update dep

Dockerfile

@@ -0,0 +1,31 @@
+FROM docker.io/library/python:3.10.13@sha256:d5b1fbbc00fd3b55620a9314222498bebf09c4bf606425bf464709ed6a79f202
+
+RUN apt-get update && apt-get install -y 	git 	git-lfs 	ffmpeg 	libsm6 	libxext6 	cmake 	rsync 	libgl1-mesa-glx 	&& rm -rf /var/lib/apt/lists/* 	&& git lfs install
+
+RUN pip install --no-cache-dir pip==22.3.1 && 	pip install --no-cache-dir 	datasets 	"huggingface-hub>=0.19" "hf-transfer>=0.1.4" "protobuf<4" "click<8.1" "pydantic~=1.0" torch==2.3.1
+
+RUN apt-get update && apt-get install -y fakeroot &&     mv /usr/bin/apt-get /usr/bin/.apt-get &&     echo '#!/usr/bin/env sh\nfakeroot /usr/bin/.apt-get $@' > /usr/bin/apt-get &&     chmod +x /usr/bin/apt-get && 	rm -rf /var/lib/apt/lists/* && 	useradd -m -u 1000 user
+
+COPY --chown=1000:1000 --from=root / /
+
+RUN --mount=target=/tmp/requirements.txt,source=requirements.txt     pip install --no-cache-dir -r /tmp/requirements.txt
+
+RUN pip freeze > /tmp/freeze.txt
+
+WORKDIR /home/user/app
+
+RUN pip install --no-cache-dir 	gradio[oauth]==4.25.0 	"uvicorn>=0.14.0" 	spaces==0.29.3
+
+COPY --link --chown=1000 ./ /home/user/app
+
+COPY --from=pipfreeze --link --chown=1000 /tmp/freeze.txt /tmp/freeze.txt
+
+# ENV PYTHONPATH=${HOME}/app \
+#     PYTHONUNBUFFERED=1 \
+#     GRADIO_ALLOW_FLAGGING=never \
+#     GRADIO_NUM_PORTS=1 \
+#     GRADIO_SERVER_NAME=0.0.0.0 \
+#     GRADIO_THEME=huggingface \
+#     SYSTEM=spaces
+
+CMD ["python", "app.py"]

app.py

@@ -32,6 +32,56 @@ import numpy as np
 import torch as th
 import torch.distributed as dist
 
+def install_dependency():
+    # install full cuda first
+    # subprocess.run(
+    #     f'conda install -c nvidia cuda-nvcc',
+    #     shell=True
+    # )
+
+    # install apex
+    subprocess.run(
+        f'TORCH_CUDA_ARCH_LIST="compute capability" 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()
+
+from guided_diffusion import dist_util, logger
+from guided_diffusion.script_util import (
+    NUM_CLASSES,
+    model_and_diffusion_defaults,
+    create_model_and_diffusion,
+    add_dict_to_argparser,
+    args_to_dict,
+    continuous_diffusion_defaults,
+    control_net_defaults,
+)
+
+from pathlib import Path
+
+from tqdm import tqdm, trange
+import dnnlib
+from nsr.train_util_diffusion import TrainLoop3DDiffusion as TrainLoop
+from guided_diffusion.continuous_diffusion import make_diffusion as make_sde_diffusion
+import nsr
+import nsr.lsgm
+from nsr.script_util import create_3DAE_model, encoder_and_nsr_defaults, loss_defaults, AE_with_Diffusion, rendering_options_defaults, eg3d_options_default, dataset_defaults
+
+from datasets.shapenet import load_eval_data
+from torch.utils.data import Subset
+from datasets.eg3d_dataset import init_dataset_kwargs
+
+from transport.train_utils import parse_transport_args
+
+from utils.infer_utils import remove_background, resize_foreground
+
+SEED = 0
+
 
 def resize_to_224(img):
     img = transforms.functional.resize(img, 224,
@@ -411,75 +461,27 @@ if __name__ == "__main__":
     os.environ[
         "TORCH_DISTRIBUTED_DEBUG"] = "DETAIL"  # set to DETAIL for runtime logging.
 
+    args = create_argparser().parse_args()
 
-    zero = torch.Tensor([0]).cuda()
-    print(zero.device) # <-- 'cpu' 🤔
-
-    @spaces.GPU
-    def greet(n):
-
-        def install_dependency():
-            # install full cuda first
-            # subprocess.run(
-            #     f'conda install -c nvidia cuda-nvcc',
-            #     shell=True
-            # )
-
-            # install apex
-            subprocess.run(
-                f'TORCH_CUDA_ARCH_LIST="compute capability" 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,
-            )
+    # args.local_rank = int(os.environ["LOCAL_RANK"])
+    args.local_rank = 0
+    args.gpus = th.cuda.device_count()
 
-        th.backends.cuda.matmul.allow_tf32 = True
-        th.backends.cudnn.allow_tf32 = True
-        th.backends.cudnn.enabled = True
-
-        install_dependency()
-
-        from guided_diffusion import dist_util, logger
-        from guided_diffusion.script_util import (
-            NUM_CLASSES,
-            model_and_diffusion_defaults,
-            create_model_and_diffusion,
-            add_dict_to_argparser,
-            args_to_dict,
-            continuous_diffusion_defaults,
-            control_net_defaults,
-        )
+    args.rendering_kwargs = rendering_options_defaults(args)
 
-        from pathlib import Path
 
-        from tqdm import tqdm, trange
-        import dnnlib
-        from nsr.train_util_diffusion import TrainLoop3DDiffusion as TrainLoop
-        from guided_diffusion.continuous_diffusion import make_diffusion as make_sde_diffusion
-        import nsr
-        import nsr.lsgm
-        from nsr.script_util import create_3DAE_model, encoder_and_nsr_defaults, loss_defaults, AE_with_Diffusion, rendering_options_defaults, eg3d_options_default, dataset_defaults
+    # main(args)
 
-        from datasets.shapenet import load_eval_data
-        from torch.utils.data import Subset
-        from datasets.eg3d_dataset import init_dataset_kwargs
+    zero = torch.Tensor([0]).cuda()
+    print(zero.device) # <-- 'cpu' 🤔
 
-        from transport.train_utils import parse_transport_args
+    @spaces.GPU
+    def greet(n):
 
-        from utils.infer_utils import remove_background, resize_foreground
 
 
         print(zero.device) # <-- 'cuda:0' 🤗
         return f"Hello {zero + n} Tensor"
 
-        # args = create_argparser().parse_args()
-
-        # # 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)
-
-        # main(args)
-
-
     demo = gr.Interface(fn=greet, inputs=gr.Number(), outputs=gr.Text())
     demo.launch()