diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 0000000..0045c02 --- /dev/null +++ b/.dockerignore @@ -0,0 +1,5 @@ +# Ignore everything by default +* + +# Whitelist specific files/directories +!runtime/ \ No newline at end of file diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml new file mode 100644 index 0000000..7788f6a --- /dev/null +++ b/.github/workflows/build.yml @@ -0,0 +1,96 @@ + +name: build + +on: + push: + branches: [main] + paths: ["runtime/**", ".github/workflows/build.yml"] + pull_request: + paths: ["runtime/**", ".github/workflows/build.yml"] + workflow_dispatch: + inputs: + publishDev: + description: 'Publish dev image as cpu-{sha} and gpu-{sha}' + required: true + default: false + type: boolean + +permissions: + id-token: write + contents: read + +jobs: + build: + name: Build + runs-on: ubuntu-latest + strategy: + matrix: + proc: ["cpu", "gpu"] + env: + SHOULD_PUBLISH_LATEST: ${{ github.ref == 'refs/heads/main' && vars.PUBLISH_LATEST_ON_MAIN != '' }} + SHOULD_PUBLISH: | + ${{ + github.ref == 'refs/heads/main' && vars.PUBLISH_LATEST_ON_MAIN != '' + || github.event_name == 'workflow_dispatch' && inputs.publishDev + }} + + LOGIN_SERVER: literacyscreening.azurecr.io + IMAGE: literacy-screening-competition + + SHA_TAG: ${{ matrix.proc }}-${{ github.sha }} + LATEST_TAG: ${{ matrix.proc }}-latest + + steps: + - name: Remove unwanted software + run: | + echo "Available storage before:" + sudo df -h + echo + sudo rm -rf /usr/share/dotnet + sudo rm -rf /usr/local/lib/android + sudo rm -rf /opt/ghc + sudo rm -rf /opt/hostedtoolcache/CodeQL + echo "Available storage after:" + sudo df -h + echo + + - uses: actions/checkout@v4 + + - name: Build Image + run: | + docker build runtime \ + --build-arg CPU_OR_GPU=${{ matrix.proc }} \ + --tag $LOGIN_SERVER/$IMAGE:$SHA_TAG \ + ${{ fromJson(env.SHOULD_PUBLISH_LATEST) && '--tag $LOGIN_SERVER/$IMAGE:$LATEST_TAG' || '' }} + + - name: Check image size + run: | + docker image list $LOGIN_SERVER/$IMAGE --format "{{.Tag}}: {{.Size}}" | tee -a $GITHUB_STEP_SUMMARY + + - name: Tests packages in container + run: | + docker run --network none \ + $LOGIN_SERVER/$IMAGE:$SHA_TAG \ + /code_execution/.pixi/envs/${{ matrix.proc }}/bin/python -m pytest tests + + - name: Log into Azure + if: ${{ fromJson(env.SHOULD_PUBLISH) }} + uses: azure/login@v1 + with: + client-id: ${{secrets.AZURE_CLIENT_ID}} + tenant-id: ${{secrets.AZURE_TENANT_ID}} + subscription-id: ${{secrets.AZURE_SUBSCRIPTION_ID}} + + - name: Log into ACR with Docker + if: ${{ fromJson(env.SHOULD_PUBLISH) }} + uses: azure/docker-login@v1 + with: + login-server: ${{ env.LOGIN_SERVER }} + username: ${{ secrets.REGISTRY_USERNAME }} + password: ${{ secrets.REGISTRY_PASSWORD }} + + - name: Push image to ACR + if: ${{ fromJson(env.SHOULD_PUBLISH) }} + run: | + docker push $LOGIN_SERVER/$IMAGE --all-tags + diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..ecee059 --- /dev/null +++ b/.gitignore @@ -0,0 +1,175 @@ +data/* +submission/* +submission_src/* +!.gitkeep + +## Python.gitignore +## https://github.com/github/gitignore/blob/4488915eec0b3a45b5c63ead28f286819c0917de/Python.gitignore + +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/#use-with-ide +.pdm.toml + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +**/.pixi/envs +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ + +# Ruff formating +.ruff_cache/ + +# Model weights +**/*.pt diff --git a/CHANGELOG.md b/CHANGELOG.md new file mode 100644 index 0000000..e2e44f8 --- /dev/null +++ b/CHANGELOG.md @@ -0,0 +1,13 @@ +# Changelog + +All notable changes to this project will be documented in this file. + +The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), +and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). + +## 2024-11-05 + +### Added + +- Initial commit + diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..bb3e722 --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2023 DrivenData + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/MAINTAINERS.md b/MAINTAINERS.md new file mode 100644 index 0000000..ae98f11 --- /dev/null +++ b/MAINTAINERS.md @@ -0,0 +1,3 @@ +# Maintainer notes + +This file documents notes for maintainers of the repository. diff --git a/Makefile b/Makefile new file mode 100644 index 0000000..708a161 --- /dev/null +++ b/Makefile @@ -0,0 +1,282 @@ +################################################################################# +# Settings # +################################################################################# + +ifeq (, $(shell which nvidia-smi)) +CPU_OR_GPU ?= cpu +else +CPU_OR_GPU ?= gpu +endif + +BLOCK_INTERNET ?