diff --git a/.dev/batch_test_list.py b/.dev/batch_test_list.py
index 6906150..c4fd8f9 100644
--- a/.dev/batch_test_list.py
+++ b/.dev/batch_test_list.py
@@ -116,8 +116,8 @@ vit = [
 ]
 fp16 = [
     dict(
-        config='configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py', # noqa
-        checkpoint='deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes-cc58bc8d.pth', # noqa
+        config='configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py', # noqa
+        checkpoint='deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-f1104f4b.pth', # noqa
         eval='mIoU',
         metric=dict(mIoU=80.46),
     )
diff --git a/.dev/batch_train_list.txt b/.dev/batch_train_list.txt
index 3f406a5..17d1993 100644
--- a/.dev/batch_train_list.txt
+++ b/.dev/batch_train_list.txt
@@ -15,5 +15,5 @@ configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py
 configs/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes.py
 configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py
 configs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k.py
-configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py
+configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py
 configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py
diff --git a/.dev/benchmark_evaluation.sh b/.dev/benchmark_evaluation.sh
index b4901fe..687e6cc 100755
--- a/.dev/benchmark_evaluation.sh
+++ b/.dev/benchmark_evaluation.sh
@@ -35,7 +35,7 @@ echo 'configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py' &
 GPUS=4  GPUS_PER_NODE=4  CPUS_PER_TASK=2 tools/slurm_test.sh $PARTITION upernet_vit-b16_ln_mln_512x512_160k_ade20k configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py $CHECKPOINT_DIR/upernet_vit-b16_ln_mln_512x512_160k_ade20k-f444c077.pth --eval mIoU --work-dir work_dirs/benchmark_evaluation/upernet_vit-b16_ln_mln_512x512_160k_ade20k --options dist_params.port=28186 &
 echo 'configs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k.py' &
 GPUS=4  GPUS_PER_NODE=4  CPUS_PER_TASK=2 tools/slurm_test.sh $PARTITION upernet_deit-s16_ln_mln_512x512_160k_ade20k configs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k.py $CHECKPOINT_DIR/upernet_deit-s16_ln_mln_512x512_160k_ade20k-c0cd652f.pth --eval mIoU --work-dir work_dirs/benchmark_evaluation/upernet_deit-s16_ln_mln_512x512_160k_ade20k --options dist_params.port=28187 &
-echo 'configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py' &
-GPUS=4  GPUS_PER_NODE=4  CPUS_PER_TASK=2 tools/slurm_test.sh $PARTITION deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py $CHECKPOINT_DIR/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes-cc58bc8d.pth --eval mIoU --work-dir work_dirs/benchmark_evaluation/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes --options dist_params.port=28188 &
+echo 'configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py' &
+GPUS=4  GPUS_PER_NODE=4  CPUS_PER_TASK=2 tools/slurm_test.sh $PARTITION deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py $CHECKPOINT_DIR/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes-cc58bc8d.pth --eval mIoU --work-dir work_dirs/benchmark_evaluation/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes --options dist_params.port=28188 &
 echo 'configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py' &
 GPUS=4  GPUS_PER_NODE=4  CPUS_PER_TASK=2 tools/slurm_test.sh $PARTITION upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py $CHECKPOINT_DIR/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K_20210531_112542-e380ad3e.pth --eval mIoU --work-dir work_dirs/benchmark_evaluation/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K --options dist_params.port=28189 &
diff --git a/.dev/benchmark_train.sh b/.dev/benchmark_train.sh
index d3db897..048bb52 100755
--- a/.dev/benchmark_train.sh
+++ b/.dev/benchmark_train.sh
@@ -34,7 +34,7 @@ echo 'configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py' &
 GPUS=8  GPUS_PER_NODE=8  CPUS_PER_TASK=2 ./tools/slurm_train.sh $PARTITION upernet_vit-b16_ln_mln_512x512_160k_ade20k configs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k.py --options checkpoint_config.max_keep_ckpts=1 dist_params.port=24742 --work-dir work_dirs/vit/upernet_vit-b16_ln_mln_512x512_160k_ade20k >/dev/null &
 echo 'configs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k.py' &
 GPUS=8  GPUS_PER_NODE=8  CPUS_PER_TASK=2 ./tools/slurm_train.sh $PARTITION upernet_deit-s16_ln_mln_512x512_160k_ade20k configs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k.py --options checkpoint_config.max_keep_ckpts=1 dist_params.port=24743 --work-dir work_dirs/vit/upernet_deit-s16_ln_mln_512x512_160k_ade20k >/dev/null &
-echo 'configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py' &
