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937b41e3b5
In this series of PR we intend to refactor pipeline parallelism test cases to enable to be completely device agnostic. These changes will include the following approaches to do the same : - Allowing for multiple device types using instantiate_device_type_test - Replacing calls to cuda stream with torch.get_device_module(device) wherever it applies This should result in improvement in usability for all devices For this PR we have shown support for the following devices: - CPU (wherever applicable) - CUDA - HPU - XPU To add other device new users can simply append their device to the device list Pull Request resolved: https://github.com/pytorch/pytorch/pull/146472 Approved by: https://github.com/H-Huang |
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| .. | ||
| artifacts | ||
| __init__.py | ||
| model_registry.py | ||
| schedule_registry.py | ||
| test_backward.py | ||
| test_microbatch.py | ||
| test_pipe.py | ||
| test_schedule_multiproc.py | ||
| test_schedule.py | ||
| test_stage.py | ||
| test_transformer.py | ||
| test_unflatten.py | ||