= true +PLATFORM_ARGS = --platform linux/amd64 + +TAG := ${CPU_OR_GPU}-latest +LOCAL_TAG := ${CPU_OR_GPU}-local + +IMAGE_NAME = literacy-screening-competition +OFFICIAL_IMAGE = literacyscreening.azurecr.io/${IMAGE_NAME} +LOCAL_IMAGE = ${IMAGE_NAME} + +# Resolve which image to use in commands. The priority is: +# 1. User-provided, e.g., SUBMISSION_IMAGE=my-image:gpu-local make test-submission +# 2. Local image, e.g., literacy-screening-competition:gpu-local +# 3. Official competition image, e.g., literacyscreening.azurecr.io/literacy-screening-competition +SUBMISSION_IMAGE ?= ${LOCAL_IMAGE}:${LOCAL_TAG} +ifeq (,$(shell docker images -q ${SUBMISSION_IMAGE})) +SUBMISSION_IMAGE = ${OFFICIAL_IMAGE}:${TAG} +endif + +# Get the image ID +SUBMISSION_IMAGE_ID := $(shell docker images -q ${SUBMISSION_IMAGE}) + +# Name of the running container, i.e., docker run ... --name +CONTAINER_NAME ?= ${IMAGE_NAME} + +# Enable or disable host GPU access +ifeq (${CPU_OR_GPU}, gpu) +GPU_ARGS = --gpus all +endif + +SKIP_GPU ?= false +ifeq (${SKIP_GPU}, true) +GPU_ARGS = +endif + +# If no TTY (for example GitHub Actions CI) no interactive tty commands for docker +ifneq (true, ${GITHUB_ACTIONS_NO_TTY}) +TTY_ARGS = -it +endif + +# Option to block or allow internet access from the submission Docker container +ifeq (true, ${BLOCK_INTERNET}) +NETWORK_ARGS = --network none +endif + +# Name of the example submission to pack when running `make pack-example` +EXAMPLE ?= random + +.PHONY: _check_image _echo_image _submission_write_perms + +# Give write access to the submission folder to everyone so Docker user can write when mounted +_submission_write_perms: + mkdir -p submission/ + chmod -R 0777 submission/ + + +_check_image: +# If container does not exist, error and tell user to pull or build +ifeq (${SUBMISSION_IMAGE_ID},) + $(error To test your submission, you must first run `make pull` (to get official container) or `make build` \ + (to build a local version if you have changes).) +endif + +_echo_image: + @echo +ifeq (,${SUBMISSION_IMAGE_ID}) + @echo "$$(tput bold)Using image:$$(tput sgr0) ${SUBMISSION_IMAGE} (image does not exist locally)" + @echo +else + @echo "$$(tput bold)Using image:$$(tput sgr0) ${SUBMISSION_IMAGE} (${SUBMISSION_IMAGE_ID})" + @echo "┏" + @echo "┃ NAME(S)" + + @docker inspect $(SUBMISSION_IMAGE_ID) --format='{{join .RepoTags "\n"}}' | awk '{print "┃ "$$0}' + + @echo "└" + @echo +endif +ifeq (,$(shell docker images ${OFFICIAL_IMAGE} -q)) + @echo "$$(tput bold)No official images available locally$$(tput sgr0)" + @echo "Run 'make pull' to download the official image." + @echo +else + @echo "$$(tput bold)Available official images:$$(tput sgr0)" + @echo "┏" + @docker images ${OFFICIAL_IMAGE} | awk '{print "┃ "$$0}' + @echo "└" + @echo +endif +ifeq (,$(shell docker images ${LOCAL_IMAGE} -q)) + @echo "$$(tput bold)No local images available$$(tput sgr0)" + @echo "Run 'make build' to build the image." + @echo +else + @echo "$$(tput bold)Available local images:$$(tput sgr0)" + @echo "┏" + @docker images ${LOCAL_IMAGE} | awk '{print "┃ "$$0}' + @echo "└" + @echo +endif + +################################################################################# +# Commands for building the container if you are changing the requirements # +################################################################################# +.PHONY: build clean interact-container pack-example pack-submission pull test-container test-submission update-lockfile + +## Builds the container locally +build: + docker build runtime \ + --build-arg CPU_OR_GPU=${CPU_OR_GPU} \ + --tag ${LOCAL_IMAGE}:${LOCAL_TAG} + +## Updates runtime environment lockfile using Docker +update-lockfile: runtime/pixi.lock + @echo Building Docker image to generate lockfile + docker build runtime \ + --file runtime/Dockerfile-lock \ + --tag pixi-lock:local + @echo Running lock container + docker run \ + ${PLATFORM_ARGS} \ + --mount type=bind,source="$(shell pwd)"/runtime/pixi.toml,target=/tmp/pixi.toml \ + --mount type=bind,source="$(shell pwd)"/runtime/pixi.lock,target=/tmp/pixi.lock \ + --rm \ + pixi-lock:local + +## Ensures that your locally built image can import all the Python packages successfully when it runs +test-container: _check_image _echo_image _submission_write_perms + docker run \ + ${PLATFORM_ARGS} \ + ${GPU_ARGS} \ + ${NETWORK_ARGS} \ + ${TTY_ARGS} \ + --mount type=bind,source="$(shell pwd)"/runtime/tests,target=/tests,readonly \ + --pid host \ + ${SUBMISSION_IMAGE_ID} \ + pixi run -e ${CPU_OR_GPU} python -m pytest tests + +## Open an interactive bash shell within the running container (with network access) +interact-container: _check_image _echo_image _submission_write_perms + docker run \ + ${PLATFORM_ARGS} \ + ${GPU_ARGS} \ + ${NETWORK_ARGS} \ + --mount type=bind,source=${shell pwd}/data,target=/code_execution/data,readonly \ + --mount type=bind,source="$(shell pwd)/submission",target=/code_execution/submission \ + --shm-size 8g \ + --pid host \ + -it \ + ${SUBMISSION_IMAGE_ID} \ + bash + +################################################################################# +# Commands for testing and debugging your submission # +################################################################################# + +## Pulls the official container from Azure Container Registry +pull: + docker pull ${OFFICIAL_IMAGE}:${TAG} + +## Creates a submission/submission.zip file from the source code in examples +pack-example: +# Don't overwrite so no work is lost accidentally +ifneq (,$(wildcard ./submission/submission.zip)) + $(error You already have a submission/submission.zip file. Rename or remove that file (e.g., rm submission/submission.zip).) +endif + mkdir -p submission/ + cd examples/${EXAMPLE}; zip -r ../../submission/submission.zip ./* + +## Creates a submission/submission.zip file from the source code in submission_src +pack-submission: +# Don't overwrite so no work is lost accidentally +ifneq (,$(wildcard ./submission/submission.zip)) + $(error You already have a submission/submission.zip file. Rename or remove that file (e.g., rm submission/submission.zip).) +endif +# Note that the glob wildcard excludes hidden/dot files + mkdir -p submission/ + cd submission_src; zip -r ../submission/submission.zip ./* + +## Runs container using code from `submission/submission.zip` and data from `/code_execution/data/` +test-submission: _check_image _echo_image _submission_write_perms +# if submission file does not exist +ifeq (,$(wildcard ./submission/submission.zip)) + $(error To test your submission, you must first put a "submission.zip" file in the "submission" folder. \ + If you want to use an example, you can run `make pack-example` first) +endif + docker run \ + ${PLATFORM_ARGS} \ + ${TTY_ARGS} \ + ${GPU_ARGS} \ + ${NETWORK_ARGS} \ + -e LOGURU_LEVEL=INFO \ + -e IS_SMOKE_TEST=true \ + --mount type=bind,source=${shell pwd}/data,target=/code_execution/data,readonly \ + --mount type=bind,source="$(shell pwd)/submission",target=/code_execution/submission \ + --shm-size 8g \ + --pid host \ + --name ${CONTAINER_NAME} \ + --rm \ + ${SUBMISSION_IMAGE_ID} + +## Delete temporary Python cache and bytecode files +clean: + find . -type f -name "*.py[co]" -delete + find . -type d -name "__pycache__" -delete + +## Format code with ruff +format: + ruff format + +################################################################################# +# Self Documenting Commands # +################################################################################# + +.DEFAULT_GOAL := help + +# Inspired by +# sed script explained: +# /^##/: +# * save line in hold space +# * purge line +# * Loop: +# * append newline + line to hold space +# * go to next line +# * if line starts with doc comment, strip comment character off and loop +# * remove target prerequisites +# * append hold space (+ newline) to line +# * replace newline plus comments by `---` +# * print line +# Separate expressions are necessary because labels cannot be delimited by +# semicolon; see +.PHONY: help +help: _echo_image + @echo + @echo "$$(tput bold)Available commands:$$(tput sgr0)" + @echo + @sed -n -e "/^## / { \ + h; \ + s/.*//; \ + :doc" \ + -e "H; \ + n; \ + s/^## //; \ + t doc" \ + -e "s/:.*//; \ + G; \ + s/\\n## /---/; \ + s/\\n/ /g; \ + p; \ + }" ${MAKEFILE_LIST} \ + | LC_ALL='C' sort --ignore-case \ + | awk -F '---' \ + -v ncol=$$(tput cols) \ + -v indent=19 \ + -v col_on="$$(tput setaf 6)" \ + -v col_off="$$(tput sgr0)" \ + '{ \ + printf "%s%*s%s ", col_on, -indent, $$1, col_off; \ + n = split($$2, words, " "); \ + line_length = ncol - indent; \ + for (i = 1; i <= n; i++) { \ + line_length -= length(words[i]) + 1; \ + if (line_length <= 0) { \ + line_length = ncol - indent - length(words[i]) - 1; \ + printf "\n%*s ", -indent, " "; \ + } \ + printf "%s ", words[i]; \ + } \ + printf "\n"; \ + }' \ + | more $(shell test $(shell uname) = Darwin && echo '--no-init --raw-control-chars') + @echo diff --git a/README.md b/README.md new file mode 100644 index 0000000..615697b --- /dev/null +++ b/README.md @@ -0,0 +1,217 @@ +# Goodnight Moon, Hello Early Literacy Screening + +![Python 3.12](https://img.shields.io/badge/Python-3.12-blue) [![Goodnight Moon, Hello Early Literacy Screening](https://img.shields.io/badge/DrivenData-Goodnight%20Moon,%20Hello%20Early%20Literacy%20Screening-white?logo=data:image/png;base64,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)](https://www.drivendata.org/competitions/298/literacy-screening) + +Welcome to the runtime repository for the [Goodnight Moon, Hello Early Literacy Screening](https://www.drivendata.org/competitions/298/literacy-screening) competition on DrivenData! This repository contains a few things to help you create your code submission for this code execution competition: + +1. **Runtime environment specification** ([`runtime/`](./runtime/)) — the