update sample.sh

wl-zhao · Feb 9, 2023 · 4588ff8 · 4588ff8
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diff --git a/example/stable-diffusion/README.md b/example/stable-diffusion/README.md
@@ -4,7 +4,7 @@ UniPC can accelerate both the conditional and unconditional sampling by stable-d
 
 ```bash
 CKPT=models/ldm/ffhq256/model.ckpt
-python3 -m torch.distributed.launch --nproc_per_node=8 --master_port=$PORT scripts/sample_diffusion_ddp.py -r $CKPT \
+python3 -m torch.distributed.launch --nproc_per_node=8 scripts/sample_diffusion_ddp.py -r $CKPT \
 	-n 50000 -l samples/ffhq/uni_pc -c 10 --uni_pc --batch_size 20
 
 ```
@@ -17,7 +17,6 @@ from ldm.models.diffusion.uni_pc import UniPCSampler
 
 and use the UniPCSampler instead of the default DDIMSampler.
 
-
 ---
 
 *Stable Diffusion was made possible thanks to a collaboration with [Stability AI](https://stability.ai/) and [Runway](https://runwayml.com/) and builds upon our previous work:*

diff --git a/example/stable-diffusion/sample.sh b/example/stable-diffusion/sample.sh
@@ -1,3 +1,3 @@
 CKPT=models/ldm/ffhq256/model.ckpt
-CUDA_VISIBLE_DEVICES=0,1 python3 -m torch.distributed.launch --nproc_per_node=2 --master_port=$PORT scripts/sample_diffusion_ddp.py -r $CKPT \
+CUDA_VISIBLE_DEVICES=0,1 python3 -m torch.distributed.launch --nproc_per_node=2 scripts/sample_diffusion_ddp.py -r $CKPT \
 	-n 50000 -l samples/ffhq/uni_pc ${@:2} -c 10 --uni_pc --batch_size 20