-GPUS=4  GPUS_PER_NODE=4  CPUS_PER_TASK=2 ./tools/slurm_train.sh $PARTITION deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py --options checkpoint_config.max_keep_ckpts=1 dist_params.port=24744 --work-dir work_dirs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes >/dev/null &
+echo 'configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py' &
+GPUS=4  GPUS_PER_NODE=4  CPUS_PER_TASK=2 ./tools/slurm_train.sh $PARTITION deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py --options checkpoint_config.max_keep_ckpts=1 dist_params.port=24744 --work-dir work_dirs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes >/dev/null &
 echo 'configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py' &
 GPUS=8  GPUS_PER_NODE=8  CPUS_PER_TASK=2 ./tools/slurm_train.sh $PARTITION upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K configs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K.py --options checkpoint_config.max_keep_ckpts=1 dist_params.port=24745 --work-dir work_dirs/swin/upernet_swin_tiny_patch4_window7_512x512_160k_ade20k_pretrain_224x224_1K >/dev/null &
diff --git a/.dev/md2yml.py b/.dev/md2yml.py
index 82368df..6bb1349 100755
--- a/.dev/md2yml.py
+++ b/.dev/md2yml.py
@@ -201,7 +201,7 @@ def parse_md(md_file):
                             'batch size':
                             1,
                             'mode':
-                            'FP32',
+                            'FP32' if 'fp16' not in config else 'FP16',
                             'resolution':
                             f'({crop_size[0]},{crop_size[1]})'
                         }]
diff --git a/README.md b/README.md
index c8d9027..18317e0 100644
--- a/README.md
+++ b/README.md
@@ -73,7 +73,6 @@ Supported methods:
 - [x] [UNet (MICCAI'2016/Nat. Methods'2019)](configs/unet)
 - [x] [PSPNet (CVPR'2017)](configs/pspnet)
 - [x] [DeepLabV3 (ArXiv'2017)](configs/deeplabv3)
-- [x] [Mixed Precision (FP16) Training (ArXiv'2017)](configs/fp16)
 - [x] [BiSeNetV1 (ECCV'2018)](configs/bisenetv1)
 - [x] [PSANet (ECCV'2018)](configs/psanet)
 - [x] [DeepLabV3+ (CVPR'2018)](configs/deeplabv3plus)
diff --git a/README_zh-CN.md b/README_zh-CN.md
index 563233f..d7cf65c 100644
--- a/README_zh-CN.md
+++ b/README_zh-CN.md
@@ -72,7 +72,6 @@ MMSegmentation 是一个基于 PyTorch 的语义分割开源工具箱。它是 O
 - [x] [UNet (MICCAI'2016/Nat. Methods'2019)](configs/unet)
 - [x] [PSPNet (CVPR'2017)](configs/pspnet)
 - [x] [DeepLabV3 (ArXiv'2017)](configs/deeplabv3)
-- [x] [Mixed Precision (FP16) Training (ArXiv'2017)](configs/fp16)
 - [x] [BiSeNetV1 (ECCV'2018)](configs/bisenetv1)
 - [x] [PSANet (ECCV'2018)](configs/psanet)
 - [x] [DeepLabV3+ (CVPR'2018)](configs/deeplabv3plus)
diff --git a/configs/bisenetv2/bisenetv2.yml b/configs/bisenetv2/bisenetv2.yml
index 373edb9..d9e11be 100644
--- a/configs/bisenetv2/bisenetv2.yml
+++ b/configs/bisenetv2/bisenetv2.yml
@@ -75,7 +75,7 @@ Models:
       hardware: V100
       backend: PyTorch
       batch size: 1
-      mode: FP32
+      mode: FP16
       resolution: (1024,1024)
     memory (GB): 5.77
   Results:
diff --git a/configs/deeplabv3/README.md b/configs/deeplabv3/README.md
index 28bdbb9..655efd7 100644
--- a/configs/deeplabv3/README.md
+++ b/configs/deeplabv3/README.md
@@ -39,6 +39,7 @@
 | DeepLabV3 | R-18-D8         | 512x1024  |   80000 | 1.7      | 13.78          | 76.70 |         78.27 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r18-d8_512x1024_80k_cityscapes.py)         | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18-d8_512x1024_80k_cityscapes/deeplabv3_r18-d8_512x1024_80k_cityscapes_20201225_021506-23dffbe2.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18-d8_512x1024_80k_cityscapes/deeplabv3_r18-d8_512x1024_80k_cityscapes-20201225_021506.log.json)                                 |
 | DeepLabV3 | R-50-D8         | 512x1024  |   80000 | -        | -              | 79.32 |         80.57 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r50-d8_512x1024_80k_cityscapes.py)         | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x1024_80k_cityscapes/deeplabv3_r50-d8_512x1024_80k_cityscapes_20200606_113404-b92cfdd4.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x1024_80k_cityscapes/deeplabv3_r50-d8_512x1024_80k_cityscapes_20200606_113404.log.json)                                 |
 | DeepLabV3 | R-101-D8        | 512x1024  |   80000 | -        | -              | 80.20 |         81.21 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py)        | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes/deeplabv3_r101-d8_512x1024_80k_cityscapes_20200606_113503-9e428899.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes/deeplabv3_r101-d8_512x1024_80k_cityscapes_20200606_113503.log.json)                             |