definition of the environment in which your code will run. +2. **Example submissions** ([`examples/`](./examples/)) — simple demonstration solutions that will run successfully in the code execution runtime and output a valid submission. + - **Random probabilities** ([`examples/random`](./examples/random/main.py/)): a dummy submission that generates a random prediction for each audio file + - **Whisper transcription** ([`examples/transcription`](./examples/transcription/main.py/)): a baseline submission that shows how to load a model asset as part of your submission. This submission uses OpenAI's Whisper model to transcribe each audio clip and compares the transcription to the expected text. It requires that you download the model weights beforehand and include them in the `assets` directory. There's no internet access in the runtime container, so any pretrained model weights must be included as part of the submission. + +You can use this repository to: + +💡 **Get started**: The example submissions provide a basic functional solution. They probably won't win you the competition, but you can use them as a guide for bringing in your own work and generating a real submission. + +🔧 **Test your submission**: Test your submission using a locally running version of the competition runtime to discover errors before submitting to the competition website. + +📦 **Request new packages in the official runtime**: Since your submission will not have general access to the internet, all dependencies must be pre-installed. If you want to use a package that is not in the runtime environment, make a pull request to this repository. + +Changes to the repository are documented in [CHANGELOG.md](./CHANGELOG.md). + +--- + +#### [1. Quickstart](#quickstart) + +- [Prerequisites](#prerequisites) +- [Setting up the data directory](#setting-up-the-data-directory) +- [Running `make` commands](#running-make-commands) + +#### [2. Testing a submission locally](#testing-a-submission-locally) +- [Code submission format](#code-submission-format) +- [Running your submission locally](#running-your-submission-locally) +- [Smoke tests](#smoke-tests) +- [Runtime network access](#runtime-network-access) + +#### [3. Updating runtime packages](#updating-runtime-packages) + +#### [4. Makefile commands](#makefile-commands) + +--- + +## Quickstart + +This quickstart guide will show you how to get the provided example solution running end-to-end. Once you get there, it's off to the races! + +### Prerequisites + +When you make a submission on the DrivenData competition site, we run your submission inside a Docker container, a virtual operating system that allows for a consistent software environment across machines. **The best way to make sure your submission to the site will run is to first run it successfully in the container on your local machine**. For that, you'll need: + +- A clone of this repository +- [Docker](https://docs.docker.com/get-docker/) +- At least 8 GB of free space for the Docker image +- [GNU make](https://www.gnu.org/software/make/) (optional, but useful for running the commands in the Makefile) + +Additional requirements to run with GPU: + +- [NVIDIA drivers](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#package-manager-installation) with CUDA 12 +- [NVIDIA container toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/index.html) + +### Setting up the data directory + +In the official code execution platform, `code_execution/data` will contain the test set audio files, `test_metadata.csv`, and `submission_format.csv`. + +To test your submission locally, you should use the smoke test data from the [data download page](https://www.drivendata.org/competitions/298/literacy-screening/data/). Download `smoke.tar.gz` and then run `tar xzvf smoke.tar.gz --strip-components=1 -C data/`. This will extract the files directly into `data/` without nesting them in subdirectories. Your local `data` dir should look like: + +``` +data +├── bfaiol.wav +├── czfqjg.wav +├── fprljz.wav +├── hgxrel.wav +├── htfbnp.wav +├── idjpne.wav +├── ktvyww.wav +├── ltbona.wav +├── submission_format.csv +├── test_labels.csv +└── test_metadata.csv +``` + +Now you're ready to run your submission against this data! + +Keep in mind, the smoke test data contains clips from the _training set_. That's why we provide the labels too. Of course, the real test set labels won't be available in the runtime container 😉 + +### Running `make` commands + +To test out the full execution pipeline, make sure Docker is running and then run the following commands in the terminal: + +1. **`make pull`** pulls the latest official Docker image from the container registry. You'll need an internet connection for this. +1. **`make pack-example`** packages a code submission with the `main.py` contained in `examples/random/` and saves it as `submission/submission.zip`. +1. **`make test-submission`** will do a test run of your submission, simulating what happens during actual code execution. This command runs the Docker container with the requisite host directories mounted, and executes `main.py` to produce a submission file containing your predictions. + +```bash +make pull +make pack-example +make test-submission +``` + +🎉 **Congratulations!