More NONDET_TOL

grimme-lab · Aug 26, 2024 · d19679f · d19679f
1 parent 9847814
commit d19679f
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Showing 6 changed files with 15 additions and 23 deletions.
diff --git a/test/test_coulomb/test_es2_shell.py b/test/test_coulomb/test_es2_shell.py
@@ -34,7 +34,7 @@
 from dxtb._src.param.utils import get_elem_param
 from dxtb._src.typing import DD, Tensor
 
-from ..conftest import DEVICE
+from ..conftest import DEVICE, NONDET_TOL
 from .samples import samples
 
 sample_list = ["MB16_43_07", "MB16_43_08", "SiH4"]
@@ -129,7 +129,7 @@ def func(p: Tensor):
         cache = es.get_cache(numbers, p, ihelp)
         return es.get_shell_energy(qsh, cache)
 
-    assert dgradcheck(func, pos)
+    assert dgradcheck(func, pos, nondet_tol=NONDET_TOL)
 
 
 @pytest.mark.grad
@@ -160,4 +160,4 @@ def func(gexp: Tensor, hubbard: Tensor):
         cache = es.get_cache(numbers, positions, ihelp)
         return es.get_shell_energy(qsh, cache)
 
-    assert dgradcheck(func, (gexp, hubbard))
+    assert dgradcheck(func, (gexp, hubbard), nondet_tol=NONDET_TOL)
diff --git a/test/test_coulomb/test_es3.py b/test/test_coulomb/test_es3.py
@@ -31,7 +31,7 @@
 from dxtb._src.param.utils import get_elem_param
 from dxtb._src.typing import DD, Tensor
 
-from ..conftest import DEVICE
+from ..conftest import DEVICE, NONDET_TOL
 from .samples import samples
 
 sample_list = ["MB16_43_01", "MB16_43_02", "SiH4_atom"]
@@ -120,4 +120,4 @@ def func(hubbard_derivs: Tensor):
         cache = es.get_cache(numbers=numbers, ihelp=ihelp)
         return es.get_atom_energy(qat, cache)
 
-    assert dgradcheck(func, hd)
+    assert dgradcheck(func, hd, nondet_tol=NONDET_TOL)
diff --git a/test/test_coulomb/test_grad_atom.py b/test/test_coulomb/test_grad_atom.py
@@ -84,8 +84,6 @@ def test_single(dtype: torch.dtype, name: str) -> None:
     assert pytest.approx(ref.cpu(), abs=tol) == egrad.cpu()
     assert pytest.approx(egrad.cpu(), abs=tol) == agrad.cpu()
 
-    pos.detach_()
-
 
 @pytest.mark.parametrize("dtype", [torch.float, torch.double])
 @pytest.mark.parametrize("name1", ["SiH4_atom"])
@@ -145,8 +143,6 @@ def test_batch(dtype: torch.dtype, name1: str, name2: str) -> None:
     assert pytest.approx(ref.cpu(), abs=tol) == egrad.cpu()
     assert pytest.approx(egrad.cpu(), abs=tol) == agrad.cpu()
 
-    pos.detach_()
-
 
 def calc_numerical_gradient(
     numbers: Tensor, positions: Tensor, ihelp: IndexHelper, charges: Tensor

diff --git a/test/test_coulomb/test_grad_atom_param.py b/test/test_coulomb/test_grad_atom_param.py
@@ -31,7 +31,7 @@
 from dxtb._src.param import get_elem_param
 from dxtb._src.typing import DD, Callable, Tensor
 
-from ..conftest import DEVICE
+from ..conftest import DEVICE, NONDET_TOL
 from .samples import samples
 
 sample_list = ["LiH", "SiH4", "MB16_43_01"]
@@ -81,7 +81,7 @@ def test_grad_param(dtype: torch.dtype, name: str) -> None:
     gradient from `torch.autograd.gradcheck`.
     """
     func, diffvars = gradcheck_param(dtype, name)
-    assert dgradcheck(func, diffvars, atol=tol)
+    assert dgradcheck(func, diffvars, atol=tol, nondet_tol=NONDET_TOL)
 
