Respect each example requirements and use uv#1330
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msaroufim merged 4 commits intopytorch:mainfrom Apr 26, 2025
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Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
Current version of the example requires `numpy<2` otherwise the following error can be seen: ``` AttributeError: module 'numpy' has no attribute 'bool8'. Did you mean: 'bool'? ``` Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
Current version of examples require `torch<2.6` otherwise the following
error can be seen:
```
File "/pytorch/examples/time_sequence_prediction/train.py", line 47, in <module>
data = torch.load('traindata.pt')
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/pytorch/examples/time_sequence_prediction/.venv/lib/python3.12/site-packages/torch/serialization.py", line 1524, in load
raise pickle.UnpicklingError(_get_wo_message(str(e))) from None
```
Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
This commit introduces few changes to CI by modifying `run_*_examples.sh` and respective github workflows: * Switched to uv * Added tearup and teardown stages for tests (`start()` and `stop()` methods wrapping up test bodies - these are called automatically) * Tearup (`start()`) installs example dependencies and, optionally (if `VIRTUAL_ENV=.venv` is passed), creates uv virtual environment * Teardown (`stop()`) removes uv virtual environment if it was created (to save space) * If no `VIRTUAL_ENV` set, then scripts expect to be executed in the existing virtual environment. These can be `python -m venv`, `uv env` or `conda env`. In this case example dependencies will be installed in this environment potentially reinstalling existing packages (including `torch`!). * Dropped automated detection of CUDA platform. Now scripts require `USE_CUDA=True` to be passed explicitly * Added `PIP_INSTALL_ARGS` environment variable to be passed to `uv pip install` calls for each example dependencies. This allows to adjust torch indices and other options. Execute all tests in current virtual environment (might rewrite packages): ``` ./run_distributed_examples.sh ``` Execute all tests creating separate environment for each example: ``` VIRTUAL_ENV=.venv ./run_distributed_examples.sh ``` Run with CUDA: ``` USE_CUDA=True ./run_distributed_examples.sh ``` Adjust index: ``` PIP_INSTALL_ARGS="--pre -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html" \ ./run_distributed_examples.sh ``` Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
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Nice! It's promising that CI is green. Will review asap |
msaroufim
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Apr 26, 2025
This was referenced Apr 29, 2025
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For: #1329
This commit introduces few changes to CI by modifying
run_*_examples.shand respective github workflows:start()andstop()methods wrapping up test bodies - these are called automatically)start()) installs example dependencies and, optionally (ifVIRTUAL_ENV=.venvis passed), creates uv virtual environmentstop()) removes uv virtual environment if it was created (to save space)VIRTUAL_ENVset, then scripts expect to be executed in the existing virtual environment. These can bepython -m venv,uv envorconda env. In this case example dependencies will be installed in this environment potentially reinstalling existing packages (includingtorch!).USE_CUDA=Trueto be passed explicitlyPIP_INSTALL_ARGSenvironment variable to be passed touv pip installcalls for each example dependencies. This allows to adjust torch indices and other options.Execute all tests in current virtual environment (might rewrite packages):
Execute all tests creating separate environment for each example:
Run with CUDA:
Adjust index:
Few changes were required in examples
requirements.txtfiles:reinforcement_learningrequirement for number to be<2due to:time_sequence_predictionandword_language_modelrequirement for torch to be<2.6due to:CC: @msaroufim, @malfet, @atalman