** You've just completed your first test run for the Goodnight Moon, Hello Early Literacy Screening Challenge. If everything worked as expected, you should see that a new submission file has been generated. + +If you were ready to make a real submission to the competition, you would upload the `submission.zip` file from step 2 above to the competition [submission page](https://www.drivendata.org/competitions/298/literacy-screening/submissions/). + +To run the Whisper transcription example instead, run `EXAMPLE=transcription make pack-example`. Just be sure to download the Whisper model first and include it in the `assets` directory. There's no internet access in the runtime container, so any pretrained model weights must be included as part of the submission. + +## Testing your submission locally + +As you develop your own submission, you'll need to know a little bit more about how your submission will be unpacked for running inference. This section contains more complete documentation for developing and testing your own submission. + +### Code submission format + +Your final submission should be a zip archive named with the extension `.zip` (for example, `submission.zip`). The root level of the `submission.zip` file must contain a `main.py` which performs inference on the test audio clips and writes the predictions to a file named `submission.csv` in the same directory as `main.py`. Check out the `main.py` scripts in the [example submissions](./examples/). + +### Running your submission locally + +This section provides instructions on how to run the your submission in the code execution container from your local machine. To simplify the steps, key processes have been defined in the `Makefile`. Commands from the `Makefile` are then run with `make {command_name}`. The basic steps are: + +```sh +make pull +make pack-submission +make test-submission +``` + +Run `make help` for more information about the available commands as well as information on the official and built images that are available locally. + +Here's the process in a bit more detail: + +1. First, make sure you have set up the [prerequisites](#prerequisites). +2. Download the official competition Docker image: + + ```sh + make pull + ``` + +> [!NOTE] +> If you have built a local version of the runtime image with `make build`, that image will take precedence over the pulled image when using any make commands that run a container. You can explicitly use the pulled image by setting the `SUBMISSION_IMAGE` shell/environment variable to the pulled image or by deleting all locally built images. + +3. Save all of your submission files, including the required `main.py` script, in the `submission_src` folder of the runtime repository. Make sure any needed model weights and other assets are saved in `submission_src` as well. + +4. Create a `submission/submission.zip` file containing your code and model assets: + + ```sh + make pack-submission + #> mkdir -p submission/ + #> cd submission_src; zip -r ../submission/submission.zip ./* + #> adding: main.py (deflated 73%) + ``` + +5. Launch an instance of the competition Docker image, and run the same inference process that will take place in the official runtime: + + ```sh + make test-submission + ``` + +This runs the container [entrypoint](./runtime/entrypoint.sh) script. First, it unzips `submission/submission.zip` into `/code_execution/` in the container. Then, it runs your submitted `main.py`. In the local testing setting, the final submission is saved out to the `submission/` folder on your local machine. + +> [!NOTE] +> Remember that `/code_execution/data` is just a mounted version of what you have saved locally in `data` so you will just be using the training files for local testing. In the official code execution platform, `/code_execution/data` will contain the actual test data. + +When you run `make test-submission` the logs will be printed to the terminal and written out to `submission/log.txt`. If you run into errors, use the container logs written to `log.txt` to determine what changes you need to make for your code to execute successfully. + +### Smoke tests + +When submitting on the platform, you will have the ability to submit "smoke tests". Smoke tests run on a reduced version of the test set data in order to run and debug issues more quickly. They will not be considered for prize evaluation and are intended to let you test your code for correctness. **You should test your code locally as thorougly as possible before submitting your code for smoke tests or for full evaluation.