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Object Detection API Docker container fails to build with public key error #10799

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@cedarwarman

Description

@cedarwarman

Prerequisites

Please answer the following questions for yourself before submitting an issue.

  • [yes] I am using the latest TensorFlow Model Garden release and TensorFlow 2.
  • [yes] I am reporting the issue to the correct repository. (Model Garden official or research directory)
  • [yes] I checked to make sure that this issue has not already been filed.

1. The entire URL of the file you are using

https://github.com/tensorflow/models/blob/master/research/object_detection/dockerfiles/tf2/Dockerfile

2. Describe the bug

A clear and concise description of what the bug is.
During Docker build command, exits with code 100 and message:

"W: GPG error: https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  InRelease: The following signatures couldn't be verified because the public key is not available: NO_PUBKEY A4B469963BF863CC
E: The repository 'https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64  InRelease' is no longer signed."

3. Steps to reproduce

Steps to reproduce the behavior.

git clone https://github.com/tensorflow/models.git
# From the root of the git repository
docker build -f research/object_detection/dockerfiles/tf2/Dockerfile -t od .

4. Expected behavior

A clear and concise description of what you expected to happen.
Successful container build.

5. Additional context

Include any logs that would be helpful to diagnose the problem.

6. System information

  • OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 22.04.1 LTS
  • Mobile device name if the issue happens on a mobile device:
  • TensorFlow installed from (source or binary): Docker container
  • TensorFlow version (use command below): Docker container (2.2.0)
  • Python version:
  • Bazel version (if compiling from source):
  • GCC/Compiler version (if compiling from source):
  • CUDA/cuDNN version: System CUDA version 11.6
  • GPU model and memory: Nvidia A100 8 GB memory

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