diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 0e7ebbd5b7..2a155c8b88 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -52,6 +52,8 @@ jobs:
       run: pip install -e '.[testing]'
     - name: Run Pytest
       run: python -m pytest -s -v
+    - name: Run Pytest (lazy)
+      run: LAZY=1 python -m pytest -s -v
 
   testtorch:
     name: Torch Tests
@@ -70,6 +72,8 @@ jobs:
       run: pip install -e '.[testing]'
     - name: Run Pytest
       run: TORCH=1 python -m pytest -s -v
+    - name: Run Pytest (lazy)
+      run: LAZY=1 TORCH=1 python -m pytest -s -v
 
   testgpu:
     name: GPU Tests
@@ -94,6 +98,8 @@ jobs:
       run: pip install -e '.[gpu,testing]'
     - name: Run Pytest
       run: GPU=1 python -m pytest -s -v
+    - name: Run Pytest (lazy)
+      run: LAZY=1 GPU=1 python -m pytest -s -v
 
   testmypy:
     name: Mypy Tests
diff --git a/test/test_mnist.py b/test/test_mnist.py
index 45cc3d8e30..6ccb295c04 100644
--- a/test/test_mnist.py
+++ b/test/test_mnist.py
@@ -81,21 +81,21 @@ class TestMNIST(unittest.TestCase):
     np.random.seed(1337)
     model = TinyConvNet()
     optimizer = optim.Adam(model.parameters(), lr=0.001)
-    train(model, X_train, Y_train, optimizer, steps=200)
+    train(model, X_train, Y_train, optimizer, steps=100)
     assert evaluate(model, X_test, Y_test) > 0.95
 
   def test_sgd(self):
     np.random.seed(1337)
     model = TinyBobNet()
     optimizer = optim.SGD(model.parameters(), lr=0.001)
-    train(model, X_train, Y_train, optimizer, steps=1000)
+    train(model, X_train, Y_train, optimizer, steps=600)
     assert evaluate(model, X_test, Y_test) > 0.95
 
   def test_rmsprop(self):
     np.random.seed(1337)
     model = TinyBobNet()
     optimizer = optim.RMSprop(model.parameters(), lr=0.0002)
-    train(model,  X_train, Y_train, optimizer, steps=1000)
+    train(model,  X_train, Y_train, optimizer, steps=400)
     assert evaluate(model, X_test, Y_test) > 0.95
 
 if __name__ == '__main__':