** + +## Updating runtime packages + +If you want to use a package that is not in the environment, you are welcome to make a pull request to this repository. Remember, your submission will only have access to packages in this runtime repository. If you're new to the GitHub contribution workflow, check out [this guide by GitHub](https://docs.github.com/en/get-started/quickstart/contributing-to-projects). + +The runtime manages dependencies using [Pixi](https://pixi.sh/latest/). Here is a good [tutorial](https://pixi.sh/latest/tutorials/python/) to get started with Pixi. The official runtime uses **Python 3.12.7**. + +1. Fork this repository. + +2. Install pixi. See [here](https://pixi.sh/latest/#installation) for installation options. + +3. Edit the `runtime/pixi.toml` file to add your new packages. We recommend starting without a specific pinned version, and then pinning to the version in the resolved `pixi.lock` file that is generated. + + - Conda-installed packages go in the `dependencies` section. These install from the [conda-forge](https://anaconda.org/conda-forge/) channel. **Installing packages with conda is strongly preferred.** Packages should only be installed using pip if they are not available in a conda channel. + - Pip-installed packages go in the `pypi-dependencies` section. + - GPU-specific dependencies go in the `features.cuda.dependencies` section, but these should be uncommon. + +4. With Docker open and running, run `make update-lockfile`. This will generate an updated `runtime/pixi.lock` from `runtime/pixi.toml` within a Docker container. + +5. Locally test that the Docker image builds successfully for both the CPU and GPU environment: + + ```sh + CPU_OR_GPU=cpu make build + CPU_OR_GPU=gpu make build + ``` + +6. Commit the changes to your forked repository. Ensure that your branch includes updated versions of both `runtime/pixi.toml` and `runtime/pixi.lock`. + +7. Open a pull request from your branch to the `main` branch of this repository. Navigate to the [Pull requests](https://github.com/drivendataorg/literacy-screening-runtime/pulls) tab in this repository, and click the "New pull request" button. For more detailed instructions, check out [GitHub's help page](https://help.github.com/en/articles/creating-a-pull-request-from-a-fork). + +8. Once you open the pull request, we will use Github Actions to build the Docker images with your changes and run the tests in `runtime/tests`. For security reasons, administrators may need to approve the workflow run before it happens. Once it starts, the process can take up to 30 minutes, and may take longer if your build is queued behind others. You will see a section on the pull request page that shows the status of the tests and links to the logs ("Details"): + + ![Example appearance of Github Actions](https://s3.amazonaws.com/drivendata-public-assets/codex_github_actions_build.png) + +9. You may be asked to submit revisions to your pull request if the tests fail or if a DrivenData staff member has feedback. Pull requests won't be merged until all tests pass and the team has reviewed and approved the changes. + +## Make commands + +A Makefile with several helpful shell recipes is included in the repository. The runtime documentation above uses it extensively. Running `make` by itself in your shell will list relevant Docker images and provide you the following list of available commands: + +``` +Available commands: + +build Builds the container locally +clean Delete temporary Python cache and bytecode files +format Format code with ruff +interact-container Open an interactive bash shell within the running container (with network access) +pack-example Creates a submission/submission.zip file from the source code in examples +pack-submission Creates a submission/submission.zip file from the source code in submission_src +pull Pulls the official container from Azure Container Registry +test-container Ensures that your locally built image can import all the Python packages successfully when it runs +test-submission Runs container using code from `submission/submission.zip` and data from `/code_execution/data/` +update-lockfile Updates runtime environment lockfile using Docker +``` diff --git a/data/.gitkeep b/data/.gitkeep new file mode 100644 index 0000000..e69de29 diff --git a/dev-requirements.txt b/dev-requirements.txt new file mode 100644 index 0000000..af3ee57 --- /dev/null +++ b/dev-requirements.txt @@ -0,0 +1 @@ +ruff diff --git a/examples/random/main.py b/examples/random/main.py new file mode 100644 index 0000000..835b210 --- /dev/null +++ b/examples/random/main.py @@ -0,0 +1,39 @@ +"""This is an