Spaces:
Running
Running
Merge pull request #74 from borisdayma/feat-setup
Browse files- README.md +0 -2
- app/app.py +0 -1
- app/dalle_mini +0 -1
- app/gradio/dalle_mini +0 -1
- dev/README.md +122 -0
- dev/inference/dalle_mini +0 -1
- requirements.txt +0 -2
- setup.cfg +16 -0
- setup.py +4 -0
README.md
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@@ -26,8 +26,6 @@ Refer to [our report](https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini
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### Dependencies Installation
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The root folder and associated [`requirements.txt`](./requirements.txt) is only for the app.
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For development, use [`dev/requirements.txt`](dev/requirements.txt) or [`dev/environment.yaml`](dev/environment.yaml).
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### Training of VQGAN
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### Dependencies Installation
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For development, use [`dev/requirements.txt`](dev/requirements.txt) or [`dev/environment.yaml`](dev/environment.yaml).
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### Training of VQGAN
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app/app.py
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#!/usr/bin/env python
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# coding: utf-8
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import random
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from dalle_mini.backend import ServiceError, get_images_from_backend
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import streamlit as st
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#!/usr/bin/env python
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# coding: utf-8
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from dalle_mini.backend import ServiceError, get_images_from_backend
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import streamlit as st
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app/dalle_mini
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../dalle_mini/
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app/gradio/dalle_mini
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../../dalle_mini/
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dev/README.md
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# Development Instructions for TPU
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## Setup
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- Apply to the [TRC program](https://sites.research.google/trc/) for free TPU credits if you're elligible.
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- Follow the [Cloud TPU VM User's Guide](https://cloud.google.com/tpu/docs/users-guide-tpu-vm) to set up gcloud.
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- Verify `gcloud config list`, in particular account, project & zone.
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- Create a TPU VM per the guide and connect to it.
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When needing a larger disk:
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- Create a balanced persistent disk (SSD, so pricier than default HDD but much faster): `gcloud compute disks create DISK_NAME --size SIZE_IN_GB --type pd-balanced`
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- Attach the disk to your instance by adding `--data-disk source=REF` per ["Adding a persistent disk to a TPU VM" guide](https://cloud.google.com/tpu/docs/setup-persistent-disk), eg `gcloud alpha compute tpus tpu-vm create INSTANCE_NAME --accelerator-type=v3-8 --version=v2-alpha --data-disk source=projects/tpu-toys/zones/europe-west4-a/disks/DISK_NAME`
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- Format the partition as described in the guide.
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- Make sure to set up automatic remount of disk at restart.
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## Connect VS Code
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- Find external IP in the UI or with `gcloud alpha compute tpus tpu-vm describe INSTANCE_NAME`
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- Verify you can connect in terminal with `ssh EXTERNAL_IP -i ~/.ssh/google_compute_engine`
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- Add the same command as ssh host in VS Code.
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- Check config file
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```
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Host INSTANCE_NAME
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HostName EXTERNAL_IP
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IdentityFile ~/.ssh/google_compute_engine
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```
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## Environment configuration
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### Use virtual environments (optional)
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We recommend using virtual environments (such as conda, venv or pyenv-virtualenv).
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If you want to use `pyenv` and `pyenv-virtualenv`:
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- Installation
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- [Set up build environment](https://github.com/pyenv/pyenv/wiki#suggested-build-environment)
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- Use [pyenv-installer](https://github.com/pyenv/pyenv-installer): `curl https://pyenv.run | bash`
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- bash set-up:
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```bash
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echo '\n'\
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'# pyenv setup \n'\
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'export PYENV_ROOT="$HOME/.pyenv" \n'\
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'export PATH="$PYENV_ROOT/bin:$PATH" \n'\
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'eval "$(pyenv init --path)" \n'\
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'eval "$(pyenv init -)" \n'\
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'eval "$(pyenv virtualenv-init -)"' >> ~/.bashrc
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```
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- Usage
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- Install a python version: `pyenv install X.X.X`
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- Create a virtual environment: `pyenv virtualenv 3.9.6 dalle_env`
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- Activate: `pyenv activate dalle_env`
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Note: you can auto-activate your environment at a location with `echo dalle_env >> .python-version`
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### Tools
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- Git
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- `git config --global user.email "name@domain.com"
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- `git config --global user.name "First Last"
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- Github CLI
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- See [installation instructions](https://github.com/cli/cli/blob/trunk/docs/install_linux.md)
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- `gh auth login`
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- Direnv
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- Install direnv: `sudo apt-get update && sudo apt-get install direnv`
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- bash set-up:
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```bash
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echo -e '\n'\
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'# direnv setup \n'\
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'eval "$(direnv hook bash)" \n' >> ~/.bashrc
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```
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### Set up repo
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- Clone repo: `gh repo clone borisdayma/dalle-mini`
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- If using `pyenv-virtualenv`, auto-activate env: `echo dalle_env >> .python-version`
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## Environment
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- Install the following (use it later to update our dev requirements.txt)
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```
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requests
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pillow
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jupyterlab
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ipywidgets
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-e ../datasets[streaming]
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-e ../transformers
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-e ../webdataset
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# JAX
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--find-links https://storage.googleapis.com/jax-releases/libtpu_releases.html
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jax[tpu]>=0.2.16
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flax
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```
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- `transformers-cli login`
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---
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- set `HF_HOME="/mnt/disks/persist/cache/huggingface"` in `/etc/environment` and ensure you have required permissions, then restart.
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## Working with datasets or models
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- Install [Git LFS](https://github.com/git-lfs/git-lfs/wiki/Installation)
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- Clone a dataset without large files: `GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/.../...`
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- Use a local [credential store](https://git-scm.com/book/en/v2/Git-Tools-Credential-Storage) for caching credentials
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- Track specific extentions: `git lfs track "*.ext"`
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- See files tracked with LFS with `git lfs ls-files`
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dev/inference/dalle_mini
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requirements.txt
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# Requirements for huggingface spaces
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streamlit>=0.84.2
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setup.cfg
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[metadata]
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name = dalle_mini
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version = attr: dalle_mini.__version__
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description = DALL·E mini - Generate images from a text prompt
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long_description = file: README.md
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long_description_content_type = text/markdown
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url = https://github.com/borisdayma/dalle-mini
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project_urls =
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Bug Tracker = https://github.com/borisdayma/dalle-mini/issues
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[options]
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packages = find:
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install_requires =
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transformers
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jax
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flax
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setup.py
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from setuptools import setup
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if __name__ == "__main__":
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setup()
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