fix deprecated tng and abstract ligntning (#644)

pytorch_lightning/core/lightning.py

@@ -1,6 +1,8 @@
 import os
 import warnings
 import collections
+import logging
+from abc import ABC, abstractmethod
 from argparse import Namespace
 
 import torch
@@ -11,12 +13,11 @@ from pytorch_lightning.core.grads import GradInformation
 from pytorch_lightning.core.hooks import ModelHooks
 from pytorch_lightning.core.memory import ModelSummary
 from pytorch_lightning.core.saving import ModelIO
-from pytorch_lightning.trainer.trainer_io import load_hparams_from_tags_csv
-import logging
+from pytorch_lightning.trainer.training_io import load_hparams_from_tags_csv
 from pytorch_lightning.overrides.data_parallel import LightningDistributedDataParallel
 
 
-class LightningModule(GradInformation, ModelIO, ModelHooks):
+class LightningModule(ABC, GradInformation, ModelIO, ModelHooks):
     """
     A LightningModule has the following properties which you can access at any time
 
@@ -96,6 +97,7 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
         self.use_ddp2 = False
         self.use_amp = False
 
+    @abstractmethod
     def forward(self, *args, **kwargs):
         """
         Expand model in into whatever you need.
@@ -103,8 +105,8 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
         :param x:
         :return:
         """
-        raise NotImplementedError
 
+    @abstractmethod
     def training_step(self, *args, **kwargs):
         """return loss, dict with metrics for tqdm
 
@@ -169,7 +171,6 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
         You can also return a -1 instead of a dict to stop the current loop. This is useful
          if you want to break out of the current training epoch early.
         """
-        raise NotImplementedError
 
     def training_end(self, *args, **kwargs):
         """return loss, dict with metrics for tqdm
@@ -602,7 +603,7 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
             # all ports should be in the 10k+ range
             default_port = int(default_port) + 15000
 
-        except Exception as e:
+        except Exception:
             default_port = 12910
 
         # if user gave a port number, use that one instead
@@ -648,6 +649,7 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
 
         return model, optimizers
 
+    @abstractmethod
     def configure_optimizers(self):
         """Return a list of optimizers and a list of schedulers (could be empty)
 
@@ -694,7 +696,6 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
          override the `optimizer_step` hook.
 
         """
-        raise NotImplementedError
 
     def optimizer_step(self, epoch, batch_idx, optimizer, optimizer_idx, second_order_closure=None):
         """Do something instead of the standard optimizer behavior
@@ -817,6 +818,7 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
         return splits
 
     @data_loader
+    @abstractmethod
     def train_dataloader(self):
         """Implement a PyTorch DataLoader
 
@@ -844,7 +846,6 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
 
 
         """
-        raise NotImplementedError
 
     @data_loader
     def tng_dataloader(self):
@@ -852,13 +853,10 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
 
         .. warning:: Deprecated in v0.5.0. use train_dataloader instead.
         """
-        try:
-            output = self.tng_dataloader()
-            warnings.warn("`tng_dataloader` has been renamed to `train_dataloader` since v0.5.0"
-                          " and will be removed in v0.8.0", DeprecationWarning)
-            return output
-        except NotImplementedError:
-            raise NotImplementedError
+        output = self.train_dataloader()
+        warnings.warn("`tng_dataloader` has been renamed to `train_dataloader` since v0.5.0"
+                      " and will be removed in v0.8.0", DeprecationWarning)
+        return output
 
     @data_loader
     def test_dataloader(self):

pytorch_lightning/trainer/trainer.py

@@ -26,7 +26,7 @@ from pytorch_lightning.trainer.evaluation_loop import TrainerEvaluationLoopMixin
 from pytorch_lightning.trainer.logging import TrainerLoggingMixin
 from pytorch_lightning.trainer.model_hooks import TrainerModelHooksMixin
 from pytorch_lightning.trainer.training_loop import TrainerTrainLoopMixin
-from pytorch_lightning.trainer.trainer_io import TrainerIOMixin
+from pytorch_lightning.trainer.training_io import TrainerIOMixin
 from pytorch_lightning.trainer.training_tricks import TrainerTrainingTricksMixin
 from pytorch_lightning.utilities.debugging import MisconfigurationException
 

tests/test_trainer.py

@@ -15,7 +15,7 @@ from pytorch_lightning.testing import (
     LightningValidationMultipleDataloadersMixin,
     LightningTestMultipleDataloadersMixin,
 )
-from pytorch_lightning.trainer import trainer_io
+from pytorch_lightning.trainer import training_io
 from pytorch_lightning.trainer.logging import TrainerLoggingMixin
 
 
@@ -187,7 +187,7 @@ def test_loading_meta_tags(tmpdir):
     tags_path = logger.experiment.get_data_path(
         logger.experiment.name, logger.experiment.version
     ) + '/meta_tags.csv'
-    tags = trainer_io.load_hparams_from_tags_csv(tags_path)
+    tags = training_io.load_hparams_from_tags_csv(tags_path)
 
     assert tags.batch_size == 32 and tags.hidden_dim == 1000