diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index a5c95dce9..8455c03bb 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -28,6 +28,11 @@ repos:
         args: ["--remove"]
       - id: mixed-line-ending
         args: ["--fix=lf"]
+  - repo: https://github.com/myint/docformatter
+    rev: v1.3.1
+    hooks:
+      - id: docformatter
+        args: ["--in-place", "--wrap-descriptions", "79"]
   - repo: local
     hooks:
       - id: clang-format
diff --git a/docs/api.rst b/docs/api.rst
index eb4778061..36eed8269 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -45,4 +45,4 @@ runner
 ops
 ------
 .. automodule:: mmcv.ops
-    :members:
\ No newline at end of file
+    :members:
diff --git a/docs/image.md b/docs/image.md
index 5e716d0be..adedf50ea 100644
--- a/docs/image.md
+++ b/docs/image.md
@@ -145,7 +145,7 @@ img_ = mmcv.impad(img, shape=(1000, 1200), pad_val=[100, 50, 200])
 # pad the image on left, right, top, bottom borders with all zeros
 img_ = mmcv.impad(img, padding=(10, 20, 30, 40), pad_val=0)
 
-# pad the image on left, right, top, bottom borders with different values 
+# pad the image on left, right, top, bottom borders with different values
 # for three channels.
 img_ = mmcv.impad(img, padding=(10, 20, 30, 40), pad_val=[100, 50, 200])
 
diff --git a/examples/train_cifar10.py b/examples/train_cifar10.py
index 7622b2cb9..63d90ee98 100644
--- a/examples/train_cifar10.py
+++ b/examples/train_cifar10.py
@@ -18,7 +18,7 @@ from mmcv.runner import DistSamplerSeedHook, Runner
 
 
 def accuracy(output, target, topk=(1, )):
-    """Computes the precision@k for the specified values of k"""
+    """Computes the precision@k for the specified values of k."""
     with torch.no_grad():
         maxk = max(topk)
         batch_size = target.size(0)
diff --git a/mmcv/cnn/__init__.py b/mmcv/cnn/__init__.py
index cb4f8f12f..4e30cd084 100644
--- a/mmcv/cnn/__init__.py
+++ b/mmcv/cnn/__init__.py
@@ -2,8 +2,8 @@
 from .alexnet import AlexNet
 from .bricks import (ACTIVATION_LAYERS, CONV_LAYERS, NORM_LAYERS,
                      PADDING_LAYERS, PLUGIN_LAYERS, UPSAMPLE_LAYERS,
-                     ContextBlock, ConvModule, GeneralizedAttention,
-                     NonLocal1d, NonLocal2d, NonLocal3d, Scale,
+                     ContextBlock, ConvModule, GeneralizedAttention, HSigmoid,
+                     HSwish, NonLocal1d, NonLocal2d, NonLocal3d, Scale,
                      build_activation_layer, build_conv_layer,
                      build_norm_layer, build_padding_layer, build_plugin_layer,
                      build_upsample_layer, is_norm)
@@ -20,7 +20,7 @@ __all__ = [
     'build_activation_layer', 'build_conv_layer', 'build_norm_layer',
     'build_padding_layer', 'build_upsample_layer', 'build_plugin_layer',
     'is_norm', 'NonLocal1d', 'NonLocal2d', 'NonLocal3d', 'ContextBlock',
-    'GeneralizedAttention', 'ACTIVATION_LAYERS', 'CONV_LAYERS', 'NORM_LAYERS',
-    'PADDING_LAYERS', 'UPSAMPLE_LAYERS', 'PLUGIN_LAYERS', 'Scale',
-    'get_model_complexity_info'
+    'HSigmoid', 'HSwish', 'GeneralizedAttention', 'ACTIVATION_LAYERS',
+    'CONV_LAYERS', 'NORM_LAYERS', 'PADDING_LAYERS', 'UPSAMPLE_LAYERS',
+    'PLUGIN_LAYERS', 'Scale', 'get_model_complexity_info'
 ]
diff --git a/mmcv/cnn/bricks/generalized_attention.py b/mmcv/cnn/bricks/generalized_attention.py
index 5af755e9d..8a779bf07 100644
--- a/mmcv/cnn/bricks/generalized_attention.py
+++ b/mmcv/cnn/bricks/generalized_attention.py
@@ -32,12 +32,13 @@ class GeneralizedAttention(nn.Module):
             Default: 1.
         attention_type (str): A binary indicator string for indicating which
             items in generalized empirical_attention module are used.
-            '1000' indicates 'query and key content' (appr - appr) item,
-            '0100' indicates 'query content and relative position'
-              (appr - position) item,
-            '0010' indicates 'key content only' (bias - appr) item,
-            '0001' indicates 'relative position only' (bias - position) item.
             Default: '1111'.
+
+            - '1000' indicates 'query and key content' (appr - appr) item,
+            - '0100' indicates 'query content and relative position'
+              (appr - position) item,
+            - '0010' indicates 'key content only' (bias - appr) item,
+            - '0001' indicates 'relative position only' (bias - position) item.
     """
 
