[train] TransformersPredictor: Add support for custom pipeline class #36494
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added 2 commits
June 16, 2023 11:14
Signed-off-by: Kai Fricke <kai@anyscale.com>
Signed-off-by: Kai Fricke <kai@anyscale.com>
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I will add more test cases for the new code paths. |
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June 20, 2023 09:07
krfricke
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Jun 23, 2023
… pipeline class"" (#36705) Reverts #36701 This re-activates the changes in #36494 which were generally working. The problem was that an import of `TFPreTrainedModel` on a GPU instance seems to initialize the GPU and make it unusable by Ray workers, so that CUDA memory allocations fail. Thus, imports of TF modules should be guarded behind the TYPE_CHECKING variable: ``` if TYPE_CHECKING: # ... from transformers.modeling_utils import PreTrainedModel from transformers.modeling_tf_utils import TFPreTrainedModel ``` Signed-off-by: Kai Fricke <kai@anyscale.com>
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arvind-chandra
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Aug 31, 2023
…ay-project#36494) Creating a `TransformersPredictor` with a custom pipeline class is currently broken: The model can't be automatically inferred from a path. This only works in the transformers pipeline. This PR adds support for this by adding additional parameters to `TransformersPredictor.from_checkpoint()` that will call `TransformersCheckpoint.get_model()` to retrieve the model, if specified. Signed-off-by: Kai Fricke <kai@anyscale.com> Signed-off-by: e428265 <arvind.chandramouli@lmco.com>
arvind-chandra
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Aug 31, 2023
…e class (ray-project#36494)" (ray-project#36701) This reverts commit 7ed5c6d. Signed-off-by: e428265 <arvind.chandramouli@lmco.com>
arvind-chandra
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Aug 31, 2023
… pipeline class"" (ray-project#36705) Reverts ray-project#36701 This re-activates the changes in ray-project#36494 which were generally working. The problem was that an import of `TFPreTrainedModel` on a GPU instance seems to initialize the GPU and make it unusable by Ray workers, so that CUDA memory allocations fail. Thus, imports of TF modules should be guarded behind the TYPE_CHECKING variable: ``` if TYPE_CHECKING: # ... from transformers.modeling_utils import PreTrainedModel from transformers.modeling_tf_utils import TFPreTrainedModel ``` Signed-off-by: Kai Fricke <kai@anyscale.com> Signed-off-by: e428265 <arvind.chandramouli@lmco.com>
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Why are these changes needed?
Creating a
TransformersPredictorwith a custom pipeline class is currently broken: The model can't be automatically inferred from a path. This only works in the transformers pipeline. This PR adds support for this by adding additional parameters toTransformersPredictor.from_checkpoint()that will callTransformersCheckpoint.get_model()to retrieve the model, if specified.Related issue number
Solves https://discuss.ray.io/t/bug-in-ray-transformerpredictor-from-checkpoint/11033/2
Checks
git commit -s) in this PR.scripts/format.shto lint the changes in this PR.method in Tune, I've added it in
doc/source/tune/api/under thecorresponding
.rstfile.