[Dummy imports] Better error message (#795)

* [Dummy imports] Better error message

* Test: load pipeline with LMS scheduler.

Fails with a cryptic message if scipy is not installed.

* Correct

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
This commit is contained in:
Patrick von Platen 2022-10-12 14:41:16 +02:00 committed by GitHub
parent 966e2fc461
commit db47b1e4d9
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9 changed files with 323 additions and 1 deletions

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@ -49,6 +49,7 @@ if is_transformers_available():
INDEX_FILE = "diffusion_pytorch_model.bin" INDEX_FILE = "diffusion_pytorch_model.bin"
CUSTOM_PIPELINE_FILE_NAME = "pipeline.py" CUSTOM_PIPELINE_FILE_NAME = "pipeline.py"
DUMMY_MODULES_FOLDER = "diffusers.utils"
logger = logging.get_logger(__name__) logger = logging.get_logger(__name__)
@ -467,9 +468,20 @@ class DiffusionPipeline(ConfigMixin):
if issubclass(class_obj, class_candidate): if issubclass(class_obj, class_candidate):
load_method_name = importable_classes[class_name][1] load_method_name = importable_classes[class_name][1]
load_method = getattr(class_obj, load_method_name) if load_method_name is None:
none_module = class_obj.__module__
if none_module.startswith(DUMMY_MODULES_FOLDER) and "dummy" in none_module:
# call class_obj for nice error message of missing requirements
class_obj()
raise ValueError(
f"The component {class_obj} of {pipeline_class} cannot be loaded as it does not seem to have"
f" any of the loading methods defined in {ALL_IMPORTABLE_CLASSES}."
)
load_method = getattr(class_obj, load_method_name)
loading_kwargs = {} loading_kwargs = {}
if issubclass(class_obj, torch.nn.Module): if issubclass(class_obj, torch.nn.Module):
loading_kwargs["torch_dtype"] = torch_dtype loading_kwargs["torch_dtype"] = torch_dtype
if issubclass(class_obj, diffusers.OnnxRuntimeModel): if issubclass(class_obj, diffusers.OnnxRuntimeModel):

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@ -9,3 +9,11 @@ class FlaxStableDiffusionPipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["flax", "transformers"]) requires_backends(self, ["flax", "transformers"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["flax", "transformers"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["flax", "transformers"])

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@ -10,6 +10,14 @@ class FlaxModelMixin(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"]) requires_backends(self, ["flax"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
class FlaxUNet2DConditionModel(metaclass=DummyObject): class FlaxUNet2DConditionModel(metaclass=DummyObject):
_backends = ["flax"] _backends = ["flax"]
@ -17,6 +25,14 @@ class FlaxUNet2DConditionModel(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"]) requires_backends(self, ["flax"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
class FlaxAutoencoderKL(metaclass=DummyObject): class FlaxAutoencoderKL(metaclass=DummyObject):
_backends = ["flax"] _backends = ["flax"]
@ -24,6 +40,14 @@ class FlaxAutoencoderKL(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"]) requires_backends(self, ["flax"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
class FlaxDiffusionPipeline(metaclass=DummyObject): class FlaxDiffusionPipeline(metaclass=DummyObject):
_backends = ["flax"] _backends = ["flax"]
@ -31,6 +55,14 @@ class FlaxDiffusionPipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"]) requires_backends(self, ["flax"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
class FlaxDDIMScheduler(metaclass=DummyObject): class FlaxDDIMScheduler(metaclass=DummyObject):
_backends = ["flax"] _backends = ["flax"]
@ -38,6 +70,14 @@ class FlaxDDIMScheduler(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"]) requires_backends(self, ["flax"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
class FlaxDDPMScheduler(metaclass=DummyObject): class FlaxDDPMScheduler(metaclass=DummyObject):
_backends = ["flax"] _backends = ["flax"]
@ -45,6 +85,14 @@ class FlaxDDPMScheduler(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"]) requires_backends(self, ["flax"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
class FlaxKarrasVeScheduler(metaclass=DummyObject): class FlaxKarrasVeScheduler(metaclass=DummyObject):
_backends = ["flax"] _backends = ["flax"]
@ -52,6 +100,14 @@ class FlaxKarrasVeScheduler(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"]) requires_backends(self, ["flax"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
class FlaxLMSDiscreteScheduler(metaclass=DummyObject): class FlaxLMSDiscreteScheduler(metaclass=DummyObject):
_backends = ["flax"] _backends = ["flax"]
@ -59,6 +115,14 @@ class FlaxLMSDiscreteScheduler(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"]) requires_backends(self, ["flax"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
class FlaxPNDMScheduler(metaclass=DummyObject): class FlaxPNDMScheduler(metaclass=DummyObject):
_backends = ["flax"] _backends = ["flax"]
@ -66,6 +130,14 @@ class FlaxPNDMScheduler(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"]) requires_backends(self, ["flax"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
class FlaxSchedulerMixin(metaclass=DummyObject): class FlaxSchedulerMixin(metaclass=DummyObject):
_backends = ["flax"] _backends = ["flax"]
@ -73,9 +145,25 @@ class FlaxSchedulerMixin(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"]) requires_backends(self, ["flax"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
class FlaxScoreSdeVeScheduler(metaclass=DummyObject): class FlaxScoreSdeVeScheduler(metaclass=DummyObject):
_backends = ["flax"] _backends = ["flax"]
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["flax"]) requires_backends(self, ["flax"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["flax"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["flax"])