     _abbr_ = 'gen_attention_block'
diff --git a/mmcv/cnn/bricks/hswish.py b/mmcv/cnn/bricks/hswish.py
index ae1f81c3e..f1a22adbc 100644
--- a/mmcv/cnn/bricks/hswish.py
+++ b/mmcv/cnn/bricks/hswish.py
@@ -5,8 +5,12 @@ from .registry import ACTIVATION_LAYERS
 
 @ACTIVATION_LAYERS.register_module()
 class HSwish(nn.Module):
-    """Hard Swish Module. Apply the hard swish function:
-    Hswish(x) = x * ReLU6(x + 3) / 6
+    """Hard Swish Module.
+
+    This module applies the hard swish function:
+
+    .. math::
+        Hswish(x) = x * ReLU6(x + 3) / 6
 
     Args:
         inplace (bool): can optionally do the operation in-place.
diff --git a/mmcv/cnn/bricks/norm.py b/mmcv/cnn/bricks/norm.py
index d42dad0a7..154ba1c35 100644
--- a/mmcv/cnn/bricks/norm.py
+++ b/mmcv/cnn/bricks/norm.py
@@ -73,6 +73,7 @@ def build_norm_layer(cfg, num_features, postfix=''):
 
     Args:
         cfg (dict): The norm layer config, which should contain:
+
             - type (str): Layer type.
             - layer args: Args needed to instantiate a norm layer.
             - requires_grad (bool, optional): Whether stop gradient updates.
@@ -81,10 +82,9 @@ def build_norm_layer(cfg, num_features, postfix=''):
             to create named layer.
 
     Returns:
-        tuple[str, nn.Module]:
-            name (str): The layer name consisting of abbreviation and postfix,
-                e.g., bn1, gn.
-            layer (nn.Module): Created norm layer.
+        (str, nn.Module): The first element is the layer name consisting of
+            abbreviation and postfix, e.g., bn1, gn. The second element is the
+            created norm layer.
     """
     if not isinstance(cfg, dict):
         raise TypeError('cfg must be a dict')
diff --git a/mmcv/cnn/bricks/plugin.py b/mmcv/cnn/bricks/plugin.py
index d1ed46f57..5e4455af5 100644
--- a/mmcv/cnn/bricks/plugin.py
+++ b/mmcv/cnn/bricks/plugin.py
@@ -31,7 +31,6 @@ def infer_abbr(class_type):
 
             >>> camel2snack("FancyBlock")
             'fancy_block'
-
         """
 
         word = re.sub(r'([A-Z]+)([A-Z][a-z])', r'\1_\2', word)
diff --git a/mmcv/cnn/bricks/upsample.py b/mmcv/cnn/bricks/upsample.py
index 779292c79..c029a439c 100644
--- a/mmcv/cnn/bricks/upsample.py
+++ b/mmcv/cnn/bricks/upsample.py
@@ -52,14 +52,15 @@ def build_upsample_layer(cfg, *args, **kwargs):
 
     Args:
         cfg (dict): The upsample layer config, which should contain:
+
             - type (str): Layer type.
             - scale_factor (int): Upsample ratio, which is not applicable to
                 deconv.
             - layer args: Args needed to instantiate a upsample layer.
-        args (argument list): Arguments passed to the `__init__`
-            method of the corresponding conv layer.
-        kwargs (keyword arguments): Keyword arguments passed to the `__init__`
+        args (argument list): Arguments passed to the ``__init__``
             method of the corresponding conv layer.
+        kwargs (keyword arguments): Keyword arguments passed to the
+            ``__init__`` method of the corresponding conv layer.
 
     Returns:
         nn.Module: Created upsample layer.
diff --git a/mmcv/cnn/resnet.py b/mmcv/cnn/resnet.py
index 83c629ec0..e0129eae2 100644
--- a/mmcv/cnn/resnet.py
+++ b/mmcv/cnn/resnet.py
@@ -9,7 +9,7 @@ from .utils import constant_init, kaiming_init
 
 
 def conv3x3(in_planes, out_planes, stride=1, dilation=1):
-    """3x3 convolution with padding"""
+    """3x3 convolution with padding."""
     return nn.Conv2d(
         in_planes,
         out_planes,
@@ -75,8 +75,8 @@ class Bottleneck(nn.Module):
                  with_cp=False):
         """Bottleneck block.
 
