Update Docker environment to Ubuntu 22, Python 3.10

[fpjentzsch]

Updates the base Docker image to Ubuntu 22.04, where Python 3.10 is the default. Some dependencies are updated alongside.

Fixes https://github.com/Xilinx/finn/issues/766.

Tested so far:

• [x] Quicktest
• [ ] Full test suite
• [x] Cybsec notebooks
• [ ] Other notebooks
• [x] CUDA support (FINN_DOCKER_GPU=1)
• [x] Full Zynq build
• [ ] Full Alveo build
• [x] Vitis/Vivado 2022.2
• [x] Vitis/Vivado 2023.1
• [x] Linting

Issues:

• pip install --user--editable is broken for certain packages (here: qonnx)
  • See https://github.com/pypa/pip/issues/7953
  • -> Workaround applied
• Xilinx tools crash during synthesis due to FlexLM issue
  • See Revenera forum
  • -> Workaround applied
• The update from PyTorch 1.7/ONNX v6/ai.onnx v9 to PyTorch 1.13.1/ONNX v7/ai.onnx v14 causes different finn-onnx export behavior in Brevitas (tested 0.8.0 and 0.9.1):
  • Primary input tensor name is not always "0", this was previously assumed
  • -> Workaround by providing "input_names" explicitly to export function
  • In certain cases the exported graph will no longer exhibit unique parameter tensors
  • -> Workaround by calling GiveUniqueParameterTensors()
• Linting: as of now, the following reformattings would take place:
  • Minor automatic changes (e.g., addition/removal of empty lines) to 22 files
  • Line length limit (currently 88 characters) was previously not always enforced for multi-line strings ("""). After this update, a few occurences are slightly over the limit (13 lines in 11 files)

Depends on:

• [x] https://github.com/fastmachinelearning/qonnx/pull/58 (update commit-hash accordingly)

[fpjentzsch]

Combining this with the update to 2023.1 tools by merging into feature/2023_1. Some issues, such as updating qonnx and fixing the linting, remain and will be fixed in that branch before merging to dev.