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from abc import abstractmethod | |
from dataclasses import dataclass | |
import torch | |
from diffusers.pipelines.pipeline_utils import DiffusionPipeline | |
from diffusers.utils import BaseOutput | |
class VideoSysPipeline(DiffusionPipeline): | |
def __init__(self): | |
super().__init__() | |
def set_eval_and_device(device: torch.device, *modules): | |
for module in modules: | |
module.eval() | |
module.to(device) | |
def generate(self, *args, **kwargs): | |
pass | |
def __call__(self, *args, **kwargs): | |
""" | |
In diffusers, it is a convention to call the pipeline object. | |
But in VideoSys, we will use the generate method for better prompt. | |
This is a wrapper for the generate method to support the diffusers usage. | |
""" | |
return self.generate(*args, **kwargs) | |
class VideoSysPipelineOutput(BaseOutput): | |
video: torch.Tensor | |