+| DeepLabV3 (FP16)  | R-101-D8 | 512x1024  |   80000 | 5.75     | 3.86           | 80.48 |             - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes.py)     | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-774d9cec.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920.log.json)                 |
 | DeepLabV3 | R-18-D8         | 769x769   |   80000 | 1.9      | 5.55           | 76.60 |         78.26 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r18-d8_769x769_80k_cityscapes.py)          | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18-d8_769x769_80k_cityscapes/deeplabv3_r18-d8_769x769_80k_cityscapes_20201225_021506-6452126a.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r18-d8_769x769_80k_cityscapes/deeplabv3_r18-d8_769x769_80k_cityscapes-20201225_021506.log.json)                                     |
 | DeepLabV3 | R-50-D8         | 769x769   |   80000 | -        | -              | 79.89 |         81.06 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r50-d8_769x769_80k_cityscapes.py)          | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_769x769_80k_cityscapes/deeplabv3_r50-d8_769x769_80k_cityscapes_20200606_221338-788d6228.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_769x769_80k_cityscapes/deeplabv3_r50-d8_769x769_80k_cityscapes_20200606_221338.log.json)                                     |
 | DeepLabV3 | R-101-D8        | 769x769   |   80000 | -        | -              | 79.67 |         80.81 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3/deeplabv3_r101-d8_769x769_80k_cityscapes.py)         | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_769x769_80k_cityscapes/deeplabv3_r101-d8_769x769_80k_cityscapes_20200607_013353-60e95418.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_769x769_80k_cityscapes/deeplabv3_r101-d8_769x769_80k_cityscapes_20200607_013353.log.json)                                 |
@@ -102,3 +103,7 @@
 | DeepLabV3 | R-101-D8 | 512x512   |  160000 | -        | -              | 41.82 |         42.49 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k_20210709_155402-f035acfd.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_160k_coco-stuff164k_20210709_155402.log.json) |
 | DeepLabV3 | R-50-D8  | 512x512   |  320000 | -        | -              | 41.37 |         42.22 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k.py)  | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k_20210709_155403-51b21115.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k/deeplabv3_r50-d8_512x512_4x4_320k_coco-stuff164k_20210709_155403.log.json)     |
 | DeepLabV3 | R-101-D8 | 512x512   |  320000 | -        | -              | 42.61 |         43.42 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k_20210709_155402-3cbca14d.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k/deeplabv3_r101-d8_512x512_4x4_320k_coco-stuff164k_20210709_155402.log.json) |
+
+Note:
+
+- `FP16` means Mixed Precision (FP16) is adopted in training.
diff --git a/configs/deeplabv3/deeplabv3.yml b/configs/deeplabv3/deeplabv3.yml
index 94acb59..cd5c8d0 100644
--- a/configs/deeplabv3/deeplabv3.yml
+++ b/configs/deeplabv3/deeplabv3.yml
@@ -157,6 +157,27 @@ Models:
       mIoU(ms+flip): 81.21
   Config: configs/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes/deeplabv3_r101-d8_512x1024_80k_cityscapes_20200606_113503-9e428899.pth
+- Name: deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes
+  In Collection: deeplabv3
+  Metadata:
+    backbone: R-101-D8
+    crop size: (512,1024)
+    lr schd: 80000
+    inference time (ms/im):
+    - value: 259.07
+      hardware: V100
+      backend: PyTorch
+      batch size: 1
+      mode: FP16
+      resolution: (512,1024)
+    memory (GB): 5.75
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 80.48
+  Config: configs/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-774d9cec.pth
 - Name: deeplabv3_r18-d8_769x769_80k_cityscapes
   In Collection: deeplabv3
   Metadata:
diff --git a/configs/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py b/configs/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes.py
similarity index 64%
rename from configs/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py
rename to configs/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes.py
index cb2c27e..e326109 100644
--- a/configs/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py
+++ b/configs/deeplabv3/deeplabv3_r101-d8_fp16_512x1024_80k_cityscapes.py
@@ -1,4 +1,4 @@
-_base_ = '../pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py'
+_base_ = './deeplabv3_r101-d8_512x1024_80k_cityscapes.py'
 # fp16 settings
 optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.)