-        If style is "pytorch", the stride-two layer is the 3x3 conv layer,
-        if it is "caffe", the stride-two layer is the first 1x1 conv layer.
+        If style is "pytorch", the stride-two layer is the 3x3 conv layer, if
+        it is "caffe", the stride-two layer is the first 1x1 conv layer.
         """
         super(Bottleneck, self).__init__()
         assert style in ['pytorch', 'caffe']
diff --git a/mmcv/cnn/utils/flops_counter.py b/mmcv/cnn/utils/flops_counter.py
index 21b703bc4..d783bb470 100644
--- a/mmcv/cnn/utils/flops_counter.py
+++ b/mmcv/cnn/utils/flops_counter.py
@@ -45,18 +45,19 @@ def get_model_complexity_info(model,
     each layer in a model.
 
     Supported layers are listed as below:
-        - Convolutions: `nn.Conv1d`, `nn.Conv2d`, `nn.Conv3d`.
-        - Activations: `nn.ReLU`, `nn.PReLU`, `nn.ELU`, `nn.LeakyReLU`,
-            `nn.ReLU6`.
-        - Poolings: `nn.MaxPool1d`, `nn.MaxPool2d`, `nn.MaxPool3d`,
-            `nn.AvgPool1d`, `nn.AvgPool2d`, `nn.AvgPool3d`,
-            `nn.AdaptiveMaxPool1d`, `nn.AdaptiveMaxPool2d`,
-            `nn.AdaptiveMaxPool3d`, `nn.AdaptiveAvgPool1d`,
-            `nn.AdaptiveAvgPool2d`, `nn.AdaptiveAvgPool3d`.
-        - BatchNorms: `nn.BatchNorm1d`, `nn.BatchNorm2d`, `nn.BatchNorm3d`.
-        - Linear: `nn.Linear`.
-        - Deconvolution: `nn.ConvTranspose2d`.
-        - Upsample: `nn.Upsample`.
+        - Convolutions: ``nn.Conv1d``, ``nn.Conv2d``, ``nn.Conv3d``.
+        - Activations: ``nn.ReLU``, ``nn.PReLU``, ``nn.ELU``, ``nn.LeakyReLU``,
+            ``nn.ReLU6``.
+        - Poolings: ``nn.MaxPool1d``, ``nn.MaxPool2d``, ``nn.MaxPool3d``,
+            ``nn.AvgPool1d``, ``nn.AvgPool2d``, ``nn.AvgPool3d``,
+            ``nn.AdaptiveMaxPool1d``, ``nn.AdaptiveMaxPool2d``,
+            ``nn.AdaptiveMaxPool3d``, ``nn.AdaptiveAvgPool1d``,
+            ``nn.AdaptiveAvgPool2d``, ``nn.AdaptiveAvgPool3d``.
+        - BatchNorms: ``nn.BatchNorm1d``, ``nn.BatchNorm2d``,
+            ``nn.BatchNorm3d``.
+        - Linear: ``nn.Linear``.
+        - Deconvolution: ``nn.ConvTranspose2d``.
+        - Upsample: ``nn.Upsample``.
 
     Args:
         model (nn.Module): The model for complexity calculation.
@@ -69,11 +70,11 @@ def get_model_complexity_info(model,
             method that generates input. otherwise, it will generate a random
             tensor with input shape to calculate FLOPs. Default: None.
         flush (bool): same as that in :func:`print`. Default: False.
-        ost (stream): same as `file` param in :func:`print`.
+        ost (stream): same as ``file`` param in :func:`print`.
             Default: sys.stdout.
 
     Returns:
-        tuple[float | str]: If `as_strings` is set to True, it will return
+        tuple[float | str]: If ``as_strings`` is set to True, it will return
             FLOPs and parameter counts in a string format. otherwise, it will
             return those in a float number format.
     """
@@ -352,7 +353,7 @@ def start_flops_count(self):
     """Activate the computation of mean flops consumption per image.
 
     A method to activate the computation of mean flops consumption per image.
-    which will be available after `add_flops_counting_methods()` is called on
+    which will be available after ``add_flops_counting_methods()`` is called on
     a desired net object. It should be called before running the network.
     """
     add_batch_counter_hook_function(self)
@@ -374,9 +375,9 @@ def start_flops_count(self):
 def stop_flops_count(self):
     """Stop computing the mean flops consumption per image.
 
