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FIX: Adalora ranknum loaded on wrong device #1852

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merged 2 commits into from
Jun 13, 2024
Merged

FIX: Adalora ranknum loaded on wrong device #1852

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8ed5eae
FIX Set correct device for AdaLoRA
BenjaminBossan Jun 12, 2024
0db737e
Undo unnecessary change
BenjaminBossan Jun 12, 2024
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3 changes: 2 additions & 1 deletion src/peft/tuners/adalora/layer.py
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Expand Up @@ -35,7 +35,8 @@ class AdaLoraLayer(LoraLayer):
# List all names of layers that may contain adapter weights
# Note: ranknum doesn't need to be included as it is not an nn.Module
adapter_layer_names = ("lora_A", "lora_B", "lora_E", "lora_embedding_A", "lora_embedding_B")
# other_param_names is defined in LoraLayer
# All names of other parameters that may contain adapter-related parameters
other_param_names = ("r", "lora_alpha", "scaling", "lora_dropout", "ranknum")

def __init__(self, base_layer: nn.Module) -> None:
super().__init__(base_layer)
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1 change: 1 addition & 0 deletions tests/test_common_gpu.py
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Expand Up @@ -1085,6 +1085,7 @@ def test_8bit_dora_merging(self):


@pytest.mark.skipif(not torch.cuda.is_available(), reason="test requires a CUDA GPU")
@pytest.mark.single_gpu_tests
class TestSameAdapterDifferentDevices:
# 1639
# The original issue comes down to the following problem: If the user has a base layer on CUDA, moves the adapter to
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