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class LDMPipeline(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 504 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class LDMSuperResolutionPipeline(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 505 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class PNDMPipeline(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 506 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class RePaintPipeline(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 507 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class ScoreSdeVePipeline(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 508 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class StableDiffusionMixin(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 509 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class DiffusersQuantizer(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 510 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class AmusedScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 511 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class CMStochasticIterativeScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 512 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class CogVideoXDDIMScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 513 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class CogVideoXDPMScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 514 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class DDIMInverseScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 515 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class DDIMParallelScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 516 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class DDIMScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 517 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class DDPMParallelScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 518 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class DDPMScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 519 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class DDPMWuerstchenScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 520 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class DEISMultistepScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 521 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class DPMSolverMultistepInverseScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 522 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class DPMSolverMultistepScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 523 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class DPMSolverSinglestepScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 524 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class EDMDPMSolverMultistepScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 525 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class EDMEulerScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 526 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class EulerAncestralDiscreteScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 527 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class EulerDiscreteScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 528 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class FlowMatchEulerDiscreteScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 529 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class FlowMatchHeunDiscreteScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 530 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class HeunDiscreteScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 531 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class IPNDMScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 532 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class KarrasVeScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 533 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class KDPM2AncestralDiscreteScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 534 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class KDPM2DiscreteScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 535 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class LCMScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 536 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class PNDMScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 537 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class RePaintScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 538 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class SASolverScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 539 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class SchedulerMixin(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 540 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class ScoreSdeVeScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 541 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class TCDScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 542 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class UnCLIPScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 543 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class UniPCMultistepScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 544 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class VQDiffusionScheduler(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 545 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class EMAModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
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"]) | 546 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_pt_objects.py |
class CaptureLogger:
"""
Args:
Context manager to capture `logging` streams
logger: 'logging` logger object
Returns:
The captured output is available via `self.out`
Example:
```python
>>> from diffusers import logging
>>> from diffusers.testing_utils import CaptureLogger
>>> msg = "Testing 1, 2, 3"
>>> logging.set_verbosity_info()
>>> logger = logging.get_logger("diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.py")
>>> with CaptureLogger(logger) as cl:
... logger.info(msg)
>>> assert cl.out, msg + "\n"
```
"""
def __init__(self, logger):
self.logger = logger
self.io = StringIO()
self.sh = logging.StreamHandler(self.io)
self.out = ""
def __enter__(self):
self.logger.addHandler(self.sh)
return self
def __exit__(self, *exc):
self.logger.removeHandler(self.sh)
self.out = self.io.getvalue() | 547 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/testing_utils.py |
def __repr__(self):
return f"captured: {self.out}\n" | 547 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/testing_utils.py |
class StateDictType(enum.Enum):
"""
The mode to use when converting state dicts.
"""
DIFFUSERS_OLD = "diffusers_old"
KOHYA_SS = "kohya_ss"
PEFT = "peft"
DIFFUSERS = "diffusers" | 548 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/state_dict_utils.py |
class AllegroPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 549 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AltDiffusionImg2ImgPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 550 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AltDiffusionPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 551 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AmusedImg2ImgPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 552 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AmusedInpaintPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 553 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AmusedPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 554 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AnimateDiffControlNetPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 555 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AnimateDiffPAGPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 556 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AnimateDiffPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 557 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AnimateDiffSDXLPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 558 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AnimateDiffSparseControlNetPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 559 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AnimateDiffVideoToVideoControlNetPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 560 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AnimateDiffVideoToVideoPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 561 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AudioLDM2Pipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 562 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AudioLDM2ProjectionModel(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 563 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AudioLDM2UNet2DConditionModel(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 564 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AudioLDMPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 565 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class AuraFlowPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 566 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class CLIPImageProjection(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 567 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class CogVideoXFunControlPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 568 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class CogVideoXImageToVideoPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 569 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class CogVideoXPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 570 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class CogVideoXVideoToVideoPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 571 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class CogView3PlusPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 572 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class ConsisIDPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 573 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class CycleDiffusionPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 574 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class FluxControlImg2ImgPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 575 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class FluxControlInpaintPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 576 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class FluxControlNetImg2ImgPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 577 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class FluxControlNetInpaintPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 578 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class FluxControlNetPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 579 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class FluxControlPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 580 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class FluxFillPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 581 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class FluxImg2ImgPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 582 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class FluxInpaintPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 583 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class FluxPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 584 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class FluxPriorReduxPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 585 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class HunyuanDiTControlNetPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 586 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class HunyuanDiTPAGPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 587 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class HunyuanDiTPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 588 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class HunyuanVideoPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 589 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class I2VGenXLPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 590 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class IFImg2ImgPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 591 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class IFImg2ImgSuperResolutionPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 592 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class IFInpaintingPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 593 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class IFInpaintingSuperResolutionPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 594 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class IFPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 595 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class IFSuperResolutionPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 596 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class ImageTextPipelineOutput(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 597 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class Kandinsky3Img2ImgPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 598 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class Kandinsky3Pipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 599 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class KandinskyCombinedPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 600 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class KandinskyImg2ImgCombinedPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 601 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
class KandinskyImg2ImgPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers"]
def __init__(self, *args, **kwargs):
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"]) | 602 | /Users/nielsrogge/Documents/python_projecten/diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.py |
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