-    A method to stop computing the mean flops consumption per image, which
-    will be available after `add_flops_counting_methods()` is called on a
-    desired net object. It can be called to pause the computation whenever.
+    A method to stop computing the mean flops consumption per image, which will
+    be available after ``add_flops_counting_methods()`` is called on a desired
+    net object. It can be called to pause the computation whenever.
     """
     remove_batch_counter_hook_function(self)
     self.apply(remove_flops_counter_hook_function)
@@ -385,8 +386,8 @@ def stop_flops_count(self):
 def reset_flops_count(self):
     """Reset statistics computed so far.
 
-    A method to Reset computed statistics, which will be available
-    after `add_flops_counting_methods()` is called on a desired net object.
+    A method to Reset computed statistics, which will be available after
+    `add_flops_counting_methods()` is called on a desired net object.
     """
     add_batch_counter_variables_or_reset(self)
     self.apply(add_flops_counter_variable_or_reset)
diff --git a/mmcv/cnn/utils/weight_init.py b/mmcv/cnn/utils/weight_init.py
index e06e6ccaa..e6d92e7a8 100644
--- a/mmcv/cnn/utils/weight_init.py
+++ b/mmcv/cnn/utils/weight_init.py
@@ -61,6 +61,6 @@ def caffe2_xavier_init(module, bias=0):
 
 
 def bias_init_with_prob(prior_prob):
-    """ initialize conv/fc bias value according to giving probablity"""
+    """initialize conv/fc bias value according to giving probablity."""
     bias_init = float(-np.log((1 - prior_prob) / prior_prob))
     return bias_init
diff --git a/mmcv/cnn/vgg.py b/mmcv/cnn/vgg.py
index 50278cee2..c20b5d0f4 100644
--- a/mmcv/cnn/vgg.py
+++ b/mmcv/cnn/vgg.py
@@ -8,7 +8,7 @@ from .utils import constant_init, kaiming_init, normal_init
 
 
 def conv3x3(in_planes, out_planes, dilation=1):
-    """3x3 convolution with padding"""
+    """3x3 convolution with padding."""
     return nn.Conv2d(
         in_planes,
         out_planes,
diff --git a/mmcv/fileio/file_client.py b/mmcv/fileio/file_client.py
index 9ec3b251e..6afae4927 100644
--- a/mmcv/fileio/file_client.py
+++ b/mmcv/fileio/file_client.py
@@ -6,8 +6,8 @@ from abc import ABCMeta, abstractmethod
 class BaseStorageBackend(metaclass=ABCMeta):
     """Abstract class of storage backends.
 
-    All backends need to implement two apis: `get()` and `get_text()`.
-    `get()` reads the file as a byte stream and `get_text()` reads the file
+    All backends need to implement two apis: ``get()`` and ``get_text()``.
+    ``get()`` reads the file as a byte stream and ``get_text()`` reads the file
     as texts.
     """
 
@@ -25,8 +25,8 @@ class CephBackend(BaseStorageBackend):
 
     Args:
         path_mapping (dict|None): path mapping dict from local path to Petrel
-            path. When `path_mapping={'src': 'dst'}`, `src` in `filepath` will
-            be replaced by `dst`. Default: None.
+            path. When ``path_mapping={'src': 'dst'}``, ``src`` in ``filepath``
+            will be replaced by ``dst``. Default: None.
     """
 
     def __init__(self, path_mapping=None):
diff --git a/mmcv/image/geometric.py b/mmcv/image/geometric.py
index 2e3a6a3dd..93d4bb756 100644
--- a/mmcv/image/geometric.py
+++ b/mmcv/image/geometric.py
@@ -336,6 +336,7 @@ def impad(img,
             areas when padding_mode is 'constant'. Default: 0.
         padding_mode (str): Type of padding. Should be: constant, edge,
             reflect or symmetric. Default: constant.
+
             - constant: pads with a constant value, this value is specified
                 with pad_val.
             - edge: pads with the last value at the edge of the image.
@@ -370,8 +371,8 @@ def impad(img,
     elif isinstance(padding, numbers.Number):
         padding = (padding, padding, padding, padding)
     else:
-        raise ValueError("Padding must be a int or a 2, or 4 element tuple."
-                         f"But received {padding}")
+        raise ValueError('Padding must be a int or a 2, or 4 element tuple.'
+                         f'But received {padding}')
 
     # check padding mode
     assert padding_mode in ['constant', 'edge', 'reflect', 'symmetric']
diff --git a/mmcv/image/io.py b/mmcv/image/io.py
index 0ee36baa6..259483d6a 100644
--- a/mmcv/image/io.py
+++ b/mmcv/image/io.py
@@ -70,7 +70,7 @@ def _jpegflag(flag='color', channel_order='bgr'):
 
 
 def _pillow2array(img, flag='color', channel_order='bgr'):
-    """Convert a pillow image to numpy array
+    """Convert a pillow image to numpy array.
 