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@ -10,6 +10,14 @@ class ModelMixin(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class AutoencoderKL(metaclass=DummyObject): class AutoencoderKL(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -17,6 +25,14 @@ class AutoencoderKL(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class UNet2DConditionModel(metaclass=DummyObject): class UNet2DConditionModel(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -24,6 +40,14 @@ class UNet2DConditionModel(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class UNet2DModel(metaclass=DummyObject): class UNet2DModel(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -31,6 +55,14 @@ class UNet2DModel(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class VQModel(metaclass=DummyObject): class VQModel(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -38,6 +70,14 @@ class VQModel(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
def get_constant_schedule(*args, **kwargs): def get_constant_schedule(*args, **kwargs):
requires_backends(get_constant_schedule, ["torch"]) requires_backends(get_constant_schedule, ["torch"])
@ -73,6 +113,14 @@ class DiffusionPipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class DDIMPipeline(metaclass=DummyObject): class DDIMPipeline(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -80,6 +128,14 @@ class DDIMPipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class DDPMPipeline(metaclass=DummyObject): class DDPMPipeline(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -87,6 +143,14 @@ class DDPMPipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class KarrasVePipeline(metaclass=DummyObject): class KarrasVePipeline(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -94,6 +158,14 @@ class KarrasVePipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class LDMPipeline(metaclass=DummyObject): class LDMPipeline(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -101,6 +173,14 @@ class LDMPipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class PNDMPipeline(metaclass=DummyObject): class PNDMPipeline(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -108,6 +188,14 @@ class PNDMPipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class ScoreSdeVePipeline(metaclass=DummyObject): class ScoreSdeVePipeline(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -115,6 +203,14 @@ class ScoreSdeVePipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class DDIMScheduler(metaclass=DummyObject): class DDIMScheduler(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -122,6 +218,14 @@ class DDIMScheduler(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class DDPMScheduler(metaclass=DummyObject): class DDPMScheduler(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -129,6 +233,14 @@ class DDPMScheduler(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class KarrasVeScheduler(metaclass=DummyObject): class KarrasVeScheduler(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -136,6 +248,14 @@ class KarrasVeScheduler(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class PNDMScheduler(metaclass=DummyObject): class PNDMScheduler(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -143,6 +263,14 @@ class PNDMScheduler(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class SchedulerMixin(metaclass=DummyObject): class SchedulerMixin(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -150,6 +278,14 @@ class SchedulerMixin(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class ScoreSdeVeScheduler(metaclass=DummyObject): class ScoreSdeVeScheduler(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
@ -157,9 +293,25 @@ class ScoreSdeVeScheduler(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
class EMAModel(metaclass=DummyObject): class EMAModel(metaclass=DummyObject):
_backends = ["torch"] _backends = ["torch"]
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"]) requires_backends(self, ["torch"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch"])

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@ -9,3 +9,11 @@ class LMSDiscreteScheduler(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch", "scipy"]) requires_backends(self, ["torch", "scipy"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch", "scipy"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch", "scipy"])

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@ -9,3 +9,11 @@ class StableDiffusionOnnxPipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch", "transformers", "onnx"]) requires_backends(self, ["torch", "transformers", "onnx"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch", "transformers", "onnx"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch", "transformers", "onnx"])

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@ -10,6 +10,14 @@ class LDMTextToImagePipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch", "transformers"]) requires_backends(self, ["torch", "transformers"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch", "transformers"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch", "transformers"])
class StableDiffusionImg2ImgPipeline(metaclass=DummyObject): class StableDiffusionImg2ImgPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"] _backends = ["torch", "transformers"]
@ -17,6 +25,14 @@ class StableDiffusionImg2ImgPipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch", "transformers"]) requires_backends(self, ["torch", "transformers"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch", "transformers"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch", "transformers"])
class StableDiffusionInpaintPipeline(metaclass=DummyObject): class StableDiffusionInpaintPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"] _backends = ["torch", "transformers"]
@ -24,9 +40,25 @@ class StableDiffusionInpaintPipeline(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch", "transformers"]) requires_backends(self, ["torch", "transformers"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch", "transformers"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch", "transformers"])
class StableDiffusionPipeline(metaclass=DummyObject): class StableDiffusionPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"] _backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, ["torch", "transformers"]) requires_backends(self, ["torch", "transformers"])
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, ["torch", "transformers"])
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, ["torch", "transformers"])

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@ -492,6 +492,12 @@ class PipelineFastTests(unittest.TestCase):
assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2 assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
assert np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2 assert np.abs(image_from_tuple_slice.flatten() - expected_slice).max() < 1e-2
def test_from_pretrained_error_message_uninstalled_packages(self):
# TODO(Patrick, Pedro) - need better test here for the future
pipe = StableDiffusionPipeline.from_pretrained("hf-internal-testing/tiny-stable-diffusion-lms-pipe")
assert isinstance(pipe, StableDiffusionPipeline)
assert isinstance(pipe.scheduler, LMSDiscreteScheduler)
def test_stable_diffusion_k_lms(self): def test_stable_diffusion_k_lms(self):
device = "cpu" # ensure determinism for the device-dependent torch.Generator device = "cpu" # ensure determinism for the device-dependent torch.Generator
unet = self.dummy_cond_unet unet = self.dummy_cond_unet

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@ -38,6 +38,14 @@ class {0}(metaclass=DummyObject):
def __init__(self, *args, **kwargs): def __init__(self, *args, **kwargs):
requires_backends(self, {1}) requires_backends(self, {1})
@classmethod
def from_config(cls, *args, **kwargs):
requires_backends(cls, {1})
@classmethod
def from_pretrained(cls, *args, **kwargs):
requires_backends(cls, {1})
""" """