Update train_with_DALI_en.md
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@ -49,8 +49,14 @@ python -m paddle.distributed.launch \
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## Train with FP16
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On the basis of the above, using FP16 half-precision can further improve the training speed, just add fields in the start training command `AMP.use_pure_fp16=True`:
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On the basis of the above, using FP16 half-precision can further improve the training speed, you can refer the following command.
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```shell
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python tools/static/train.py -c configs/ResNet/ResNet50.yaml -o use_dali=True -o AMP.use_pure_fp16=True
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export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
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export FLAGS_fraction_of_gpu_memory_to_use=0.8
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python -m paddle.distributed.launch \
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--gpus="0,1,2,3,4,5,6,7" \
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tools/static/train.py \
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-c configs/ResNet/ResNet50_fp16.yaml
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```
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