FROM nvcr.io/nvidia/cuda:11.7.1-cudnn8-runtime-ubuntu20.04

ARG DEBIAN_FRONTEND=noninteractive
ENV TZ=Asia/Tokyo

RUN apt-get update && apt-get install -y wget git git-lfs libglib2.0-0 libsm6 libxrender1 libxext-dev

RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
    sh Miniconda3-latest-Linux-x86_64.sh -b -p /opt/miniconda3 && \
    rm -r Miniconda3-latest-Linux-x86_64.sh

ENV PATH /opt/miniconda3/bin:$PATH

RUN git clone https://github.com/CompVis/stable-diffusion && \
    cd stable-diffusion && \
    conda init bash && \
    conda env create -f environment.yaml && \
    echo "conda activate ldm" >> ~/.bashrc

// 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"
}

(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
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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/stable-diffusion# nvidia-smi
Tue Sep  6 14:52:34 2022       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 515.65.01    Driver Version: 516.94       CUDA Version: 11.7     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA GeForce ...  On   | 00000000:01:00.0 Off |                  N/A |
| N/A   56C    P3    13W /  N/A |      0MiB /  4096MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

(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

(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'

(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'

(ldm) root@21feb17171f4:/workspaces/StableDiffusion2/basujindal/stable-diffusion# conda deactivate       
(base) root@21feb17171f4:/workspaces/StableDiffusion2/basujindal/stable-diffusion# conda remove -n ldm --all
(base) root@21feb17171f4:/workspaces/StableDiffusion2/basujindal/stable-diffusion# conda env create -f environment.yaml 
(base) root@21feb17171f4:/workspaces/StableDiffusion2/basujindal/stable-diffusion# conda activate ldm

(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
UNet: Running in eps-prediction mode
CondStage: Running in eps-prediction mode
Downloading: "https://github.com/DagnyT/hardnet/raw/master/pretrained/train_liberty_with_aug/checkpoint_liberty_with_aug.pth" to /root/.cache/torch/hub/checkpoints/checkpoint_liberty_with_aug.pth
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Killed

[wsl2]
memory=12GB

(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
UNet: Running in eps-prediction mode
CondStage: Running in eps-prediction mode
FirstStage: Running in eps-prediction mode
making attention of type 'vanilla' with 512 in_channels
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
making attention of type 'vanilla' with 512 in_channels
Sampling:   0%|                                                                                                                             | 0/2 [00:00<?, ?it/sseeds used =  [27, 28, 29, 30, 31, 32, 33, 34, 35, 36]                                                                                       | 0/1 [00:00<?, ?it/s]
Data shape for PLMS sampling is [10, 4, 64, 64]
Running PLMS Sampling with 50 timesteps
PLMS Sampler: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [06:46<00:00,  8.13s/it]
torch.Size([10, 4, 64, 64])
saving images 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [06:46<00:00,  8.38s/it]
memory_final =  7.72352
data: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [07:04<00:00, 424.21s/it]
Sampling:  50%|██████████████████████████████████████████████████████████                                                          | 1/2 [07:04<07:04, 424.21s/itseeds used =  [37, 38, 39, 40, 41, 42, 43, 44, 45, 46]                                                                                       | 0/1 [00:00<?, ?it/s]
Data shape for PLMS sampling is [10, 4, 64, 64]
Running PLMS Sampling with 50 timesteps
PLMS Sampler: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [07:19<00:00,  8.79s/it]
torch.Size([10, 4, 64, 64])
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memory_final =  6.833664
data: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [07:27<00:00, 447.21s/it]
Sampling: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [14:31<00:00, 435.71s/it]
Samples finished in 15.12 minutes and exported to outputs/txt2img-samples/a_photograph_of_an_astronaut_riding_a_horse
 Seeds used = 27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46