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Merge remote-tracking branch 'origin' into fix/prefer_llm_checker

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suluyan.sly@alibaba-inc.com
2024-12-09 14:27:48 +08:00
parent 1d60f92a2e d2ef1003ea
commit 47bb7c45c5
2 changed files with 8 additions and 6 deletions
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4
modelscope/pipelines/multi_modal/efficient_diffusion_tuning_pipeline.py
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@@ -36,8 +36,10 @@ class EfficientDiffusionTuningPipeline(Pipeline):
'data/test/images/vision_efficient_tuning_test_1.png')
>>> print(f'Output: {result}.')
"""
logger.warn(
'[NOTE]Do not use this pipeline because the dependencies are too old, '
'use https://github.com/modelscope/DiffSynth-Studio instead')
super().__init__(model=model, **kwargs)
self.device = 'cuda' if torch.cuda.is_available() else 'cpu'
self.model = self.model.to(self.device)
self.model.eval()

10
tests/pipelines/test_efficient_diffusion_tuning.py
View File

@@ -11,10 +11,10 @@ from modelscope.utils.test_utils import test_level
class EfficientDiffusionTuningTest(unittest.TestCase):
def setUp(self) -> None:
os.system('pip install ms-swift -U')
# os.system('pip install ms-swift -U')
self.task = Tasks.efficient_diffusion_tuning
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
@unittest.skip
def test_efficient_diffusion_tuning_lora_run_pipeline(self):
model_id = 'damo/multi-modal_efficient-diffusion-tuning-lora'
model_revision = 'v1.0.2'
@@ -24,7 +24,7 @@ class EfficientDiffusionTuningTest(unittest.TestCase):
result = edt_pipeline(inputs)
print(f'Efficient-diffusion-tuning-lora output: {result}.')
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
@unittest.skip
def test_efficient_diffusion_tuning_lora_load_model_from_pretrained(self):
model_id = 'damo/multi-modal_efficient-diffusion-tuning-lora'
model_revision = 'v1.0.2'
@@ -32,7 +32,7 @@ class EfficientDiffusionTuningTest(unittest.TestCase):
from modelscope.models.multi_modal import EfficientStableDiffusion
self.assertTrue(model.__class__ == EfficientStableDiffusion)
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
@unittest.skip
def test_efficient_diffusion_tuning_control_lora_run_pipeline(self):
# TODO: to be fixed in the future
model_id = 'damo/multi-modal_efficient-diffusion-tuning-control-lora'
@@ -48,7 +48,7 @@ class EfficientDiffusionTuningTest(unittest.TestCase):
result = edt_pipeline(inputs)
print(f'Efficient-diffusion-tuning-control-lora output: {result}.')
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
@unittest.skip
def test_efficient_diffusion_tuning_control_lora_load_model_from_pretrained(
self):
model_id = 'damo/multi-modal_efficient-diffusion-tuning-control-lora'