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class CogVideo:
def __init__(self, device="cuda"):
"""
Initializes the CogVideo model with a specific device.
Args:
device (str, optional): The device to run the model on. Defaults to "cuda".
"""
import argparse
# Manually creating an args object
self.args = argparse.Namespace(
generate_frame_num=5,
coglm_temperature2=0.89,
use_guidance_stage1=True,
use_guidance_stage2=False, # Assuming this is not set
guidance_alpha=3.0,
stage_1=False, # Assuming this is not set
stage_2=False, # Assuming this is not set
both_stages=True,
parallel_size=1,
stage1_max_inference_batch_size=-1,
multi_gpu=False, # Assuming this is not set
device=3,
)
def infer_one_video(
self,
prompt: str = None,
size: list = [320, 512],
seconds: int = 2,
fps: int = 8,
seed: int = 42,
):
"""
Generates a single video based on the provided prompt and parameters.
Args:
prompt (str, optional): The text prompt to generate the video from. Defaults to None.
size (list, optional): The size of the video as [height, width]. Defaults to [320, 512].
seconds (int, optional): The duration of the video in seconds. Defaults to 2.
fps (int, optional): The frames per second of the video. Defaults to 8.
seed (int, optional): The seed for random number generation. Defaults to 42.
Returns:
torch.Tensor: The generated video as a tensor.
"""
from videogen_hub.pipelines.cogvideo.cogvideo_pipeline import pipeline
return pipeline(
self.args, raw_text=prompt, height=size[0], width=size[1], duration=seconds
)
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