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VSCode のコマンドパレットから「Remote-Containers: Add Development Container Configuration Files…」を選択し、作成したDockerfileを指定します。
devcontainer.jsonが作成されるので、編集します
// For format details, see https://aka.ms/devcontainer.json. For config options, see the README at:
// https://github.com/microsoft/vscode-dev-containers/tree/v0.245.0/containers/docker-existing-dockerfile
{
"name": "Existing Dockerfile",
// Sets the run context to one level up instead of the .devcontainer folder.
"context": "..",
// Update the 'dockerFile' property if you aren't using the standard 'Dockerfile' filename.
"dockerFile": "../Dockerfile",
// 追記ここから。GPU利用可のコンテナ起動オプション
"runArgs":[
"--gpus",
"all"
],
// 追記ここまで。
"customizations": {
"vscode": {
"extensions": [
"ms-python.python"
]
}
}
// Use 'forwardPorts' to make a list of ports inside the container available locally.
// "forwardPorts": [],
// Uncomment the next line to run commands after the container is created - for example installing curl.
// "postCreateCommand": "apt-get update && apt-get install -y curl",
// Uncomment when using a ptrace-based debugger like C++, Go, and Rust
// "runArgs": [ "--cap-add=SYS_PTRACE", "--security-opt", "seccomp=unconfined" ],
// Uncomment to use the Docker CLI from inside the container. See https://aka.ms/vscode-remote/samples/docker-from-docker.
// "mounts": [ "source=/var/run/docker.sock,target=/var/run/docker.sock,type=bind" ],
// Uncomment to connect as a non-root user if you've added one. See https://aka.ms/vscode-remote/containers/non-root.
// "remoteUser": "vscode"
}
コマンドパレットから「Remote-Containers: Rebuild and Reopen in Container」を選択することで、コンテナ内でVSCodeが起動する形となります。 VSCode の左下がこの状態ですね
Modelの配置
前回取得した Hugging Face のモデルを、Stable Diffusionがモデルのデフォルトパスとして指定している”models/ldm/stable-diffusion-v1/model.ckpt”に配備します。 このあたりは、”txt2image.py”を読んでいくとなんのパラメータ指定が出来るのかがわ借ります。 別のパスを指定する場合は —ckpt オプションで指定可能となっています
実行！
参考にさせていただいたページに従って、test.pyを用意し、実行します
(ldm) root@21feb17171f4:/workspaces/StableDiffusion2/stable-diffusion# python test.py
Traceback (most recent call last):
File "test.py", line 6, in <module>
pipe = StableDiffusionPipeline.from_pretrained(
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/diffusers/pipeline_utils.py", line 154, in from_pretrained
cached_folder = snapshot_download(
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/huggingface_hub/utils/_deprecation.py", line 93, in inner_f
return f(*args, **kwargs)
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/huggingface_hub/_snapshot_download.py", line 168, in snapshot_download
repo_info = _api.repo_info(
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/huggingface_hub/hf_api.py", line 1454, in repo_info
return self.model_info(
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/huggingface_hub/hf_api.py", line 1276, in model_info
_raise_for_status(r)
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/huggingface_hub/utils/_errors.py", line 169, in _raise_for_status
raise e
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/huggingface_hub/utils/_errors.py", line 131, in _raise_for_status
response.raise_for_status()
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/requests/models.py", line 1021, in raise_for_status
raise HTTPError(http_error_msg, response=self)
requests.exceptions.HTTPError: 403 Client Error: Forbidden for url: https://huggingface.co/api/models/CompVis/stable-diffusion-v1-4/revision/fp16 (Request ID: PQ6M8N2Lators-j6XdN6V)
Access to model CompVis/stable-diffusion-v1-4 is restricted and you are not in the authorized list. Visit https://huggingface.co/CompVis/stable-diffusion-v1-4 to ask for access.
