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fix: Don't require efficiency_config for torchtune (#2104)

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# What does this PR do?

Revert a change that by mistake forced efficiency_config on torchtune
provider
users.

```
    fix: Don't require efficiency_config for torchtune

    It was enforced by mistake when
    0751a960a5 merged.

    Other asserts made sense in that the code was written, potentially, to
    always expect a non-None value. But not efficiency_config.
```

Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
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Ihar Hrachyshka 2025-05-06 12:50:44 -04:00 • committed by GitHub
parent 7377a5c83e
commit c219a74fa0
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3
llama_stack/providers/inline/post_training/torchtune/recipes/lora_finetuning_single_device.py
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@ -39,7 +39,6 @@ from llama_stack.apis.datasets import Datasets
from llama_stack.apis.post_training import (
Checkpoint,
DataConfig,
EfficiencyConfig,
LoraFinetuningConfig,
OptimizerConfig,
QATFinetuningConfig,
@ -90,8 +89,6 @@ class LoraFinetuningSingleDevice:
) -> None:
assert isinstance(training_config.data_config, DataConfig), "DataConfig must be initialized"
assert isinstance(training_config.efficiency_config, EfficiencyConfig), "EfficiencyConfig must be initialized"
self.job_uuid = job_uuid
self.training_config = training_config
if not isinstance(algorithm_config, LoraFinetuningConfig):