diff --git a/pl_bolts/models/self_supervised/cpc/cpc_module.py b/pl_bolts/models/self_supervised/cpc/cpc_module.py
index 926a4f6b25..d325fc55cf 100644
--- a/pl_bolts/models/self_supervised/cpc/cpc_module.py
+++ b/pl_bolts/models/self_supervised/cpc/cpc_module.py
@@ -124,7 +124,7 @@ def forward(self, img_1):
         Z = self.encoder(img_1)
 
         # non cpc resnets return a list
-        if self.hparams.encoder != "cpc_encoder":
+        if self.hparams.encoder_name != "cpc_encoder":
             Z = Z[0]
 
         # (?) -> (b, -1, nb_feats, nb_feats)
diff --git a/tests/models/self_supervised/test_models.py b/tests/models/self_supervised/test_models.py
index 03d3f98170..59f0ca0519 100644
--- a/tests/models/self_supervised/test_models.py
+++ b/tests/models/self_supervised/test_models.py
@@ -15,9 +15,7 @@
 from tests import _MARK_REQUIRE_GPU
 
 
-# todo: seems to be failing on GH Actions for min config
 @pytest.mark.skipif(**_MARK_REQUIRE_GPU)
-@pytest.mark.skip(reason="RuntimeError: Given groups=1, weight of size [256, 2048, 1, 1], expected input[2, 1, 32, 32]")
 def test_cpcv2(tmpdir, datadir):
     datamodule = CIFAR10DataModule(data_dir=datadir, num_workers=0, batch_size=2)
     datamodule.train_transforms = CPCTrainTransformsCIFAR10()
@@ -30,7 +28,12 @@ def test_cpcv2(tmpdir, datadir):
         online_ft=True,
         num_classes=datamodule.num_classes,
     )
-    trainer = Trainer(fast_dev_run=True, default_root_dir=tmpdir)
+
+    # FIXME: workaround for bug caused by
+    # https://github.com/PyTorchLightning/lightning-bolts/commit/2e903c333c37ea83394c7da2ce826de1b82fb356
+    model.datamodule = datamodule
+
+    trainer = Trainer(fast_dev_run=True, default_root_dir=tmpdir, gpus=1 if torch.cuda.device_count() > 0 else 0)
     trainer.fit(model, datamodule=datamodule)