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[Tests] fix things after #7013 #7899

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Merged
merged 9 commits into from
May 9, 2024
Merged

[Tests] fix things after #7013 #7899

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f3806f8
debugging
sayakpaul May 9, 2024
11ac4ca
save the resulting image
sayakpaul May 9, 2024
1712260
check if order reversing works.
sayakpaul May 9, 2024
582fc94
checking values.
sayakpaul May 9, 2024
f8cdcc1
up
sayakpaul May 9, 2024
79641af
okay
sayakpaul May 9, 2024
5eb3974
checking
sayakpaul May 9, 2024
aeca046
fix
sayakpaul May 9, 2024
b96b591
remove print
sayakpaul May 9, 2024
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2 changes: 1 addition & 1 deletion src/diffusers/loaders/lora.py
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Expand Up @@ -1294,7 +1294,7 @@ def set_lora_device(self, adapter_names: List[str], device: Union[torch.device,
text_encoder_module.lora_B[adapter_name].to(device)
# this is a param, not a module, so device placement is not in-place -> re-assign
if (
hasattr(text_encoder, "lora_magnitude_vector")
hasattr(text_encoder_module, "lora_magnitude_vector")
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@BenjaminBossan FYI.

and text_encoder_module.lora_magnitude_vector is not None
):
text_encoder_module.lora_magnitude_vector[
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1 change: 1 addition & 0 deletions tests/lora/test_lora_layers_sd.py
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Expand Up @@ -196,6 +196,7 @@ def test_integration_move_lora_dora_cpu(self):

for name, param in pipe.text_encoder.named_parameters():
if "lora_" in name:
print(f"{name=}")
self.assertNotEqual(param.device, torch.device("cpu"))


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4 changes: 2 additions & 2 deletions tests/lora/test_lora_layers_sdxl.py
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Expand Up @@ -194,7 +194,7 @@ def test_sdxl_1_0_lora(self):
).images

images = images[0, -3:, -3:, -1].flatten()
expected = np.array([0.4468, 0.4087, 0.4134, 0.366, 0.3202, 0.3505, 0.3786, 0.387, 0.3535])
expected = np.array([0.4468, 0.4061, 0.4134, 0.3637, 0.3202, 0.365, 0.3786, 0.3725, 0.3535])

max_diff = numpy_cosine_similarity_distance(expected, images)
assert max_diff < 1e-4
Expand Down Expand Up @@ -283,7 +283,7 @@ def test_sdxl_1_0_lora_fusion(self):

images = images[0, -3:, -3:, -1].flatten()
# This way we also test equivalence between LoRA fusion and the non-fusion behaviour.
expected = np.array([0.4468, 0.4087, 0.4134, 0.366, 0.3202, 0.3505, 0.3786, 0.387, 0.3535])
expected = np.array([0.4468, 0.4061, 0.4134, 0.3637, 0.3202, 0.365, 0.3786, 0.3725, 0.3535])

max_diff = numpy_cosine_similarity_distance(expected, images)
assert max_diff < 1e-4
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