fix docstring in app

doc/source/cv.rst

@@ -4,7 +4,11 @@ Federated Computer Vision  Module References
 federatedscope.cv.dataset
 -----------------------
 
-.. automodule:: federatedscope.cv.dataset
+.. automodule:: federatedscope.cv.dataset.leaf
+    :members:
+    :private-members:
+
+.. automodule:: federatedscope.cv.dataset.leaf_cv
     :members:
     :private-members:
 

federatedscope/cv/dataloader/dataloader.py

@@ -3,14 +3,20 @@
 
 
 def load_cv_dataset(config=None):
-    r"""
-    return {
-                'client_id': {
-                    'train': DataLoader(),
-                    'test': DataLoader(),
-                    'val': DataLoader()
-                }
-            }
+    """
+    Return the dataset of ``femnist`` or ``celeba``.
+
+    Args:
+        config: configurations for FL, see ``federatedscope.core.configs``
+
+    Returns:
+        FL dataset dict, with ``client_id`` as key.
+
+    Note:
+      ``load_cv_dataset()`` will return a dict as shown below:
+        ```
+        {'client_id': {'train': dataset, 'test': dataset, 'val': dataset}}
+        ```
     """
     splits = config.data.splits
 

federatedscope/cv/dataset/leaf.py

@@ -18,7 +18,8 @@ def is_exists(path, names):
 
 
 class LEAF(Dataset):
-    """Base class for LEAF dataset from "LEAF: A Benchmark for Federated Settings"
+    """
+    Base class for LEAF dataset from "LEAF: A Benchmark for Federated Settings"
 
     Arguments:
         root (str): root path.
@@ -91,7 +92,7 @@ def process(self):
 
 class LocalDataset(Dataset):
     """
-        Convert data list to torch Dataset to save memory usage.
+    Convert data list to torch Dataset to save memory usage.
     """
     def __init__(self,
                  Xs,

federatedscope/cv/trainer/trainer.py

@@ -3,6 +3,9 @@
 
 
 class CVTrainer(GeneralTorchTrainer):
+    """
+    ``CVTrainer`` is the same as ``core.trainers.GeneralTorchTrainer``.
+    """
     pass
 
 

federatedscope/nlp/dataloader/dataloader.py

@@ -5,14 +5,21 @@
 
 
 def load_nlp_dataset(config=None):
-    r"""
-    return {
-                'client_id': {
-                    'train': DataLoader(),
-                    'test': DataLoader(),
-                    'val': DataLoader()
-                }
-            }
+    """
+    Return the dataset of ``shakespeare``, ``subreddit``, ``twitter``, \
+    or ``synthetic``.
+
+    Args:
+        config: configurations for FL, see ``federatedscope.core.configs``
+
+    Returns:
+        FL dataset dict, with ``client_id`` as key.
+
+    Note:
+      ``load_nlp_dataset()`` will return a dict as shown below:
+        ```
+        {'client_id': {'train': dataset, 'test': dataset, 'val': dataset}}
+        ```
     """
     splits = config.data.splits
 

federatedscope/nlp/trainer/trainer.py

@@ -4,6 +4,9 @@
 
 
 class NLPTrainer(GeneralTorchTrainer):
+    """
+    ``NLPTrainer`` is used for text data.
+    """
     def _hook_on_batch_forward(self, ctx):
         x, label = [move_to(_, ctx.device) for _ in ctx.data_batch]
         if isinstance(x, dict):