 # fp16 placeholder
diff --git a/configs/deeplabv3plus/README.md b/configs/deeplabv3plus/README.md
index bf6c5d5..c3e4340 100644
--- a/configs/deeplabv3plus/README.md
+++ b/configs/deeplabv3plus/README.md
@@ -40,6 +40,7 @@
 | DeepLabV3+ | R-18-D8         | 512x1024  |   80000 | 2.2      | 14.27          | 76.89 |         78.76 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r18-d8_512x1024_80k_cityscapes.py)         | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_512x1024_80k_cityscapes/deeplabv3plus_r18-d8_512x1024_80k_cityscapes_20201226_080942-cff257fe.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_512x1024_80k_cityscapes/deeplabv3plus_r18-d8_512x1024_80k_cityscapes-20201226_080942.log.json)                                 |
 | DeepLabV3+ | R-50-D8         | 512x1024  |   80000 | -        | -              | 80.09 |         81.13 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes.py)         | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes/deeplabv3plus_r50-d8_512x1024_80k_cityscapes_20200606_114049-f9fb496d.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_512x1024_80k_cityscapes/deeplabv3plus_r50-d8_512x1024_80k_cityscapes_20200606_114049.log.json)                                 |
 | DeepLabV3+ | R-101-D8        | 512x1024  |   80000 | -        | -              | 80.97 |         82.03 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py)        | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_cityscapes_20200606_114143-068fcfe9.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_cityscapes_20200606_114143.log.json)                             |
+| DeepLabV3+ (FP16)| R-101-D8 | 512x1024  |   80000 | 6.35     | 7.87           | 80.46 |             - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-f1104f4b.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920.log.json) |
 | DeepLabV3+ | R-18-D8         | 769x769   |   80000 | 2.5      | 5.74           | 76.26 |         77.91 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r18-d8_769x769_80k_cityscapes.py)          | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_769x769_80k_cityscapes/deeplabv3plus_r18-d8_769x769_80k_cityscapes_20201226_083346-f326e06a.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r18-d8_769x769_80k_cityscapes/deeplabv3plus_r18-d8_769x769_80k_cityscapes-20201226_083346.log.json)                                     |
 | DeepLabV3+ | R-50-D8         | 769x769   |   80000 | -        | -              | 79.83 |         81.48 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes.py)          | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes/deeplabv3plus_r50-d8_769x769_80k_cityscapes_20200606_210233-0e9dfdc4.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r50-d8_769x769_80k_cityscapes/deeplabv3plus_r50-d8_769x769_80k_cityscapes_20200606_210233.log.json)                                     |
 | DeepLabV3+ | R-101-D8        | 769x769   |   80000 | -        | -              | 80.98 |         82.18 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r101-d8_769x769_80k_cityscapes.py)         | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_769x769_80k_cityscapes/deeplabv3plus_r101-d8_769x769_80k_cityscapes_20200607_000405-a7573d20.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_769x769_80k_cityscapes/deeplabv3plus_r101-d8_769x769_80k_cityscapes_20200607_000405.log.json)                                 |
@@ -83,3 +84,7 @@
 | ---------- | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | -------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
 | DeepLabV3+ | R-101-D8 | 480x480   |   40000 | -        | -           | 52.86 |         54.54 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59_20210416_111233-ed937f15.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59/deeplabv3plus_r101-d8_480x480_40k_pascal_context_59-20210416_111233.log.json) |
 | DeepLabV3+ | R-101-D8 | 480x480   |   80000 | -        | -              | 53.2 |         54.67 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59_20210416_111127-7ca0331d.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59/deeplabv3plus_r101-d8_480x480_80k_pascal_context_59-20210416_111127.log.json) |
+
+Note:
+
+- `FP16` means Mixed Precision (FP16) is adopted in training.
diff --git a/configs/deeplabv3plus/deeplabv3plus.yml b/configs/deeplabv3plus/deeplabv3plus.yml
index ff78da3..7b54f50 100644
--- a/configs/deeplabv3plus/deeplabv3plus.yml
+++ b/configs/deeplabv3plus/deeplabv3plus.yml
@@ -152,6 +152,27 @@ Models:
       mIoU(ms+flip): 82.03
   Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_cityscapes_20200606_114143-068fcfe9.pth
+- Name: deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes
+  In Collection: deeplabv3plus
+  Metadata:
+    backbone: R-101-D8
+    crop size: (512,1024)
+    lr schd: 80000
+    inference time (ms/im):
+    - value: 127.06
+      hardware: V100
+      backend: PyTorch
+      batch size: 1
+      mode: FP16
+      resolution: (512,1024)
+    memory (GB): 6.35
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 80.46
+  Config: configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230920-f1104f4b.pth
 - Name: deeplabv3plus_r18-d8_769x769_80k_cityscapes
   In Collection: deeplabv3plus
   Metadata:
diff --git a/configs/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py b/configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py
similarity index 62%
rename from configs/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py
rename to configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py
index 1d7e1be..fc36940 100644
--- a/configs/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py
+++ b/configs/deeplabv3plus/deeplabv3plus_r101-d8_fp16_512x1024_80k_cityscapes.py
@@ -1,4 +1,4 @@
-_base_ = '../deeplabv3/deeplabv3_r101-d8_512x1024_80k_cityscapes.py'
+_base_ = './deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py'
 # fp16 settings
 optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.)