     Args:
         img (:obj:`PIL.Image.Image`): The image loaded using PIL
@@ -215,7 +215,7 @@ def imfrombytes(content, flag='color', channel_order='bgr', backend=None):
 
 
 def imwrite(img, file_path, params=None, auto_mkdir=True):
-    """Write image to file
+    """Write image to file.
 
     Args:
         img (ndarray): Image array to be written.
diff --git a/mmcv/image/misc.py b/mmcv/image/misc.py
index 01d19d467..1e02b952e 100644
--- a/mmcv/image/misc.py
+++ b/mmcv/image/misc.py
@@ -9,7 +9,7 @@ except ImportError:
 
 
 def tensor2imgs(tensor, mean=(0, 0, 0), std=(1, 1, 1), to_rgb=True):
-    """Convert tensor to 3-channel images
+    """Convert tensor to 3-channel images.
 
     Args:
         tensor (torch.Tensor): Tensor that contains multiple images, shape (
diff --git a/mmcv/image/photometric.py b/mmcv/image/photometric.py
index 79d50cd58..948936a20 100644
--- a/mmcv/image/photometric.py
+++ b/mmcv/image/photometric.py
@@ -53,7 +53,7 @@ def imdenormalize(img, mean, std, to_bgr=True):
 
 
 def iminvert(img):
-    """Invert (negate) an image
+    """Invert (negate) an image.
 
     Args:
         img (ndarray): Image to be inverted.
diff --git a/mmcv/ops/deform_conv.py b/mmcv/ops/deform_conv.py
index 4714f0885..01c54b866 100644
--- a/mmcv/ops/deform_conv.py
+++ b/mmcv/ops/deform_conv.py
@@ -240,11 +240,12 @@ class DeformConv2dPack(DeformConv2d):
 
     The offset tensor is like `[y0, x0, y1, x1, y2, x2, ..., y8, x8]`.
     The spatial arrangement is like:
-    ```
-    (x0, y0) (x1, y1) (x2, y2)
-    (x3, y3) (x4, y4) (x5, y5)
-    (x6, y6) (x7, y7) (x8, y8)
-    ```
+
+    .. code:: text
+
+        (x0, y0) (x1, y1) (x2, y2)
+        (x3, y3) (x4, y4) (x5, y5)
+        (x6, y6) (x7, y7) (x8, y8)
 
     Args:
         in_channels (int): Same as nn.Conv2d.
diff --git a/mmcv/ops/nms.py b/mmcv/ops/nms.py
index 72755fcb2..d9e92d867 100644
--- a/mmcv/ops/nms.py
+++ b/mmcv/ops/nms.py
@@ -216,7 +216,7 @@ def nms_match(dets, iou_threshold):
     """Matched dets into different groups by NMS.
 
     NMS match is Similar to NMS but when a bbox is suppressed, nms match will
-    record the indice of supporessed bbox and form a group with the indice of
+    record the indice of suppressed bbox and form a group with the indice of
     kept bbox. In each group, indice is sorted as score order.
 
     Arguments:
@@ -224,9 +224,9 @@ def nms_match(dets, iou_threshold):
         iou_thr (float): IoU thresh for NMS.
 
     Returns:
-        List[Tensor | ndarray]: The outer list corresponds different matched
-            group, the inner Tensor corresponds the indices for a group in
-            score order.
+        List[torch.Tensor | np.ndarray]: The outer list corresponds different
+            matched group, the inner Tensor corresponds the indices for a group
+            in score order.
     """
     if dets.shape[0] == 0:
         matched = []
diff --git a/mmcv/ops/point_sample.py b/mmcv/ops/point_sample.py
index 2e1c681b2..ec5aaf3e3 100644
--- a/mmcv/ops/point_sample.py
+++ b/mmcv/ops/point_sample.py
@@ -134,9 +134,9 @@ def rel_roi_point_to_rel_img_point(rois,
 
 
 def point_sample(input, points, align_corners=False, **kwargs):
-    """A wrapper around :function:`grid_sample` to support 3D point_coords
-    tensors Unlike :function:`torch.nn.functional.grid_sample` it assumes
-    point_coords to lie inside [0, 1] x [0, 1] square.
+    """A wrapper around :func:`grid_sample` to support 3D point_coords tensors
+    Unlike :func:`torch.nn.functional.grid_sample` it assumes point_coords to
+    lie inside ``[0, 1] x [0, 1]`` square.
 
