add lazy ops docs

docs/tutorials/4_data_pipeline.md

@@ -87,6 +87,39 @@ test_pipeline = [
 ]
 ```
 
+We have supported some lazy operators and encourage users to apply them.
+Lazy ops record how the data should be processed, but it will postpone the processing on the raw data until the raw data forward `Fuse` stage.
+Specifically, lazy ops avoid frequent reading and modification operation on the raw data, but process the raw data once in the final Fuse stage, thus accelerating data preprocessing.
+
+Here is a pipeline example applying lazy ops.
+
+```python
+train_pipeline = [
+    dict(type='SampleFrames', clip_len=32, frame_interval=2, num_clips=1),
+    dict(type='RawFrameDecode', decoding_backend='turbojpeg'),
+    # The following three lazy ops only process the bbox of frames without
+    # modifying the raw data.
+    dict(type='Resize', scale=(-1, 256), lazy=True),
+    dict(
+        type='MultiScaleCrop',
+        input_size=224,
+        scales=(1, 0.8),
+        random_crop=False,
+        max_wh_scale_gap=0,
+        lazy=True),
+    dict(type='Resize', scale=(224, 224), keep_ratio=False, lazy=True),
+    # Lazy operator `Flip` only record whether a frame should be fliped and the
+    # flip direction.
+    dict(type='Flip', flip_ratio=0.5, lazy=True),
+    # Processing the raw data once in Fuse stage.
+    dict(type='Fuse'),
+    dict(type='Normalize', **img_norm_cfg),
+    dict(type='FormatShape', input_format='NCTHW'),
+    dict(type='Collect', keys=['imgs', 'label'], meta_keys=[]),
+    dict(type='ToTensor', keys=['imgs', 'label'])
+]
+```
+
 For each operation, we list the related dict fields that are added/updated/removed.
 
 ### Data loading