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FROM nvcr.io/nvidia/pytorch:21.10-py3 (#6379)

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21.12 generates dockerhub errors so rolling back to 21.10 with latest pytorch install. Not sure if this torch install will work on non-GPU dockerhub autobuild so this is an experiment.

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  1. Dockerfile +2 -2
Dockerfile CHANGED
@@ -1,7 +1,7 @@
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  # YOLOv5 πŸš€ by Ultralytics, GPL-3.0 license
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  # Start FROM Nvidia PyTorch image https://ngc.nvidia.com/catalog/containers/nvidia:pytorch
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- FROM nvcr.io/nvidia/pytorch:21.12-py3
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  # Install linux packages
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  RUN apt update && apt install -y zip htop screen libgl1-mesa-glx
@@ -12,7 +12,7 @@ RUN python -m pip install --upgrade pip
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  RUN pip uninstall -y nvidia-tensorboard nvidia-tensorboard-plugin-dlprof
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  RUN pip install --no-cache -r requirements.txt coremltools onnx gsutil notebook wandb>=0.12.2
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  RUN pip install --no-cache -U torch torchvision numpy Pillow
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- # RUN pip install --no-cache torch==1.10.1+cu113 torchvision==0.11.2+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
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  # Create working directory
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  RUN mkdir -p /usr/src/app
 
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  # YOLOv5 πŸš€ by Ultralytics, GPL-3.0 license
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  # Start FROM Nvidia PyTorch image https://ngc.nvidia.com/catalog/containers/nvidia:pytorch
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+ FROM nvcr.io/nvidia/pytorch:21.10-py3
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  # Install linux packages
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  RUN apt update && apt install -y zip htop screen libgl1-mesa-glx
 
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  RUN pip uninstall -y nvidia-tensorboard nvidia-tensorboard-plugin-dlprof
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  RUN pip install --no-cache -r requirements.txt coremltools onnx gsutil notebook wandb>=0.12.2
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  RUN pip install --no-cache -U torch torchvision numpy Pillow
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+ RUN pip install --no-cache torch==1.10.1+cu113 torchvision==0.11.2+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
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  # Create working directory
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  RUN mkdir -p /usr/src/app