update

app.py

@@ -32,18 +32,18 @@ import numpy as np
 import torch as th
 import torch.distributed as dist
 
-# def install_dependency():
-#     # install apex
-#     subprocess.run(
-#         f'FORCE_CUDA=1 {sys.executable} -m pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" git+https://github.com/NVIDIA/apex.git@master',
-#         shell=True,
-#     )
+def install_dependency():
+    # install apex
+    subprocess.run(
+        f'FORCE_CUDA=1 {sys.executable} -m pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" git+https://github.com/NVIDIA/apex.git@master',
+        shell=True,
+    )
 
 th.backends.cuda.matmul.allow_tf32 = True
 th.backends.cudnn.allow_tf32 = True
 th.backends.cudnn.enabled = True
 
-# install_dependency()
+install_dependency()
 
 from guided_diffusion import dist_util, logger
 from guided_diffusion.script_util import (
@@ -457,7 +457,8 @@ if __name__ == "__main__":
 
     args = create_argparser().parse_args()
 
-    args.local_rank = int(os.environ["LOCAL_RANK"])
+    # args.local_rank = int(os.environ["LOCAL_RANK"])
+    args.local_rank = 0
     args.gpus = th.cuda.device_count()
 
     args.rendering_kwargs = rendering_options_defaults(args)
@@ -474,3 +475,4 @@ if __name__ == "__main__":
         return f"Hello {zero + n} Tensor"
 
     demo = gr.Interface(fn=greet, inputs=gr.Number(), outputs=gr.Text())
+    demo.launch()