example submission that just generates random predictions.""" + +from pathlib import Path + +import librosa +from loguru import logger +import numpy as np +import pandas as pd + +DATA_DIR = Path("data/") + + +def main(): + # load the two csvs in the data directory + df = pd.read_csv(DATA_DIR / "submission_format.csv", index_col="filename") + metadata = pd.read_csv(DATA_DIR / "test_metadata.csv", index_col="filename") + + # set random state for a reproducible submission since we're generating random probabilities + rng = np.random.RandomState(99) + + # iterate over audio files + scores = [] + for file in df.index: + logger.info(f"Loading {file}") + audio, sr = librosa.load(DATA_DIR / file) + + # since this is a dummy submission, just assign a random number between 0 and 1 + scores.append(rng.random()) + + # write the scores to score column in the submission format + df["score"] = scores + + # write out predictions to submission.csv in the main directory + logger.info("Writing out submission.csv") + df.to_csv("submission.csv") + + +if __name__ == "__main__": + main() diff --git a/examples/transcription/assets/.gitkeep b/examples/transcription/assets/.gitkeep new file mode 100644 index 0000000..e69de29 diff --git a/examples/transcription/main.py b/examples/transcription/main.py new file mode 100644 index 0000000..c4fbd46 --- /dev/null +++ b/examples/transcription/main.py @@ -0,0 +1,61 @@ +"""This is an example submission that uses a pretrained model to generate transcriptions. +Note: for this submission to work, you must download the whisper model to the assets/ dir first.""" + +import string +from pathlib import Path + +from loguru import logger +import numpy as np +import pandas as pd +import torch +import whisper + +DATA_DIR = Path("data/") + + +def download_whisper_model(download_root="assets"): + """Code to download model locally so we can include it in our submission""" + whisper.load_model("turbo", download_root=download_root) + + +def clean_column(col: pd.Series): + return col.str.lower().str.strip().replace(f"[{string.punctuation}]", "", regex=True) + + +def main(): + # load the metadata that has the expected text for each audio file + df = pd.read_csv(DATA_DIR / "test_metadata.csv", index_col="filename") + + # load whisper model and put on GPU if available + device = "cuda" if torch.cuda.is_available() else "cpu" + model = whisper.load_model("assets/large-v3-turbo.pt").to(device) + + # iterate over audio files and get transcribed text + transcribed_texts = [] + for file in df.index: + logger.info(f"Transcribing {file}") + # set temperature at 0 for reproducible results + result = model.transcribe(str(DATA_DIR / file), language="english", temperature=0) + transcribed_texts.append(result["text"]) + + df["transcribed_text"] = transcribed_texts + + # clean columns to avoid false mismatches + df["expected_text"] = clean_column(df.expected_text) + df["transcribed_text"] = clean_column(df.transcribed_text) + + # score = 1 if transcribed text matches expected text + # score = 0.5 if transcription doesn't match; avoids penalizing confident but wrong + df["score"] = np.where(df.transcribed_text == df.expected_text, 1.0, 0.5) + + # ensure index matches submission format + sub_format = pd.read_csv(DATA_DIR / "submission_format.csv", index_col="filename") + preds = df[["score"]].loc[sub_format.index] + + # write out predictions to submission.csv in the main directory + logger.info("Writing out submission.csv") + preds.to_csv("submission.csv") + + +if __name__ == "__main__": + main() diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..9b59dc9 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,2 @@ +[tool.ruff] +line-length = 99 diff --git a/runtime/Dockerfile b/runtime/Dockerfile new file mode 100644 index 0000000..bd4df17 --- /dev/null +++ b/runtime/Dockerfile @@ -0,0 +1,49 @@ +FROM --platform=linux/amd64 ghcr.io/prefix-dev/pixi:0.34.0-jammy-cuda-12.1.1 + +USER root + +ARG CPU_OR_GPU=gpu + +ENV DEBIAN_FRONTEND=noninteractive \ + LANG=C.UTF-8 \ + LC_ALL=C.UTF-8 \ + PYTHONUNBUFFERED=1 \ + SHELL=/bin/bash + +# Create user andset permissions +ENV RUNTIME_USER=runtimeuser +ENV RUNTIME_UID=1000 +ENV RUNTIME_GID=1000 +ENV CPU_OR_GPU=$CPU_OR_GPU +ENV CONDA_OVERRIDE_CUDA="12.1" + +RUN echo "Creating ${RUNTIME_USER} user..." \ + && groupadd --gid ${RUNTIME_GID} ${RUNTIME_USER} \ + && useradd --create-home --gid ${RUNTIME_GID} --no-log-init --uid ${RUNTIME_UID} ${RUNTIME_USER} + +COPY apt.txt apt.txt +RUN apt-get update --fix-missing \ + && apt-get install -y apt-utils 2> /dev/null \ + && xargs -a apt.txt apt-get install -y \ + && apt-get clean \ + && rm -rf /var/lib/apt/lists/* /apt.txt + +# Set up code execution working directory +RUN mkdir /code_execution +RUN chown -R ${RUNTIME_USER}:${RUNTIME_USER} /code_execution +WORKDIR /code_execution + +# Switch to runtime user +USER ${RUNTIME_USER} + +COPY pixi.lock ./pixi.lock +COPY pixi.toml ./pixi.toml + +RUN pixi install -e ${CPU_OR_GPU} --frozen \ + && pixi clean cache --yes \ + && pixi info + +COPY entrypoint.sh /entrypoint.sh +COPY --chown=${RUNTIME_USER}:${RUNTIME_USER} tests ./tests + +CMD ["bash", "/entrypoint.sh"] diff --git a/runtime/Dockerfile-lock b/runtime/Dockerfile-lock new file mode 100644 index 0000000..fcd8edf --- /dev/null +++ b/runtime/Dockerfile-lock @@ -0,0 +1,8 @@ +FROM --platform=linux/amd64 ghcr.io/prefix-dev/pixi:0.34.0-jammy + +USER root + +RUN mkdir -p /tmp +WORKDIR /tmp + +ENTRYPOINT ["pixi", "ls", "--manifest-path", "pixi.toml", "--platform", "linux-64", "-v"] diff --git a/runtime/apt.txt b/runtime/apt.txt new file mode 100644 index 0000000..fd64c1a --- /dev/null +++ b/runtime/apt.txt @@ -0,0 +1,6 @@ +curl +ffmpeg +libxml2 +tzdata +wget +zip diff --git a/runtime/entrypoint.sh b/runtime/entrypoint.sh new file mode 100644 index 0000000..aba4637 --- /dev/null +++ b/runtime/entrypoint.sh @@ -0,0 +1,48 @@ +#!/bin/bash + +set -euxo pipefail + +main () { + expected_filename=main.py + + cd /code_execution + + submission_files=$(zip -sf ./submission/submission.zip) + if ! grep -q ${expected_filename}<<<$submission_files; then + echo "Submission zip archive must include $expected_filename" + return 1 + fi + + echo "Unpacking submission" + unzip ./submission/submission.zip -d ./ + + ls -alh + + if $IS_SMOKE_TEST; then + echo "Running smoke test" + pixi run -e $CPU_OR_GPU python main.py + else + echo "Running submission using $CPU_OR_GPU" + pixi run -e $CPU_OR_GPU python main.py &> "/code_execution/submission/private_log.txt" + fi + + echo "Exporting submission.csv result..." + + # Valid scripts must create a "submission.csv" file within the same directory as main + if [ -f "submission.csv" ] + then + echo "Script completed its run." + cp submission.csv ./submission/submission.csv + else + echo "ERROR: Script did not produce a submission.csv file in the main directory." + exit_code=1 + fi +} + +main |& tee "/code_execution/submission/log.txt" +exit_code=${PIPESTATUS[0]} + +# Copy for terminationMessagePath +cp /code_execution/submission/log.txt /tmp/log + +exit $exit_code diff --git a/runtime/pixi.lock b/runtime/pixi.lock new file mode 100644 index 0000000..c65d448 --- /dev/null +++ b/runtime/pixi.lock @@ -0,0 +1,7225 @@ +version: 5 +environments: + cpu: + channels: + - url: https://conda.anaconda.org/conda-forge/ + - url: https://conda.anaconda.org/pytorch/ + indexes: + - https://pypi.org/simple + packages: + linux-64: + - conda: https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2 + - conda: 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"literacy-screening" +channels = ["conda-forge", "pytorch"] +platforms = ["linux-64"] + +# conda package dependencies +[dependencies] +accelerate = "1.0.1" +einops = "0.8.0" +langchain = "0.3.*" +librosa = "0.10.2.post1" +loguru = "0.7.*" +numpy = "1.26.*" +pandas = "2.2.3" +pytest = "8.3.3" +python = "3.12.7" +pytorch = {version = "2.4.1", channel = "pytorch"} +scikit-learn = "1.5.*" +scipy = "1.14.*" +torchaudio = {version = "2.4.1", channel = "pytorch"} +torchvision = {version = "0.19.1", channel = "pytorch"} +transformers = "4.46.*" +tqdm = "4.66.*" + +[pypi-dependencies] +speechbrain = "==1.0.1" +openai-whisper = "==20240930" + +[feature.cuda] +platforms = ["linux-64"] +channels = ["nvidia", {channel = "pytorch", priority = -1}] +system-requirements = {cuda = "12.1"} + +[feature.cuda.dependencies] +pytorch-cuda = {version = "12.1.*", channel = "pytorch"} + +[feature.cpu] +platforms = ["linux-64"] + +[feature.cuda.tasks] +check_cuda = 'python -c "import torch; print(torch.cuda.is_available())"' + +[environments] +cpu = ["cpu"] +gpu = ["cuda"] diff --git a/runtime/tests/test_packages.py b/runtime/tests/test_packages.py new file mode 100644 index 0000000..d499048 --- /dev/null +++ b/runtime/tests/test_packages.py @@ -0,0 +1,42 @@ +import importlib +import subprocess + +import pytest + +packages = [ + "numpy", + "pandas", + "scipy", + "sklearn", + "torch", + "torchaudio", + "transformers", + "whisper", + "speechbrain", +] + + +def is_gpu_available(): + try: + return subprocess.check_call(["nvidia-smi"]) == 0 + + except FileNotFoundError: + return False + + +GPU_AVAILABLE = is_gpu_available() + + +@pytest.mark.parametrize("package_name", packages, ids=packages) +def test_import(package_name): + """Test that certain dependencies are importable.""" + importlib.import_module(package_name) + + +@pytest.mark.skipif(not GPU_AVAILABLE, reason="No GPU available") +def test_allocate_torch(): + import torch + + assert torch.cuda.is_available() + + torch.zeros(1).cuda() diff --git a/submission_src/.gitkeep b/submission_src/.gitkeep new file mode 100644 index 0000000..e69de29