ci: mark model_parallel tests as cuda specific #35269
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`parallelize()` API is deprecated in favor of accelerate's `device_map="auto"` and therefore is not accepting new features. At the same time `parallelize()` implementation is currently CUDA-specific. This commit marks respective ci tests with `@require_torch_gpu`. Fixes: huggingface#35252 Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
dvrogozh
commented
Dec 13, 2024
| @@ -3046,6 +3046,7 @@ def test_multi_gpu_data_parallel_forward(self): | |||
| with torch.no_grad(): | |||
| _ = model(**self._prepare_for_class(inputs_dict, model_class)) | |||
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| @require_torch_gpu | |||
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@require_torch_multi_gpu on the next line was previously made non-CUDA specific by 11c27dd. Right now it sets requirement for having any multi-GPUs on the system.
I wonder, maybe it makes sense to rename @require_torch_gpu to @require_torch_cuda to avoid naming collision? I can follow up on that in separate PR.
This was referenced Dec 13, 2024
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parallelize()API is deprecated in favor of accelerate'sdevice_map="auto"and therefore is not accepting new features. At the same timeparallelize()implementation is currently CUDA-specific. This commit marks respective ci tests with@require_torch_gpu.Fixes: #35252
CC: @ArthurZucker @SunMarc