoms) if tags missing.
         # https://wiki.fysik.dtu.dk/ase/_modules/ase/atoms.html#Atoms.get_tags
-        tags = torch.Tensor(atoms.get_tags())
+        tags = torch.tensor(atoms.get_tags(), dtype=torch.int)
 
         # put the minimum data in torch geometric data object
         data = Data(
@@ -228,10 +228,15 @@ def convert(self, atoms: ase.Atoms, sid=None):
             energy = atoms.get_potential_energy(apply_constraint=False)
             data.energy = energy
         if self.r_forces:
-            forces = torch.Tensor(atoms.get_forces(apply_constraint=False))
+            forces = torch.tensor(
+                atoms.get_forces(apply_constraint=False), dtype=torch.float32
+            )
             data.forces = forces
         if self.r_stress:
-            stress = torch.Tensor(atoms.get_stress(apply_constraint=False, voigt=False))
+            stress = torch.tensor(
+                atoms.get_stress(apply_constraint=False, voigt=False),
+                dtype=torch.float32,
+            )
             data.stress = stress
         if self.r_distances and self.r_edges:
             data.distances = edge_distances
@@ -245,13 +250,13 @@ def convert(self, atoms: ase.Atoms, sid=None):
                         fixed_idx[constraint.index] = 1
             data.fixed = fixed_idx
         if self.r_pbc:
-            data.pbc = torch.tensor(atoms.pbc)
+            data.pbc = torch.tensor(atoms.pbc, dtype=torch.bool)
         if self.r_data_keys is not None:
             for data_key in self.r_data_keys:
                 data[data_key] = (
                     atoms.info[data_key]
                     if isinstance(atoms.info[data_key], (int, float, str))
-                    else torch.Tensor(atoms.info[data_key])
+                    else torch.tensor(atoms.info[data_key])
                 )
 
         return data