     Args:
         input (Tensor): Feature map, shape (N, C, H, W).
diff --git a/mmcv/parallel/_functions.py b/mmcv/parallel/_functions.py
index 98f7e6ae9..ea5cbb6a2 100644
--- a/mmcv/parallel/_functions.py
+++ b/mmcv/parallel/_functions.py
@@ -4,8 +4,7 @@ from torch.nn.parallel._functions import _get_stream
 
 
 def scatter(input, devices, streams=None):
-    """Scatters tensor across multiple GPUs.
-    """
+    """Scatters tensor across multiple GPUs."""
     if streams is None:
         streams = [None] * len(devices)
 
diff --git a/mmcv/parallel/scatter_gather.py b/mmcv/parallel/scatter_gather.py
index cafc03271..c45fb1643 100644
--- a/mmcv/parallel/scatter_gather.py
+++ b/mmcv/parallel/scatter_gather.py
@@ -43,7 +43,7 @@ def scatter(inputs, target_gpus, dim=0):
 
 
 def scatter_kwargs(inputs, kwargs, target_gpus, dim=0):
-    """Scatter with support for kwargs dictionary"""
+    """Scatter with support for kwargs dictionary."""
     inputs = scatter(inputs, target_gpus, dim) if inputs else []
     kwargs = scatter(kwargs, target_gpus, dim) if kwargs else []
     if len(inputs) < len(kwargs):
diff --git a/mmcv/runner/__init__.py b/mmcv/runner/__init__.py
index a0e80da70..389c80662 100644
--- a/mmcv/runner/__init__.py
+++ b/mmcv/runner/__init__.py
@@ -27,5 +27,5 @@ __all__ = [
     'obj_from_dict', 'init_dist', 'get_dist_info', 'master_only',
     'OPTIMIZER_BUILDERS', 'OPTIMIZERS', 'DefaultOptimizerConstructor',
     'build_optimizer', 'build_optimizer_constructor', 'IterLoader',
-    'IterBasedRunner', 'set_random_seed'
+    'set_random_seed'
 ]
diff --git a/mmcv/runner/base_runner.py b/mmcv/runner/base_runner.py
index ca780b47f..807beef69 100644
--- a/mmcv/runner/base_runner.py
+++ b/mmcv/runner/base_runner.py
@@ -247,7 +247,7 @@ class BaseRunner(metaclass=ABCMeta):
         """Register a hook into the hook list.
 
         The hook will be inserted into a priority queue, with the specified
-        priority (See :cls:`Priority` for details of priorities).
+        priority (See :class:`Priority` for details of priorities).
         For hooks with the same priority, they will be triggered in the same
         order as they are registered.
 
diff --git a/mmcv/runner/checkpoint.py b/mmcv/runner/checkpoint.py
index 504ffc931..fa5b9a104 100644
--- a/mmcv/runner/checkpoint.py
+++ b/mmcv/runner/checkpoint.py
@@ -103,8 +103,8 @@ def load_state_dict(module, state_dict, strict=False, logger=None):
 
 
 def load_url_dist(url, model_dir=None):
-    """ In distributed setting, this function only download checkpoint at
-    local rank 0 """
+    """In distributed setting, this function only download checkpoint at local
+    rank 0."""
     rank, world_size = get_dist_info()
     rank = int(os.environ.get('LOCAL_RANK', rank))
     if rank == 0:
diff --git a/mmcv/runner/epoch_based_runner.py b/mmcv/runner/epoch_based_runner.py
index 9581eb48e..a962e7a57 100644
--- a/mmcv/runner/epoch_based_runner.py
+++ b/mmcv/runner/epoch_based_runner.py
@@ -161,7 +161,7 @@ class EpochBasedRunner(BaseRunner):
 
 
 class Runner(EpochBasedRunner):
-    """Deprecated name of EpochBasedRunner"""
+    """Deprecated name of EpochBasedRunner."""
 
     def __init__(self, *args, **kwargs):
         warnings.warn(
diff --git a/mmcv/runner/hooks/lr_updater.py b/mmcv/runner/hooks/lr_updater.py
index 6bf869602..7260c4a13 100644
--- a/mmcv/runner/hooks/lr_updater.py
+++ b/mmcv/runner/hooks/lr_updater.py
@@ -5,7 +5,7 @@ from .hook import HOOKS, Hook
 
 
 class LrUpdaterHook(Hook):
-    """LR Scheduler in MMCV
+    """LR Scheduler in MMCV.
 
