[doc] Update Dict Train Loader doc. (#6579)

* update doc

* update example

docs/source/advanced/multiple_loaders.rst

@@ -89,7 +89,24 @@ For more details please have a look at :paramref:`~pytorch_lightning.trainer.tra
             return loaders
 
 Furthermore, Lightning also supports that nested lists and dicts (or a combination) can
-be returned 
+be returned.
+
+.. testcode::
+
+    class LitModel(LightningModule):
+
+        def train_dataloader(self):
+
+            loader_a = torch.utils.data.DataLoader(range(8), batch_size=4)
+            loader_b = torch.utils.data.DataLoader(range(16), batch_size=2)
+
+            return {'a': loader_a, 'b': loader_b}
+
+        def training_step(self, batch, batch_idx):
+            # access a dictionnary with a batch from each dataloader
+            batch_a = batch["a"]
+            batch_b = batch["b"]
+
 
 .. testcode::
 
@@ -103,12 +120,29 @@ be returned
             loader_c = torch.utils.data.DataLoader(range(64), batch_size=4)
 
             # pass loaders as a nested dict. This will create batches like this:
-            # {'loader_a_b': {'a': batch from loader a, 'b': batch from loader b},
+            loaders = {
-            #  'loader_c_d': {'c': batch from loader c, 'd': batch from loader d}}
+                'loaders_a_b': {
-            loaders = {'loaders_a_b': {'a': loader_a, 'b': loader_b},
+                    'a': loader_a,
-                       'loaders_c_d': {'c': loader_c, 'd': loader_d}}
+                    'b': loader_b
+                },
+                'loaders_c_d': {
+                    'c': loader_c,
+                    'd': loader_d
+                }
+            }
             return loaders
 
+        def training_step(self, batch, batch_idx):
+            # access the data
+            batch_a_b = batch["loaders_a_b"]
+            batch_c_d = batch["loaders_c_d"]
+
+            batch_a = batch_a_b["a"]
+            batch_b = batch_a_b["a"]
+
+            batch_c = batch_c_d["c"]
+            batch_d = batch_c_d["d"]
+
 ----------
 
 Test/Val dataloaders