google colab の実行が止まってしまいます。^Cとは何でしょうか?

###質問の内容
stable diffusion 2.0が出たとのことで、実際にgoogle colabで動かしてみようと思ったのですが、^Cと表示され実行が止まってしまいます。以前stable diffusion 1.0を動かした際には問題なく使えいました。git hubのコードを確認したところ大きく変わったところは見当たらず容量の問題かと思い調べたところ解決するような記事がなかったため、詳しい皆様のお力をお借りしたいです。

実現したいこと

stable diffusion2.0の text2image、inpaintingを実装したい。

実行結果

Global seed set to 42
Loading model from /content/drive/MyDrive/ckpt_stab/sd-v1-4.ckpt
Global Step: 470000
/usr/local/lib/python3.8/dist-packages/xformers/_C.so: undefined symbol: _ZNK3c104impl13OperatorEntry20reportSignatureErrorENS0_12CppSignatureE
WARNING:root:WARNING: /usr/local/lib/python3.8/dist-packages/xformers/_C.so: undefined symbol: _ZNK3c104impl13OperatorEntry20reportSignatureErrorENS0_12CppSignatureE
Need to compile C++ extensions to get sparse attention suport. Please run python setup.py build develop
WARNING:root:A matching Triton is not available, some optimizations will not be enabled.
Error caught was: module 'triton.language' has no attribute 'constexpr'
/usr/local/lib/python3.8/dist-packages/pytorch_lightning/utilities/distributed.py:258: LightningDeprecationWarning: `pytorch_lightning.utilities.distributed.rank_zero_only` has been deprecated in v1.8.1 and will be removed in v1.10.0. You can import it from `pytorch_lightning.utilities` instead.
  rank_zero_deprecation(
LatentDiffusion: Running in eps-prediction mode
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is None and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 1280, context_dim is 1024 and using 20 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is None and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 640, context_dim is 1024 and using 10 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is None and using 5 heads.
Setting up MemoryEfficientCrossAttention. Query dim is 320, context_dim is 1024 and using 5 heads.
DiffusionWrapper has 865.91 M params.
making attention of type 'vanilla-xformers' with 512 in_channels
building MemoryEfficientAttnBlock with 512 in_channels...
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla-xformers' with 512 in_channels
building MemoryEfficientAttnBlock with 512 in_channels...
^C

該当のソースコード

Python
1ソースコード
2!python scripts/txt2img.py --prompt "illustration of a dog sitting in front of a big tree" --plms --ckpt /content/drive/MyDrive/ckpt_stab/sd-v1-4.ckpt --n_samples 1

試したこと

実行するPythonファイルの中身を確認した。
^Cという実行結果について調べたが記載されている物が見つからなかった。

補足情報（FW/ツールのバージョンなど）

ソースコードや実行結果も貼らさせていただきましたが、^Cで実行が終わる理由と原因を主に教えていただきたいです。よろしくお願いします。

meg_

2022/12/18 11:31

第三者が検証可能な手順を提示いただけないでしょうか？また実行環境の詳細も教えてください。

MARU

2022/12/18 16:11

大変失礼いたしました。 !pip install albumentations==0.4.3 !pip install diffusers !pip install opencv-python==4.1.2.30 !pip install pudb==2019.2 !pip install imageio==2.9.0 !pip install imageio-ffmpeg==0.4.2 !pip install pytorch-lightning !pip install omegaconf==2.1.1 !pip install test-tube>=0.7.5 !pip install streamlit>=0.73.1 !pip install einops==0.3.0 !pip install torch-fidelity==0.3.0 !pip install transformers==4.19.2 !pip install kornia !pip install xformers !pip install triton !pip install -e git+https://github.com/CompVis/taming-transformers.git@master#egg=taming-transformers !pip install -e git+https://github.com/openai/CLIP.git@main#egg=clip !pip install invisible-watermark !git clone https://github.com/mlfoundations/open_clip #stable diffusion 2.0 !git clone https://github.com/Stability-AI/stablediffusion %cd stablediffusion !pip install -e . これらをインストールした上で、open_clipの中の src/open_clip をstablediffusionファイルの中に移動し、stablediffusion/scripts/text2img.pyを実行した結果このような表示になりました。古いバージョンとなる　https://github.com/CompVis/stable-diffusion/tree/21f890f9da3cfbeaba8e2ac3c425ee9e998d5229 　のモデルではこのコードで動作確認できていたのですが、今回の実行結果はエラーで止まるわけではなく中断され、この表示が私には初めてだったため質問させていただきました。また、ドライブのマウントとGPUで行っています。

MARU

2022/12/18 16:54

また、リソースを確認したところ、システムRAMの部分が実行の際に一気に跳ね上がり停止するのですが、そこが原因ということなのでしょうか。