     Args:
         by_epoch (bool): LR changes epoch by epoch
@@ -325,7 +325,7 @@ def get_position_from_periods(iteration, cumulative_periods):
 
 @HOOKS.register_module()
 class CyclicLrUpdaterHook(LrUpdaterHook):
-    """Cyclic LR Scheduler
+    """Cyclic LR Scheduler.
 
     Implement the cyclical learning rate policy (CLR) described in
     https://arxiv.org/pdf/1506.01186.pdf
@@ -341,7 +341,6 @@ class CyclicLrUpdaterHook(LrUpdaterHook):
         step_ratio_up (float): The ratio of the increasing process of LR in
             the total cycle.
         by_epoch (bool): Whether to update LR by epoch.
-
     """
 
     def __init__(self,
diff --git a/mmcv/runner/hooks/momentum_updater.py b/mmcv/runner/hooks/momentum_updater.py
index 017ee5bda..0f9cad1d0 100644
--- a/mmcv/runner/hooks/momentum_updater.py
+++ b/mmcv/runner/hooks/momentum_updater.py
@@ -128,7 +128,7 @@ class CosineAnealingMomentumUpdaterHook(MomentumUpdaterHook):
 
 @HOOKS.register_module()
 class CyclicMomentumUpdaterHook(MomentumUpdaterHook):
-    """Cyclic momentum Scheduler
+    """Cyclic momentum Scheduler.
 
     Implemet the cyclical momentum scheduler policy described in
     https://arxiv.org/pdf/1708.07120.pdf
@@ -143,7 +143,6 @@ class CyclicMomentumUpdaterHook(MomentumUpdaterHook):
         step_ratio_up (float): The ratio of the increasing process of momentum
             in  the total cycle.
         by_epoch (bool): Whether to update momentum by epoch.
-
     """
 
     def __init__(self,
diff --git a/mmcv/runner/log_buffer.py b/mmcv/runner/log_buffer.py
index 3030db335..ed4652f6d 100644
--- a/mmcv/runner/log_buffer.py
+++ b/mmcv/runner/log_buffer.py
@@ -31,7 +31,7 @@ class LogBuffer:
             self.n_history[key].append(count)
 
     def average(self, n=0):
-        """Average latest n values or all values"""
+        """Average latest n values or all values."""
         assert n >= 0
         for key in self.val_history:
             values = np.array(self.val_history[key][-n:])
diff --git a/mmcv/runner/optimizer/default_constructor.py b/mmcv/runner/optimizer/default_constructor.py
index d56b742dc..e886c616a 100644
--- a/mmcv/runner/optimizer/default_constructor.py
+++ b/mmcv/runner/optimizer/default_constructor.py
@@ -44,8 +44,11 @@ class DefaultOptimizerConstructor:
         model (:obj:`nn.Module`): The model with parameters to be optimized.
         optimizer_cfg (dict): The config dict of the optimizer.
             Positional fields are
+
                 - `type`: class name of the optimizer.
+
             Optional fields are
+
                 - any arguments of the corresponding optimizer type, e.g.,
                   lr, weight_decay, momentum, etc.
         paramwise_cfg (dict, optional): Parameter-wise options.
diff --git a/mmcv/utils/config.py b/mmcv/utils/config.py
index 7513cbf45..4cdf23ef4 100644
--- a/mmcv/utils/config.py
+++ b/mmcv/utils/config.py
@@ -78,7 +78,6 @@ class Config:
         >>> cfg
         "Config [path: /home/kchen/projects/mmcv/tests/data/config/a.py]: "
         "{'item1': [1, 2], 'item2': {'a': 0}, 'item3': True, 'item4': 'test'}"
-
     """
 
     @staticmethod
@@ -180,8 +179,7 @@ class Config:
 
     @staticmethod
     def auto_argparser(description=None):
-        """Generate argparser from config file automatically (experimental)
-        """
+        """Generate argparser from config file automatically (experimental)"""
         partial_parser = ArgumentParser(description=description)
         partial_parser.add_argument('config', help='config file path')
         cfg_file = partial_parser.parse_known_args()[0].config
@@ -356,7 +354,7 @@ class Config:
                 mmcv.dump(cfg_dict, file)
 
     def merge_from_dict(self, options):
-        """Merge list into cfg_dict
+        """Merge list into cfg_dict.
 