 
 @pytest.mark.grad
@@ -93,7 +93,7 @@ def test_gradgrad_param(dtype: torch.dtype, name: str) -> None:
     gradient from `torch.autograd.gradgradcheck`.
     """
     func, diffvars = gradcheck_param(dtype, name)
-    assert dgradgradcheck(func, diffvars, atol=tol)
+    assert dgradgradcheck(func, diffvars, atol=tol, nondet_tol=NONDET_TOL)
 
 
 def gradcheck_param_batch(dtype: torch.dtype, name1: str, name2: str) -> tuple[
@@ -157,7 +157,7 @@ def test_grad_param_batch(dtype: torch.dtype, name1: str, name2: str) -> None:
     # same for both values.
     diffvars[0].requires_grad_(False)
 
-    assert dgradcheck(func, diffvars, atol=tol)
+    assert dgradcheck(func, diffvars, atol=tol, nondet_tol=NONDET_TOL)
 
 
 @pytest.mark.grad
@@ -177,4 +177,4 @@ def test_gradgrad_param_batch(dtype: torch.dtype, name1: str, name2: str) -> Non
     # same for both values.
     diffvars[0].requires_grad_(False)
 
-    assert dgradgradcheck(func, diffvars, atol=tol)
+    assert dgradgradcheck(func, diffvars, atol=tol, nondet_tol=NONDET_TOL)
diff --git a/test/test_coulomb/test_grad_atom_pos.py b/test/test_coulomb/test_grad_atom_pos.py
@@ -31,7 +31,7 @@
 from dxtb._src.param import get_elem_param
 from dxtb._src.typing import DD, Callable, Tensor
 
-from ..conftest import DEVICE
+from ..conftest import DEVICE, NONDET_TOL
 from .samples import samples
 
 sample_list = ["LiH", "SiH4", "MB16_43_01"]
@@ -85,7 +85,7 @@ def test_grad_pos(dtype: torch.dtype, name: str) -> None:
     gradient from `torch.autograd.gradcheck`.
     """
     func, diffvars = gradcheck_pos(dtype, name)
-    assert dgradcheck(func, diffvars, atol=tol)
+    assert dgradcheck(func, diffvars, atol=tol, nondet_tol=NONDET_TOL)
 
 
 @pytest.mark.grad
@@ -97,7 +97,7 @@ def test_gradgrad_pos(dtype: torch.dtype, name: str) -> None:
     gradient from `torch.autograd.gradgradcheck`.
     """
     func, diffvars = gradcheck_pos(dtype, name)
-    assert dgradgradcheck(func, diffvars, atol=tol)
+    assert dgradgradcheck(func, diffvars, atol=tol, nondet_tol=NONDET_TOL)
 
 
 def gradcheck_pos_batch(
@@ -156,7 +156,7 @@ def test_grad_pos_batch(dtype: torch.dtype, name1: str, name2: str) -> None:
     gradient from `torch.autograd.gradcheck`.
     """
     func, diffvars = gradcheck_pos_batch(dtype, name1, name2)
-    assert dgradcheck(func, diffvars, atol=tol)
+    assert dgradcheck(func, diffvars, atol=tol, nondet_tol=NONDET_TOL)
 
 
 @pytest.mark.grad
@@ -169,4 +169,4 @@ def test_gradgrad_pos_batch(dtype: torch.dtype, name1: str, name2: str) -> None:
     gradient from `torch.autograd.gradgradcheck`.
     """
     func, diffvars = gradcheck_pos_batch(dtype, name1, name2)
-    assert dgradgradcheck(func, diffvars, atol=tol)
+    assert dgradgradcheck(func, diffvars, atol=tol, nondet_tol=NONDET_TOL)
diff --git a/test/test_coulomb/test_grad_shell.py b/test/test_coulomb/test_grad_shell.py
@@ -82,8 +82,6 @@ def test_single(dtype: torch.dtype, name: str) -> None:
     assert pytest.approx(ref.cpu(), abs=tol) == egrad.cpu()
     assert pytest.approx(egrad.cpu(), abs=tol) == agrad.cpu()
 
-    pos.detach_()
-
 
 @pytest.mark.parametrize("dtype", [torch.float, torch.double])
 @pytest.mark.parametrize("name1", ["SiH4"])
@@ -144,8 +142,6 @@ def test_batch(dtype: torch.dtype, name1: str, name2: str) -> None:
     assert pytest.approx(ref.cpu(), abs=tol) == egrad.cpu()
     assert pytest.approx(egrad.cpu(), abs=tol) == agrad.cpu()
 
-    pos.detach_()
-
 
 def calc_numerical_gradient(
     numbers: Tensor, positions: Tensor, ihelp: IndexHelper, charges: Tensor