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[Trainer] Force is_model_parallel when model is loaded in multiple GPUs using accelerate #22532

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Merged
younesbelkada merged 6 commits into from
Apr 3, 2023
Merged

[Trainer] Force is_model_parallel when model is loaded in multiple GPUs using accelerate #22532

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1ccad27
add `is_model_parallel` arg on Trainer
younesbelkada Apr 3, 2023
316a1ec
add warning
younesbelkada Apr 3, 2023
8a0ddb9
adapt from suggestions
younesbelkada Apr 3, 2023
e394c09
revert t5 changes
younesbelkada Apr 3, 2023
d98c4c1
remove commas
younesbelkada Apr 3, 2023
5eb72b4
adapt from suggestions
younesbelkada Apr 3, 2023
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13 changes: 13 additions & 0 deletions src/transformers/trainer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -370,6 +370,19 @@ def __init__(
else:
self.is_model_parallel = False

if (
getattr(model, "hf_device_map", None) is not None
and len([device for device in set(model.hf_device_map.values()) if device not in ["cpu", "disk"]]) > 1
and not self.is_model_parallel
):
self.is_model_parallel = True

# warn users
logger.info(
"You have loaded a model on multiple GPUs. `is_model_parallel` attribute will be force-set"
" to `True` to avoid any unexpected behavior such as device placement mismatching."
)

# At this stage the model is already loaded
if getattr(model, "is_loaded_in_8bit", False):
if getattr(model, "_is_int8_training_enabled", False):
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