 # fp16 placeholder
diff --git a/configs/fcn/README.md b/configs/fcn/README.md
index d33f402..3a2712a 100644
--- a/configs/fcn/README.md
+++ b/configs/fcn/README.md
@@ -39,6 +39,7 @@
 | FCN    | R-18-D8    | 512x1024  |   80000 | 1.7      | 14.65          | 71.11 |         72.91 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r18-d8_512x1024_80k_cityscapes.py)       | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r18-d8_512x1024_80k_cityscapes/fcn_r18-d8_512x1024_80k_cityscapes_20201225_021327-6c50f8b4.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r18-d8_512x1024_80k_cityscapes/fcn_r18-d8_512x1024_80k_cityscapes-20201225_021327.log.json)         |
 | FCN    | R-50-D8    | 512x1024  |   80000 | -        |                | 73.61 |         74.24 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r50-d8_512x1024_80k_cityscapes.py)       | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r50-d8_512x1024_80k_cityscapes/fcn_r50-d8_512x1024_80k_cityscapes_20200606_113019-03aa804d.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r50-d8_512x1024_80k_cityscapes/fcn_r50-d8_512x1024_80k_cityscapes_20200606_113019.log.json)         |
 | FCN    | R-101-D8   | 512x1024  |   80000 | -        | -              | 75.13 |         75.94 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r101-d8_512x1024_80k_cityscapes.py)      | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_512x1024_80k_cityscapes/fcn_r101-d8_512x1024_80k_cityscapes_20200606_113038-3fb937eb.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_512x1024_80k_cityscapes/fcn_r101-d8_512x1024_80k_cityscapes_20200606_113038.log.json)     |
+| FCN (FP16)| R-101-D8 | 512x1024 |   80000 | 5.37    | 8.64           | 76.80 |             - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes.py)           | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes/fcn_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230921-fb13e883.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes/fcn_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230921.log.json)                                         |
 | FCN    | R-18-D8    | 769x769   |   80000 | 1.9      | 6.40           | 70.80 |         73.16 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r18-d8_769x769_80k_cityscapes.py)        | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r18-d8_769x769_80k_cityscapes/fcn_r18-d8_769x769_80k_cityscapes_20201225_021451-9739d1b8.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r18-d8_769x769_80k_cityscapes/fcn_r18-d8_769x769_80k_cityscapes-20201225_021451.log.json)             |
 | FCN    | R-50-D8    | 769x769   |   80000 | -        | -              | 72.64 |         73.32 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r50-d8_769x769_80k_cityscapes.py)        | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r50-d8_769x769_80k_cityscapes/fcn_r50-d8_769x769_80k_cityscapes_20200606_195749-f5caeabc.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r50-d8_769x769_80k_cityscapes/fcn_r50-d8_769x769_80k_cityscapes_20200606_195749.log.json)             |
 | FCN    | R-101-D8   | 769x769   |   80000 | -        | -              | 75.52 |         76.61 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r101-d8_769x769_80k_cityscapes.py)       | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_769x769_80k_cityscapes/fcn_r101-d8_769x769_80k_cityscapes_20200606_214354-45cbac68.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_769x769_80k_cityscapes/fcn_r101-d8_769x769_80k_cityscapes_20200606_214354.log.json)         |
@@ -92,3 +93,7 @@
 | ------ | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | ------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
 | FCN    | R-101-D8 | 480x480   |   40000 | -        | -           | 48.42 |         50.4 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r101-d8_480x480_40k_pascal_context_59.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_480x480_40k_pascal_context_59/fcn_r101-d8_480x480_40k_pascal_context_59_20210415_230724-8cf83682.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_480x480_40k_pascal_context_59/fcn_r101-d8_480x480_40k_pascal_context_59-20210415_230724.log.json) |
 | FCN    | R-101-D8 | 480x480   |   80000 | -        | -              | 49.35 |         51.38 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fcn/fcn_r101-d8_480x480_80k_pascal_context_59.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_480x480_80k_pascal_context_59/fcn_r101-d8_480x480_80k_pascal_context_59_20210416_110804-9a6f2c94.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_480x480_80k_pascal_context_59/fcn_r101-d8_480x480_80k_pascal_context_59-20210416_110804.log.json) |
+
+Note:
+
+- `FP16` means Mixed Precision (FP16) is adopted in training.
diff --git a/configs/fcn/fcn.yml b/configs/fcn/fcn.yml
index 3f889c4..fa6e576 100644
--- a/configs/fcn/fcn.yml
+++ b/configs/fcn/fcn.yml
@@ -155,6 +155,27 @@ Models:
       mIoU(ms+flip): 75.94
   Config: configs/fcn/fcn_r101-d8_512x1024_80k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_512x1024_80k_cityscapes/fcn_r101-d8_512x1024_80k_cityscapes_20200606_113038-3fb937eb.pth
+- Name: fcn_r101-d8_fp16_512x1024_80k_cityscapes
+  In Collection: fcn
+  Metadata:
+    backbone: R-101-D8
+    crop size: (512,1024)
+    lr schd: 80000
+    inference time (ms/im):
+    - value: 115.74
+      hardware: V100
+      backend: PyTorch
+      batch size: 1
+      mode: FP16
+      resolution: (512,1024)
+    memory (GB): 5.37
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 76.8
+  Config: configs/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes/fcn_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230921-fb13e883.pth
 - Name: fcn_r18-d8_769x769_80k_cityscapes
   In Collection: fcn
   Metadata:
diff --git a/configs/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py b/configs/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes.py
similarity index 67%
rename from configs/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py
rename to configs/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes.py
index 8e85e56..c6739d9 100644
--- a/configs/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py
+++ b/configs/fcn/fcn_r101-d8_fp16_512x1024_80k_cityscapes.py
@@ -1,4 +1,4 @@
-_base_ = '../fcn/fcn_r101-d8_512x1024_80k_cityscapes.py'
+_base_ = './fcn_r101-d8_512x1024_80k_cityscapes.py'
 # fp16 settings
 optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.)
