added lazy decorator

pytorch_lightning/root_module/decorators.py

@@ -0,0 +1,17 @@
+
+def data_loader(fn):
+    """
+    Decorator to make any fx with this use the lazy property
+    :param fn:
+    :return:
+    """
+
+    attr_name = '_lazy_' + fn.__name__
+
+    @property
+    def _data_loader(self):
+        if not hasattr(self, attr_name):
+            setattr(self, attr_name, fn(self))
+        return getattr(self, attr_name)
+
+    return _data_loader

pytorch_lightning/root_module/root_module.py

@@ -1,11 +1,9 @@
-import os
 import torch
-import math
-
 from pytorch_lightning.root_module.memory import ModelSummary
 from pytorch_lightning.root_module.grads import GradInformation
 from pytorch_lightning.root_module.model_saving import ModelIO, load_hparams_from_tags_csv
 from pytorch_lightning.root_module.hooks import ModelHooks
+from pytorch_lightning.root_module.decorators import data_loader
 
 
 class LightningModule(GradInformation, ModelIO, ModelHooks):
@@ -26,11 +24,6 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
         # track if gpu was requested for checkpointing
         self.on_gpu = False
 
-        # computed vars for the dataloaders
-        self._tng_dataloader = None
-        self._val_dataloader = None
-        self._test_dataloader = None
-
     def forward(self, *args, **kwargs):
         """
         Expand model in into whatever you need.
@@ -91,7 +84,7 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
         for param in self.parameters():
             param.requires_grad = True
 
-    @property
+    @data_loader
     def tng_dataloader(self):
         """
         Implement a function to load an h5py of this data
@@ -99,7 +92,7 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
         """
         raise NotImplementedError
 
-    @property
+    @data_loader
     def test_dataloader(self):
         """
         Implement a function to load an h5py of this data
@@ -107,7 +100,7 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
         """
         raise NotImplementedError
 
-    @property
+    @data_loader
     def val_dataloader(self):
         """
         Implement a function to load an h5py of this data
@@ -142,3 +135,6 @@ class LightningModule(GradInformation, ModelIO, ModelHooks):
         model.load_model_specific(checkpoint)
         model.load_state_dict(checkpoint['state_dict'], strict=False)
         return model
+
+
+