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Upgrade to torch 13 #175

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merged 4 commits into from
Feb 17, 2023
Merged

Upgrade to torch 13 #175

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e1a6d0a
upgrade to torch 13
mvpatel2000 Feb 16, 2023
5528c42
remove cd
mvpatel2000 Feb 16, 2023
73521f0
fix tests, force 113
mvpatel2000 Feb 17, 2023
0fe7159
Merge branch 'main' into mvpatel2000/up-113
mvpatel2000 Feb 17, 2023
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8 changes: 1 addition & 7 deletions examples/stable_diffusion/README.md
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Expand Up @@ -31,18 +31,12 @@ This folder contains starter code for finetuning Stable Diffusion. You can easil
## Clone the repo and install requirements

```bash
git clone https://github.com/mosaicml/examples.gitcd examples/
git clone https://github.com/mosaicml/examples.git
cd examples
pip install -e ".[stable-diffusion]"
cd examples/stable_diffusion
```
## Optionally, install xformers
xformers contains faster, more memory effecient transformer layers. But can take a while to install.

```
pip install ninja # Faster xformers install
pip install git+https://github.com/facebookresearch/xformers.git@3df785ce54114630155621e2be1c2fa5037efa27#egg=xformers
```
## Train the model
```
composer main.py yamls/finetune.yaml
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9 changes: 4 additions & 5 deletions examples/stable_diffusion/requirements.txt
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@@ -1,6 +1,6 @@
# --------- pytorch --------- #
torch>=1.12.0
torchvision>=0.11.0
torch>=1.13.0
torchvision>=0.12.0
mosaicml[all]>=0.12.1,<0.13

# --------- others --------- #
Expand All @@ -10,6 +10,5 @@ omegaconf
diffusers[torch]==0.11.1
transformers[torch]==4.25.1

# -------- optional -------- #
# ninja # Faster xformers install
# git+https://github.com/facebookresearch/xformers.git@3df785ce54114630155621e2be1c2fa5037efa27#egg=xformers #xformers
# -------- xformers -------- #
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xformers
2 changes: 1 addition & 1 deletion examples/stable_diffusion/tests/test_model.py
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Expand Up @@ -33,7 +33,7 @@ def build_dummy_stable_diffusion_model(model_name_or_path: str,
"""
unet = UNet2DConditionModel(**PretrainedConfig.get_config_dict(
model_name_or_path, subfolder='unet')[0])
if is_xformers_available():
if torch.cuda.is_available() and is_xformers_available():
unet.enable_xformers_memory_efficient_attention()
vae = AutoencoderKL(**PretrainedConfig.get_config_dict(model_name_or_path,
subfolder='vae')[0])
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2 changes: 1 addition & 1 deletion examples/stable_diffusion/yamls/mcloud_run.yaml
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Expand Up @@ -2,7 +2,7 @@ run_name: stable-diffusion-finetune
cluster: # Name of the cluster to use for this run
gpu_type: # Type of GPU to use
gpu_num: # Number of GPUs to use
image: mosaicml/pytorch:1.12.1_cu116-python3.9-ubuntu20.04
image: mosaicml/pytorch:1.13.1_cu117-python3.10-ubuntu20.04
integrations:
- integration_type: git_repo
git_repo: mosaicml/examples
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