 # fp16 placeholder
diff --git a/configs/fp16/README.md b/configs/fp16/README.md
deleted file mode 100644
index bbc73cc..0000000
--- a/configs/fp16/README.md
+++ /dev/null
@@ -1,34 +0,0 @@
-# Mixed Precision Training
-
-## Introduction
-
-<!-- [OTHERS] -->
-
-<a href="https://github.com/baidu-research/DeepBench">Official Repo</a>
-
-<a href="https://github.com/open-mmlab/mmcv/blob/v1.3.14/mmcv/runner/hooks/optimizer.py#L134">Code Snippet</a>
-
-<details>
-<summary align="right"><a href="https://arxiv.org/abs/1710.03740">Mixed Precision (FP16) Training (ArXiv'2017)</a></summary>
-
-```latex
-@article{micikevicius2017mixed,
-  title={Mixed precision training},
-  author={Micikevicius, Paulius and Narang, Sharan and Alben, Jonah and Diamos, Gregory and Elsen, Erich and Garcia, David and Ginsburg, Boris and Houston, Michael and Kuchaiev, Oleksii and Venkatesh, Ganesh and others},
-  journal={arXiv preprint arXiv:1710.03740},
-  year={2017}
-}
-```
-
-</details>
-
-## Results and models
-
-### Cityscapes
-
-| Method     | Backbone | Crop Size | Lr schd | Mem (GB) | Inf time (fps) |  mIoU | mIoU(ms+flip) | config                                                                                                                                | download                                                                                                                                                                                                                                                                                                                                                                                 |
-| ---------- | -------- | --------- | ------: | -------- | -------------- | ----: | ------------: | ------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| FCN        | R-101-D8 | 512x1024  |   80000 | 5.37     | 8.64           | 76.80 |             - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py)           | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes/fcn_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230921-50245227.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes/fcn_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230921.log.json)                                         |
-| PSPNet     | R-101-D8 | 512x1024  |   80000 | 5.34     | 8.77           | 79.46 |             - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py)        | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes/pspnet_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230919-ade37931.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes/pspnet_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230919.log.json)                             |
-| DeepLabV3  | R-101-D8 | 512x1024  |   80000 | 5.75     | 3.86           | 80.48 |             - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py)     | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230920-bc86dc84.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230920.log.json)                 |
-| DeepLabV3+ | R-101-D8 | 512x1024  |   80000 | 6.35     | 7.87           | 80.46 |             - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230920-cc58bc8d.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230920.log.json) |
diff --git a/configs/fp16/fp16.yml b/configs/fp16/fp16.yml
deleted file mode 100644
index 755642e..0000000
--- a/configs/fp16/fp16.yml
+++ /dev/null
@@ -1,99 +0,0 @@
-Collections:
-- Name: fp16
-  Metadata:
-    Training Data:
-    - Cityscapes
-  Paper:
-    URL: https://arxiv.org/abs/1710.03740
-    Title: Mixed Precision Training
-  README: configs/fp16/README.md
-  Code:
-    URL: https://github.com/open-mmlab/mmcv/blob/v1.3.14/mmcv/runner/hooks/optimizer.py#L134
-    Version: v1.3.14
-  Converted From:
-    Code: https://github.com/baidu-research/DeepBench
-Models:
-- Name: fcn_r101-d8_512x1024_80k_fp16_cityscapes
-  In Collection: fp16
-  Metadata:
-    backbone: R-101-D8
-    crop size: (512,1024)
-    lr schd: 80000
-    inference time (ms/im):
-    - value: 115.74
-      hardware: V100
-      backend: PyTorch
-      batch size: 1
-      mode: FP32
-      resolution: (512,1024)
-    memory (GB): 5.37
-  Results:
-  - Task: Semantic Segmentation
-    Dataset: Cityscapes
-    Metrics:
-      mIoU: 76.8
-  Config: configs/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes.py
-  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fp16/fcn_r101-d8_512x1024_80k_fp16_cityscapes/fcn_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230921-50245227.pth
-- Name: pspnet_r101-d8_512x1024_80k_fp16_cityscapes
-  In Collection: fp16
-  Metadata:
-    backbone: R-101-D8
-    crop size: (512,1024)
-    lr schd: 80000
-    inference time (ms/im):
-    - value: 114.03
-      hardware: V100
-      backend: PyTorch
-      batch size: 1
-      mode: FP32
-      resolution: (512,1024)
-    memory (GB): 5.34
-  Results:
-  - Task: Semantic Segmentation
-    Dataset: Cityscapes
-    Metrics:
-      mIoU: 79.46
-  Config: configs/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes.py
-  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fp16/pspnet_r101-d8_512x1024_80k_fp16_cityscapes/pspnet_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230919-ade37931.pth
-- Name: deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes
-  In Collection: fp16
-  Metadata:
-    backbone: R-101-D8
-    crop size: (512,1024)
-    lr schd: 80000
-    inference time (ms/im):
-    - value: 259.07
-      hardware: V100
-      backend: PyTorch
-      batch size: 1
-      mode: FP32
-      resolution: (512,1024)
-    memory (GB): 5.75
-  Results:
-  - Task: Semantic Segmentation
-    Dataset: Cityscapes
-    Metrics:
-      mIoU: 80.48
-  Config: configs/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes.py
-  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230920-bc86dc84.pth
