【复现】AnimateDiff ControlNet Pipeline复现过程记录

code：diffusers/examples/community at main · huggingface/diffusers · GitHub

似乎不用全下载，目前只用到了pipeline_animatediff_controlnet.py和anidi.py（readme中的AnimateDiff ControlNet Pipeline粘出来）

1.路径及文件问题

改为自己的绝对路径，custom_pipeline也要改，指向py文件

motion_id = "/data/diffusers-main/checkpoint/animatediff-motion-adapter-v1-5-2"
adapter = MotionAdapter.from_pretrained(motion_id)
controlnet = ControlNetModel.from_pretrained("/data/diffusers-main/checkpoint/control_v11p_sd15_openpose", torch_dtype=torch.float16)
vae = AutoencoderKL.from_pretrained("/data/diffusers-main/checkpoint/sd-vae-ft-mse", torch_dtype=torch.float16)
# 加载预训练的运动适配器、控制网络和自编码器模型

model_id = "/data/diffusers-main/checkpoint/Realistic_Vision_V5.1_noVAE"
pipe = DiffusionPipeline.from_pretrained(
    model_id,
    motion_adapter=adapter,
    controlnet=controlnet,
    vae=vae,
    # custom_pipeline="pipeline_animatediff_controlnet",
    custom_pipeline="/data/diffusers-main/examples/community/pipeline_animatediff_controlnet.py",
).to(device="cuda", dtype=torch.float16)
# 创建扩散管道并加载预训练的模型，包括运动适配器、控制网络和自编码器模型

 pipeline_animatediff_controlnet.py文件中的主类名要改成pipeline_animatediff_controlnet

同时在anidi.py中添加

from pipeline_animatediff_controlnet import pipeline_animatediff_controlnet

这样两个文件就连起来了。直接把custom_pipeline改成AnimateDiffControlNetPipeline应该也可以

2.找不到图片

 这是要自己把16帧条件输入视频处理成图像吗？

拆分工具：在线GIF图片帧拆分工具 - UU在线工具 (uutool.cn)

 ok了

3.torch.cuda.OutOfMemoryError

Traceback (most recent call last):
  File "/data/diffusers-main/examples/community/anidi.py", line 43, in 
    result = pipe(
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/root/.cache/huggingface/modules/diffusers_modules/local/pipeline_animatediff_controlnet.py", line 1079, in __call__
    down_block_res_samples, mid_block_res_sample = self.controlnet(
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/diffusers/models/controlnet.py", line 800, in forward
    sample, res_samples = downsample_block(
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/diffusers/models/unet_2d_blocks.py", line 1160, in forward
    hidden_states = attn(
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/diffusers/models/transformer_2d.py", line 392, in forward
    hidden_states = block(
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/diffusers/models/attention.py", line 288, in forward
    attn_output = self.attn1(
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/diffusers/models/attention_processor.py", line 522, in forward
    return self.processor(
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/diffusers/models/attention_processor.py", line 743, in __call__
    attention_probs = attn.get_attention_scores(query, key, attention_mask)
  File "/data/diffusers-main/.conda/lib/python3.10/site-packages/diffusers/models/attention_processor.py", line 590, in get_attention_scores
    baddbmm_input = torch.empty(
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 18.00 GiB (GPU 0; 11.91 GiB total capacity; 5.43 GiB already allocated; 4.75 GiB free; 6.38 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF

报错的位置：

        if attention_mask is None:
            baddbmm_input = torch.empty(
                query.shape[0], query.shape[1], key.shape[1], dtype=query.dtype, device=query.device
            )
            beta = 0
        else:
            baddbmm_input = attention_mask
            beta = 1

在计算注意力得分时，尝试分配显存空间时出错。显存要求18G。。要并行GPU才行

尝试1.

import os
os.environ['CUDA_VISIBLE_DEVICES']='0,1'
model_id = torch.nn.DataParallel(model_id, device_ids=[0, 1])

没用，还是显示只使用了GPU0

尝试2.调小参数，比如生成视频的大小/batchsize/num_inference_steps/guidance_scale

没用T T

尝试3.

最终发现，如果可以肯定没有别的问题，那一定是参数设置的还不够小

 

好了，主要影响显存的就是height和width，减半就行。上一次尝试没用的原因可能是有的地方的参数遗漏了，要保持所有地方同步

4.AttributeError: 'list' object has no attribute 'frames'

Traceback (most recent call last):
  File "/data/diffusers-main/examples/community/anidi.py", line 64, in 
    export_to_gif(result.frames[0], "result.gif")
AttributeError: 'list' object has no attribute 'frames'

位置：

 result 是一个列表对象而不是具有 frames 属性的对象。为了解决这个问题，您需要检查代码中生成 result 的部分，并确定为什么 result 变量是一个列表。

这段代码从 diffusers.utils 模块中导入了 export_to_gif 函数，并使用该函数将推理结果的第一个帧保存为 GIF 图像。通过访问 result.frames[0] 来获取结果的第一个帧数据。然后，export_to_gif 函数将该帧数据作为输入，将其保存为名为 "result.gif" 的 GIF 图像文件。

解决：去掉frame[0]

from diffusers.utils import export_to_gif
# export_to_gif(result.frames[0], "/data/diffusers-main/output/result.gif")
export_to_gif(result, "/data/diffusers-main/output/result.gif")

complete！

不过为啥出来的脸这么诡异，怪不得默认prompt是astronauts in the space，不用画脸。。