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re-enable PYTORCH_CUDA_ALLOC_CONF expandable_segments (#1765) [skip ci]

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Wing Lian
2024-07-17 15:38:26 -04:00
committed by GitHub
parent 8619b2d855
commit 8731b95d04
1 changed files with 5 additions and 5 deletions
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10
src/axolotl/train.py
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@@ -53,11 +53,11 @@ def train(
*, cfg: DictDefault, cli_args: TrainerCliArgs, dataset_meta: TrainDatasetMeta *, cfg: DictDefault, cli_args: TrainerCliArgs, dataset_meta: TrainDatasetMeta
) -> Tuple[Union[PeftModel, PreTrainedModel], PreTrainedTokenizer]: ) -> Tuple[Union[PeftModel, PreTrainedModel], PreTrainedTokenizer]:
# enable expandable segments for cuda allocation to improve VRAM usage # enable expandable segments for cuda allocation to improve VRAM usage
# torch_version = torch.__version__.split(".") torch_version = torch.__version__.split(".")
# torch_major, torch_minor = int(torch_version[0]), int(torch_version[1]) torch_major, torch_minor = int(torch_version[0]), int(torch_version[1])
# if torch_major == 2 and torch_minor >= 2: if torch_major == 2 and torch_minor >= 2:
# if os.getenv("PYTORCH_CUDA_ALLOC_CONF") is None: if os.getenv("PYTORCH_CUDA_ALLOC_CONF") is None:
# os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True" os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
# load the tokenizer first # load the tokenizer first
LOG.debug( LOG.debug(