-- Name: deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes
-  In Collection: fp16
-  Metadata:
-    backbone: R-101-D8
-    crop size: (512,1024)
-    lr schd: 80000
-    inference time (ms/im):
-    - value: 127.06
-      hardware: V100
-      backend: PyTorch
-      batch size: 1
-      mode: FP32
-      resolution: (512,1024)
-    memory (GB): 6.35
-  Results:
-  - Task: Semantic Segmentation
-    Dataset: Cityscapes
-    Metrics:
-      mIoU: 80.46
-  Config: configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py
-  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes_20200717_230920-cc58bc8d.pth
diff --git a/configs/pspnet/README.md b/configs/pspnet/README.md
index 72b280a..ad7fcdf 100644
--- a/configs/pspnet/README.md
+++ b/configs/pspnet/README.md
@@ -35,6 +35,7 @@
 | PSPNet | R-18-D8   | 512x1024  |   80000 | 1.7      | 15.71          | 74.87 |         76.04 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r18-d8_512x1024_80k_cityscapes.py)   | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r18-d8_512x1024_80k_cityscapes/pspnet_r18-d8_512x1024_80k_cityscapes_20201225_021458-09ffa746.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r18-d8_512x1024_80k_cityscapes/pspnet_r18-d8_512x1024_80k_cityscapes-20201225_021458.log.json)         |
 | PSPNet | R-50-D8   | 512x1024  |   80000 | -        | -              | 78.55 |         79.79 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r50-d8_512x1024_80k_cityscapes.py)   | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x1024_80k_cityscapes/pspnet_r50-d8_512x1024_80k_cityscapes_20200606_112131-2376f12b.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x1024_80k_cityscapes/pspnet_r50-d8_512x1024_80k_cityscapes_20200606_112131.log.json)         |
 | PSPNet | R-101-D8  | 512x1024  |   80000 | -        | -              | 79.76 |         81.01 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py)  | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes/pspnet_r101-d8_512x1024_80k_cityscapes_20200606_112211-e1e1100f.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes/pspnet_r101-d8_512x1024_80k_cityscapes_20200606_112211.log.json)     |
+| PSPNet (FP16) | R-101-D8 | 512x1024  |   80000 | 5.34     | 8.77           | 79.46 |             - | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py)        | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes/pspnet_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230919-a0875e5c.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes/pspnet_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230919.log.json)                             |
 | PSPNet | R-18-D8   | 769x769   |   80000 | 1.9      | 6.20           | 75.90 |         77.86 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r18-d8_769x769_80k_cityscapes.py)    | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r18-d8_769x769_80k_cityscapes/pspnet_r18-d8_769x769_80k_cityscapes_20201225_021458-3deefc62.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r18-d8_769x769_80k_cityscapes/pspnet_r18-d8_769x769_80k_cityscapes-20201225_021458.log.json)             |
 | PSPNet | R-50-D8   | 769x769   |   80000 | -        | -              | 79.59 |         80.69 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r50-d8_769x769_80k_cityscapes.py)    | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_769x769_80k_cityscapes/pspnet_r50-d8_769x769_80k_cityscapes_20200606_210121-5ccf03dd.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_769x769_80k_cityscapes/pspnet_r50-d8_769x769_80k_cityscapes_20200606_210121.log.json)             |
 | PSPNet | R-101-D8  | 769x769   |   80000 | -        | -              | 79.77 |         81.06 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet/pspnet_r101-d8_769x769_80k_cityscapes.py)   | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_769x769_80k_cityscapes/pspnet_r101-d8_769x769_80k_cityscapes_20200606_225055-dba412fa.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_769x769_80k_cityscapes/pspnet_r101-d8_769x769_80k_cityscapes_20200606_225055.log.json)         |
@@ -112,3 +113,7 @@ We support evaluation results on these two datasets using models above trained o
 | PSPNet | R-101-D8 | 512x512   |  160000 | -        | -              | 41.28 |         41.66 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet_r101-d8_512x512_4x4_160k_coco-stuff164k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x512_4x4_160k_coco-stuff164k/pspnet_r101-d8_512x512_4x4_160k_coco-stuff164k_20210707_152004-4af9621b.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x512_4x4_160k_coco-stuff164k/pspnet_r101-d8_512x512_4x4_160k_coco-stuff164k_20210707_152004.log.json) |
 | PSPNet | R-50-D8  | 512x512   |  320000 | -        | -              | 40.53 |         40.75 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet_r50-d8_512x512_4x4_320k_coco-stuff164k.py)  | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x512_4x4_320k_coco-stuff164k/pspnet_r50-d8_512x512_4x4_320k_coco-stuff164k_20210707_152004-be9610cc.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r50-d8_512x512_4x4_320k_coco-stuff164k/pspnet_r50-d8_512x512_4x4_320k_coco-stuff164k_20210707_152004.log.json)     |
 | PSPNet | R-101-D8 | 512x512   |  320000 | -        | -              | 41.95 |         42.42 | [config](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/pspnet_r101-d8_512x512_4x4_320k_coco-stuff164k.py) | [model](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x512_4x4_320k_coco-stuff164k/pspnet_r101-d8_512x512_4x4_320k_coco-stuff164k_20210707_152004-72220c60.pth) &#124; [log](https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x512_4x4_320k_coco-stuff164k/pspnet_r101-d8_512x512_4x4_320k_coco-stuff164k_20210707_152004.log.json) |
+
+Note:
+
+- `FP16` means Mixed Precision (FP16) is adopted in training.
