update: test_no_gradients

Author: kozistr

tests/test_gradients.py

@@ -2,12 +2,12 @@
 import torch
 
 from pytorch_optimizer.base.exception import NoSparseGradientError
-from pytorch_optimizer.optimizer import SAM, TRAC, WSAM, AdamP, Lookahead, load_optimizer
+from pytorch_optimizer.optimizer import SAM, TRAC, WSAM, AdamP, Lookahead, OrthoGrad, load_optimizer
 from tests.constants import NO_SPARSE_OPTIMIZERS, SPARSE_OPTIMIZERS, VALID_OPTIMIZER_NAMES
 from tests.utils import build_environment, simple_parameter, simple_sparse_parameter, sphere_loss
 
 
-@pytest.mark.parametrize('optimizer_name', [*VALID_OPTIMIZER_NAMES, 'lookahead', 'trac'])
+@pytest.mark.parametrize('optimizer_name', [*VALID_OPTIMIZER_NAMES, 'lookahead', 'trac', 'orthograd'])
 def test_no_gradients(optimizer_name):
     if optimizer_name in {'lomo', 'adalomo', 'adammini', 'demo'}:
         pytest.skip(f'skip {optimizer_name} optimizer.')
@@ -28,6 +28,8 @@ def test_no_gradients(optimizer_name):
         optimizer = Lookahead(load_optimizer('adamw')(params), k=1)
     elif optimizer_name == 'trac':
         optimizer = TRAC(load_optimizer('adamw')(params))
+    elif optimizer_name == 'orthograd':
+        optimizer = OrthoGrad(load_optimizer('adamw')(params))
     else:
         optimizer = load_optimizer(optimizer_name)(params)