Cleanup - 2 (deepchem#4113)

* dftutils update

* update dftutils

* change testing env from dqc to torch

* added spin value

deepchem/utils/dftutils.py

@@ -11,11 +11,7 @@
 except Exception as e:
     warnings.warn("Could not import torch. Skipping tests." + str(e))
 
-try:
-    import xitorch as xt
-except Exception as e:
-    warnings.warn("Could not import xitorch. Skipping tests." + str(e))
-
+from deepchem.utils.differentiation_utils import EditableModule
 
 T = TypeVar('T')
 
@@ -231,7 +227,7 @@ def hashstr(s: str) -> str:
     return str(hashlib.blake2s(str.encode(s)).hexdigest())
 
 
-class BaseGrid(xt.EditableModule):
+class BaseGrid(EditableModule):
     """
     Interface to DQC's BaseGrid class. BaseGrid is a class that regulates the integration points over the spatial
     dimensions.

deepchem/utils/test/test_dftutils.py

@@ -9,11 +9,9 @@
     warnings.warn("Could not import torch. Skipping tests." + str(e))
 
 
-@pytest.mark.dqc
+@pytest.mark.torch
 def test_dftutils():
-    import dqc
-    from dqc.system.mol import Mol
-    from dqc.qccalc.ks import KS
+    from deepchem.utils.dft_utils import parse_moldesc, Mol, KS
     from deepchem.utils.dftutils import KSCalc
     system = {
         'type': 'mol',
@@ -22,16 +20,16 @@ def test_dftutils():
             'basis': '6-311++G(3df,3pd)'
         }
     }
-    atomzs, atomposs = dqc.parse_moldesc(system["kwargs"]["moldesc"])
-    mol = Mol(**system["kwargs"])
+    atomzs, atomposs = parse_moldesc(system["kwargs"]["moldesc"])
+    mol = Mol(**system["kwargs"], spin=0.0)
     qc = KS(mol, xc='lda_x').run()
     qcs = KSCalc(qc)
     a = qcs.energy()
     b = torch.tensor(-99.1360, dtype=torch.float64)
     assert torch.allclose(a, b)
 
 
-@pytest.mark.dqc
+@pytest.mark.torch
 def test_SpinParam_sum():
     from deepchem.utils.dftutils import SpinParam
     dens_u = torch.rand(10)
@@ -41,7 +39,7 @@ def test_SpinParam_sum():
     assert torch.all(sp.sum().eq(dens_u + dens_d)).item()
 
 
-@pytest.mark.dqc
+@pytest.mark.torch
 def test_SpinParam_reduce():
     from deepchem.utils.dftutils import SpinParam
     dens_u = torch.rand(10)
@@ -54,7 +52,7 @@ def fcn(a, b):
     assert torch.all(sp.reduce(fcn).eq(dens_u * dens_d)).item()
 
 
-@pytest.mark.dqc
+@pytest.mark.torch
 def test_str():
     from deepchem.utils.dftutils import hashstr
     s = "hydrogen fluoride"