rm EvalModel

Author: rohitgr7

tests/accelerators/test_ddp_spawn.py

@@ -20,7 +20,6 @@
 from pytorch_lightning.core import memory
 from pytorch_lightning.trainer import Trainer
 from pytorch_lightning.trainer.states import TrainerState
-from tests.base import EvalModelTemplate
 from tests.helpers import BoringModel
 from tests.helpers.datamodules import ClassifDataModule
 from tests.helpers.simple_models import ClassificationModel
@@ -72,7 +71,7 @@ def test_ddp_all_dataloaders_passed_to_fit(tmpdir):
     """Make sure DDP works with dataloaders passed to fit()"""
     tutils.set_random_master_port()
 
-    model = EvalModelTemplate()
+    model = BoringModel()
     fit_options = dict(train_dataloader=model.train_dataloader(), val_dataloaders=model.val_dataloader())
 
     trainer = Trainer(

tests/accelerators/test_dp.py

@@ -19,7 +19,6 @@
 import tests.helpers.utils as tutils
 from pytorch_lightning.callbacks import EarlyStopping
 from pytorch_lightning.core import memory
-from tests.base import EvalModelTemplate
 from tests.helpers import BoringModel
 from tests.helpers.datamodules import ClassifDataModule
 from tests.helpers.simple_models import ClassificationModel
@@ -76,7 +75,8 @@ def test_dp_test(tmpdir):
     import os
     os.environ['CUDA_VISIBLE_DEVICES'] = '0,1'
 
-    model = EvalModelTemplate()
+    dm = ClassifDataModule()
+    model = ClassificationModel()
     trainer = pl.Trainer(
         default_root_dir=tmpdir,
         max_epochs=2,
@@ -85,14 +85,14 @@ def test_dp_test(tmpdir):
         gpus=[0, 1],
         accelerator='dp',
     )
-    trainer.fit(model)
+    trainer.fit(model, datamodule=dm)
     assert 'ckpt' in trainer.checkpoint_callback.best_model_path
-    results = trainer.test()
+    results = trainer.test(datamodule=dm)
     assert 'test_acc' in results[0]
 
     old_weights = model.c_d1.weight.clone().detach().cpu()
 
-    results = trainer.test(model)
+    results = trainer.test(model, datamodule=dm)
     assert 'test_acc' in results[0]
 
     # make sure weights didn't change