update: test_betas

Author: kozistr

tests/test_optimizer_parameters.py

@@ -4,7 +4,7 @@
 
 from pytorch_optimizer import load_optimizers
 
-VALID_OPTIMIZER_NAMES: List[str] = [
+OPTIMIZER_NAMES: List[str] = [
     'adamp',
     'sgdp',
     'madgrad',
@@ -19,23 +19,47 @@
     'lamb',
 ]
 
+BETA_OPTIMIZER_NAMES: List[str] = [
+    'adabelief',
+    'adabound',
+    'adahessian',
+    'admap',
+    'diffgrad',
+    'diffrgrad',
+    'lamb',
+    'radam',
+    'ranger',
+    'ranger21',
+]
+
 
-@pytest.mark.parametrize('optimizer_names', VALID_OPTIMIZER_NAMES)
+@pytest.mark.parametrize('optimizer_names', OPTIMIZER_NAMES)
 def test_learning_rate(optimizer_names):
     with pytest.raises(ValueError):
         optimizer = load_optimizers(optimizer_names)
         optimizer(None, lr=-1e-2)
 
 
-@pytest.mark.parametrize('optimizer_names', VALID_OPTIMIZER_NAMES)
+@pytest.mark.parametrize('optimizer_names', OPTIMIZER_NAMES)
 def test_epsilon(optimizer_names):
     with pytest.raises(ValueError):
         optimizer = load_optimizers(optimizer_names)
         optimizer(None, eps=-1e-6)
 
 
-@pytest.mark.parametrize('optimizer_names', VALID_OPTIMIZER_NAMES)
+@pytest.mark.parametrize('optimizer_names', OPTIMIZER_NAMES)
 def test_weight_decay(optimizer_names):
     with pytest.raises(ValueError):
         optimizer = load_optimizers(optimizer_names)
         optimizer(None, weight_decay=-1e-3)
+
+
+@pytest.mark.parametrize('optimizer_names', BETA_OPTIMIZER_NAMES)
+def test_betas(optimizer_names):
+    with pytest.raises(ValueError):
+        optimizer = load_optimizers(optimizer_names)
+        optimizer(None, betas=(-0.1, 0.1))
+
+    with pytest.raises(ValueError):
+        optimizer = load_optimizers(optimizer_names)
+        optimizer(None, betas=(0.1, -0.1))