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fp16.yml
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fp16.yml
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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