(ldm) root@21feb17171f4:/workspaces/StableDiffusion2/stable-diffusion# python test.py
Downloading: 100%|████████████████████████████████████████████████████| 1.34k/1.34k [00:00<00:00, 1.13MB/s]
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0it [00:01, ?it/s]
Traceback (most recent call last):
File "test.py", line 15, in <module>
image = pipe(prompt)["sample"][0]
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py", line 137, in __call__
noise_pred = self.unet(latent_model_input, t, encoder_hidden_states=text_embeddings)["sample"]
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/diffusers/models/unet_2d_condition.py", line 150, in forward
sample, res_samples = downsample_block(
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/diffusers/models/unet_blocks.py", line 505, in forward
hidden_states = attn(hidden_states, context=encoder_hidden_states)
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/diffusers/models/attention.py", line 168, in forward
x = block(x, context=context)
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/diffusers/models/attention.py", line 196, in forward
x = self.attn1(self.norm1(x)) + x
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/diffusers/models/attention.py", line 245, in forward
sim = torch.einsum("b i d, b j d -> b i j", q, k) * self.scale
RuntimeError: CUDA out of memory. Tried to allocate 512.00 MiB (GPU 0; 4.00 GiB total capacity; 3.13 GiB already allocated; 0 bytes free; 3.13 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
(ldm) root@21feb17171f4:/workspaces/StableDiffusion2# mkdir basujindal
(ldm) root@21feb17171f4:/workspaces/StableDiffusion2# ls
Dockerfile basujindal stable-diffusion
(ldm) root@21feb17171f4:/workspaces/StableDiffusion2# cd basujindal/
(ldm) root@21feb17171f4:/workspaces/StableDiffusion2/basujindal# git clone https://github.com/basujindal/stable-diffusion.git
適当なフォルダを作って、リポジトリからclone
(ldm) root@21feb17171f4:/workspaces/StableDiffusion2/basujindal# cd stable-diffusion/
(ldm) root@21feb17171f4:/workspaces/StableDiffusion2/basujindal/stable-diffusion# python optimizedSD/optimized_txt2img.py --prompt "a photograph of an astronaut riding a horse" --H 512 --W 512 --seed 27 --n_iter 2 --n_samples 10 --ddim_steps 50
Global seed set to 27
Loading model from models/ldm/stable-diffusion-v1/model.ckpt
Traceback (most recent call last):
File "optimizedSD/optimized_txt2img.py", line 184, in <module>
sd = load_model_from_config(f"{ckpt}")
File "optimizedSD/optimized_txt2img.py", line 29, in load_model_from_config
pl_sd = torch.load(ckpt, map_location="cpu")
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/torch/serialization.py", line 699, in load
with _open_file_like(f, 'rb') as opened_file:
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/torch/serialization.py", line 231, in _open_file_like
return _open_file(name_or_buffer, mode)
File "/opt/miniconda3/envs/ldm/lib/python3.8/site-packages/torch/serialization.py", line 212, in __init__
super(_open_file, self).__init__(open(name, mode))
FileNotFoundError: [Errno 2] No such file or directory: 'models/ldm/stable-diffusion-v1/model.ckpt'
おっと、モデルを新たに置き直さないと行けない。 サクッとコピーして、再度実行する
(ldm) root@21feb17171f4:/workspaces/StableDiffusion2/basujindal/stable-diffusion# python optimizedSD/optimized_txt2img.py --prompt "a photograph of an astronaut riding a horse" --H 512 --W 512 --seed 27 --n_iter 2 --n_samples 10 --ddim_steps 50
Global seed set to 27
Loading model from models/ldm/stable-diffusion-v1/model.ckpt
Global Step: 470000
Traceback (most recent call last):
File "optimizedSD/optimized_txt2img.py", line 204, in <module>
model = instantiate_from_config(config.modelUNet)
File "/stable-diffusion/ldm/util.py", line 85, in instantiate_from_config
return get_obj_from_str(config["target"])(**config.get("params", dict()))
File "/stable-diffusion/ldm/util.py", line 93, in get_obj_from_str
return getattr(importlib.import_module(module, package=None), cls)
File "/opt/miniconda3/envs/ldm/lib/python3.8/importlib/__init__.py", line 127, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "<frozen importlib._bootstrap>", line 1014, in _gcd_import
File "<frozen importlib._bootstrap>", line 991, in _find_and_load
File "<frozen importlib._bootstrap>", line 961, in _find_and_load_unlocked
File "<frozen importlib._bootstrap>", line 219, in _call_with_frames_removed
File "<frozen importlib._bootstrap>", line 1014, in _gcd_import
File "<frozen importlib._bootstrap>", line 991, in _find_and_load
File "<frozen importlib._bootstrap>", line 973, in _find_and_load_unlocked
ModuleNotFoundError: No module named 'optimizedSD'
