diff --git a/docs/source-pytorch/common/trainer.rst b/docs/source-pytorch/common/trainer.rst
index cc8b57a182..caad2a9f21 100644
--- a/docs/source-pytorch/common/trainer.rst
+++ b/docs/source-pytorch/common/trainer.rst
@@ -1597,6 +1597,16 @@ The number of epochs run.
     if trainer.current_epoch >= 10:
         ...
 
+
+datamodule
+**********
+
+The current datamodule, which is used by the trainer.
+
+.. code-block:: python
+
+    used_datamodule = trainer.datamodule
+
 is_last_batch
 *************
 
@@ -1694,6 +1704,17 @@ The metrics sent to the progress bar.
     assert progress_bar_metrics["a_val"] == 2
 
 
+predict_dataloaders
+*******************
+
+The current predict dataloaders of the trainer.
+Note that property returns a list of predict dataloaders.
+
+.. code-block:: python
+
+    used_predict_dataloaders = trainer.predict_dataloaders
+
+
 estimated_stepping_batches
 **************************
 
@@ -1773,3 +1794,37 @@ both conditions are met. If any of these arguments is not set, it won't be consi
     trainer = Trainer(min_steps=5, min_epochs=5, max_epochs=100)
     model = LitModel()
     trainer.fit(model)
+
+
+train_dataloader
+****************
+
+The current train dataloader of the trainer.
+
+.. code-block:: python
+
+    used_train_dataloader = trainer.train_dataloader
+
+
+test_dataloaders
+****************
+
+The current test dataloaders of the trainer.
+Note that property returns a list of test dataloaders.
+
+
+.. code-block:: python
+
+    used_test_dataloaders = trainer.test_dataloaders
+
+val_dataloaders
+***************
+
+
+The current val dataloaders of the trainer.
+Note that property returns a list of val dataloaders.
+
+
+.. code-block:: python
+
+    used_val_dataloaders = trainer.val_dataloaders
diff --git a/docs/source-pytorch/data/datamodule.rst b/docs/source-pytorch/data/datamodule.rst
index fbee2e80e4..4a6bce7029 100644
--- a/docs/source-pytorch/data/datamodule.rst
+++ b/docs/source-pytorch/data/datamodule.rst
@@ -412,6 +412,10 @@ the method runs on the correct devices).
     dm.setup(stage="test")
     trainer.test(datamodule=dm)
 
+You can access the current used datamodule of a trainer via ``trainer.datamodule`` and the current used
+dataloaders via ``trainer.train_dataloader``, ``trainer.val_dataloaders`` and ``trainer.test_dataloaders``.
+
+
 ----------------
 
 *****************************