         Merge the dict parsed by MultipleKVAction into this cfg.
 
diff --git a/mmcv/utils/progressbar.py b/mmcv/utils/progressbar.py
index 3cbb3d4c1..b2b509d6c 100644
--- a/mmcv/utils/progressbar.py
+++ b/mmcv/utils/progressbar.py
@@ -8,7 +8,7 @@ from .timer import Timer
 
 
 class ProgressBar:
-    """A progress bar which can print the progress"""
+    """A progress bar which can print the progress."""
 
     def __init__(self, task_num=0, bar_width=50, start=True, file=sys.stdout):
         self.task_num = task_num
@@ -176,7 +176,8 @@ def track_parallel_progress(func,
 
 
 def track_iter_progress(tasks, bar_width=50, file=sys.stdout):
-    """Track the progress of tasks iteration or enumeration with a progress bar.
+    """Track the progress of tasks iteration or enumeration with a progress
+    bar.
 
     Tasks are yielded with a simple for-loop.
 
diff --git a/mmcv/video/io.py b/mmcv/video/io.py
index 803fc6457..dfddcfd9d 100644
--- a/mmcv/video/io.py
+++ b/mmcv/video/io.py
@@ -200,7 +200,7 @@ class VideoReader:
                    start=0,
                    max_num=0,
                    show_progress=True):
-        """Convert a video to frame images
+        """Convert a video to frame images.
 
         Args:
             frame_dir (str): Output directory to store all the frame images.
@@ -282,7 +282,7 @@ def frames2video(frame_dir,
                  start=0,
                  end=0,
                  show_progress=True):
-    """Read the frame images from a directory and join them as a video
+    """Read the frame images from a directory and join them as a video.
 
     Args:
         frame_dir (str): The directory containing video frames.
diff --git a/mmcv/video/optflow.py b/mmcv/video/optflow.py
index cc49a2a50..ab0a532be 100644
--- a/mmcv/video/optflow.py
+++ b/mmcv/video/optflow.py
@@ -139,7 +139,7 @@ def dequantize_flow(dx, dy, max_val=0.02, denorm=True):
 
 
 def flow_warp(img, flow, filling_value=0, interpolate_mode='nearest'):
-    """Use flow to warp img
+    """Use flow to warp img.
 
     Args:
         img (ndarray, float or uint8): Image to be warped.
diff --git a/setup.py b/setup.py
index 988809519..34a6c67ca 100644
--- a/setup.py
+++ b/setup.py
@@ -14,9 +14,8 @@ from Cython.Distutils import build_ext as build_cmd  # NOQA: E402  # isort:skip
 
 
 def choose_requirement(primary, secondary):
-    """If some version of primary requirement installed, return primary,
-    else return secondary.
-    """
+    """If some version of primary requirement installed, return primary, else
+    return secondary."""
     try:
         name = re.split(r'[!<>=]', primary)[0]
         get_distribution(name)
@@ -40,8 +39,7 @@ def get_version():
 
 
 def parse_requirements(fname='requirements.txt', with_version=True):
-    """
-    Parse the package dependencies listed in a requirements file but strips
+    """Parse the package dependencies listed in a requirements file but strips
     specific versioning information.
 
     Args:
@@ -60,9 +58,7 @@ def parse_requirements(fname='requirements.txt', with_version=True):
     require_fpath = fname
 
     def parse_line(line):
-        """
-        Parse information from a line in a requirements text file
-        """
+        """Parse information from a line in a requirements text file."""
         if line.startswith('-r '):
             # Allow specifying requirements in other files
             target = line.split(' ')[1]
diff --git a/tests/test_runner/test_hooks.py b/tests/test_runner/test_hooks.py
index 8c7ae62f0..68e5a19d9 100644
--- a/tests/test_runner/test_hooks.py
+++ b/tests/test_runner/test_hooks.py
@@ -1,10 +1,8 @@
-"""
-Tests the hooks with runners.
+"""Tests the hooks with runners.
 
 CommandLine:
     pytest tests/test_hooks.py
     xdoctest tests/test_hooks.py zero
-
 """
 import logging
 import os.path as osp
@@ -49,9 +47,7 @@ def test_pavi_hook():
 
 
 def test_momentum_runner_hook():
-    """
-    xdoctest -m tests/test_hooks.py test_momentum_runner_hook
-    """
+    """xdoctest -m tests/test_hooks.py test_momentum_runner_hook."""
     sys.modules['pavi'] = MagicMock()
     loader = DataLoader(torch.ones((10, 2)))
     runner = _build_demo_runner()
@@ -99,9 +95,7 @@ def test_momentum_runner_hook():
 
 
 def test_cosine_runner_hook():
-    """
-    xdoctest -m tests/test_hooks.py test_cosine_runner_hook
-    """
+    """xdoctest -m tests/test_hooks.py test_cosine_runner_hook."""
     sys.modules['pavi'] = MagicMock()
     loader = DataLoader(torch.ones((10, 2)))
     runner = _build_demo_runner()