diff --git a/configs/pspnet/pspnet.yml b/configs/pspnet/pspnet.yml
index 4b3cd1f..1a46b46 100644
--- a/configs/pspnet/pspnet.yml
+++ b/configs/pspnet/pspnet.yml
@@ -158,6 +158,27 @@ Models:
       mIoU(ms+flip): 81.01
   Config: configs/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes.py
   Weights: https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_512x1024_80k_cityscapes/pspnet_r101-d8_512x1024_80k_cityscapes_20200606_112211-e1e1100f.pth
+- Name: pspnet_r101-d8_fp16_512x1024_80k_cityscapes
+  In Collection: pspnet
+  Metadata:
+    backbone: R-101-D8
+    crop size: (512,1024)
+    lr schd: 80000
+    inference time (ms/im):
+    - value: 114.03
+      hardware: V100
+      backend: PyTorch
+      batch size: 1
+      mode: FP16
+      resolution: (512,1024)
+    memory (GB): 5.34
+  Results:
+  - Task: Semantic Segmentation
+    Dataset: Cityscapes
+    Metrics:
+      mIoU: 79.46
+  Config: configs/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py
+  Weights: https://download.openmmlab.com/mmsegmentation/v0.5/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes/pspnet_r101-d8_fp16_512x1024_80k_cityscapes_20200717_230919-a0875e5c.pth
 - Name: pspnet_r18-d8_769x769_80k_cityscapes
   In Collection: pspnet
   Metadata:
diff --git a/configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py b/configs/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py
similarity index 60%
rename from configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py
rename to configs/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py
index eaf569d..c71b7f6 100644
--- a/configs/fp16/deeplabv3plus_r101-d8_512x1024_80k_fp16_cityscapes.py
+++ b/configs/pspnet/pspnet_r101-d8_fp16_512x1024_80k_cityscapes.py
@@ -1,4 +1,4 @@
-_base_ = '../deeplabv3plus/deeplabv3plus_r101-d8_512x1024_80k_cityscapes.py'
+_base_ = './pspnet_r101-d8_512x1024_80k_cityscapes.py'
 # fp16 settings
 optimizer_config = dict(type='Fp16OptimizerHook', loss_scale=512.)
 # fp16 placeholder
diff --git a/docs/model_zoo.md b/docs/model_zoo.md
index 7babd2e..ce23b53 100644
--- a/docs/model_zoo.md
+++ b/docs/model_zoo.md
@@ -129,7 +129,7 @@ Please refer to [CGNet](https://github.com/open-mmlab/mmsegmentation/blob/master
 
 ### Mixed Precision (FP16) Training
 
-Please refer [Mixed Precision (FP16) Training](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fp16) for details.
+Please refer [Mixed Precision (FP16) Training] on BiSeNetV2 (https://github.com/open-mmlab/mmsegmentation/blob/master/configs/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py) for details.
 
 ### U-Net
 
diff --git a/docs_zh-CN/model_zoo.md b/docs_zh-CN/model_zoo.md
index a7f6ead..a165865 100644
--- a/docs_zh-CN/model_zoo.md
+++ b/docs_zh-CN/model_zoo.md
@@ -119,7 +119,7 @@
 
 ### Mixed Precision (FP16) Training
 
-Please refer [Mixed Precision (FP16) Training](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/fp16/README.md) for details.
+请参考 [Mixed Precision (FP16) Training] 在 BiSeNetV2 训练的样例 (https://github.com/open-mmlab/mmsegmentation/blob/master/configs/bisenetv2/bisenetv2_fcn_fp16_4x4_1024x1024_160k_cityscapes.py) for details.
 
 ## 速度标定
 
diff --git a/model-index.yml b/model-index.yml
index 00da8d6..487bafd 100644
--- a/model-index.yml
+++ b/model-index.yml
@@ -16,7 +16,6 @@ Import:
 - configs/fastfcn/fastfcn.yml
 - configs/fastscnn/fastscnn.yml
 - configs/fcn/fcn.yml
-- configs/fp16/fp16.yml
 - configs/gcnet/gcnet.yml
 - configs/hrnet/hrnet.yml
 - configs/icnet/icnet.yml