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Updated public release (#5)
* Delete existing files * Copy full-model code from 028c085 * Restore README.md from ace repo * Update README.md to add future docs and fix example link * Update full-model refs to ace/ACE * Remove refs to internal compute systems from README * Update version to 0.2.0 * Delete GPU CI test because it wont run on this repo * Remove Documentation section from README * Delete internal stuff from Makefile * Remove internal data processing configs/scripts * Also delete test_config.py
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‎.github/workflows/docs.yaml‎

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name: docs
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on:
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push:
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branches:
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- main
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pull_request:
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branches:
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- main
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jobs:
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build:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- uses: actions/setup-python@v4
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with:
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python-version: "3.10"
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- uses: actions/cache@v4
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with:
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path: ${{ env.pythonLocation }}
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key: ${{ env.pythonLocation }}-${{ hashFiles('fme/requirements.txt') }}-${{ hashFiles('fme/docs/requirements.txt') }}-${{ hashFiles('fme/constraints.txt') }}
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- name: Install dependencies
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run: |
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python -m pip install uv==0.2.5
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uv pip install --system -c constraints.txt -e fme[docs]
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- name: Build docs
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run: |
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cd fme/docs && make doctest html
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- name: Deploy to GitHub Pages
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uses: peaceiris/actions-gh-pages@v3
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if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/main' }}
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with:
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publish_branch: gh-pages
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github_token: ${{ secrets.GITHUB_TOKEN }}
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publish_dir: fme/docs/_build/
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force_orphan: true

‎.github/workflows/fme-unit-tests.yaml‎

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‎.github/workflows/tests.yaml‎

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name: tests
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on:
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push:
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branches:
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- main
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pull_request:
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branches:
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- main
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jobs:
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cpu:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- uses: actions/setup-python@v4
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with:
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python-version: "3.10"
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- uses: actions/cache@v4
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with:
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path: ${{ env.pythonLocation }}
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key: ${{ env.pythonLocation }}-${{ hashFiles('fme/requirements.txt') }}-${{ hashFiles('fme/dev-requirements.txt') }}-${{ hashFiles('fme/constraints.txt') }}
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- name: Install dependencies
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run: |
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python -m pip install uv==0.2.5
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uv pip install --system -c constraints.txt -e fme[dev]
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- name: Run pytest
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run: |
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make test

‎.gitignore‎

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fme/docs/available_modules.rst
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fme/docs/_build
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.vscode
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# Byte-compiled / optimized / DLL files
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# Sphinx documentation
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docs/_build/
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.DS_Store
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# PyBuilder
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target/
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# Pyre type checker
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.pyre/
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# scratch directory for testing
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scratch/

‎.pre-commit-config.yaml‎

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exclude: |
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(?x)^(
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models/fcn-mip/.+ |
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models/FourCastNet/.+
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)$
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repos:
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- repo: https://github.com/psf/black
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rev: 23.3.0
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name: flake8 __init__.py files
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files: "__init__.py"
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# ignore unused import error in __init__.py files
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args: ["--ignore=F401,E203", --config, setup.cfg]
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args: ["--ignore=F401,E203,W503", --config, setup.cfg]
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- repo: https://github.com/pre-commit/mirrors-mypy
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rev: v1.2.0
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hooks:

‎Makefile‎

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VERSION ?= $(shell git rev-parse --short HEAD)
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IMAGE ?= fme
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ENVIRONMENT_NAME ?= fme
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USERNAME ?= $(shell beaker account whoami --format=json | jq -r '.[0].name')
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build_docker_image:
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docker build -f docker/Dockerfile -t $(IMAGE):$(VERSION) .
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build_beaker_image: build_docker_image
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beaker image create --name $(IMAGE)-$(VERSION) $(IMAGE):$(VERSION)
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build_podman_image:
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podman-hpc build -f docker/Dockerfile -t $(IMAGE):$(VERSION) .
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migrate_podman_image: build_podman_image
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podman-hpc migrate $(IMAGE):$(VERSION)
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enter_docker_image: build_docker_image
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docker run -it --rm $(IMAGE):$(VERSION) bash
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launch_beaker_session:
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./launch-beaker-session.sh $(USERNAME)/$(IMAGE)-$(VERSION)
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install_local_packages:
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./install_local_packages.sh
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install_dependencies:
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./install_dependencies.sh
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# recommended to deactivate current conda environment before running this
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create_environment:
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conda create -n $(ENVIRONMENT_NAME) python=3.8 pip
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conda run -n $(ENVIRONMENT_NAME) ./install_dependencies.sh
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conda run -n $(ENVIRONMENT_NAME) ./install_local_packages.sh
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conda create -n $(ENVIRONMENT_NAME) python=3.10 pip
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conda run --no-capture-output -n $(ENVIRONMENT_NAME) python -m pip install uv==0.2.5
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conda run --no-capture-output -n $(ENVIRONMENT_NAME) uv pip install -c constraints.txt -e fme[dev]
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test_fme_unit_tests:
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pytest -m "not requires_gpu" --durations 10 fme/
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test:
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pytest --durations 20 .

‎README.md‎

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# ACE: AI2 Climate Emulator
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This repo contains the inference code accompanying "ACE: A fast, skillful learned global atmospheric model for climate prediction" ([arxiv:2310.02074](https://arxiv.org/abs/2310.02074)).
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## DISCLAIMER
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This is rapidly changing research software. We make no guarantees of maintaining backwards compatibility.
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## Quickstart
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### 1. Install
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`gs://ai2cm-public-requester-pays/2023-11-29-ai2-climate-emulator-v1/checkpoints/ace_ckpt.tar`.
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### 3. Update configuration and run
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Update the paths in the [example config](examples/config-inference.yaml). Then in the
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Update the paths in the [example config](fme/docs/inference-config.yaml). Then in the
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`fme` conda environment, run inference with:
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```
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python -m fme.fcn_training.inference.inference examples/config-inference.yaml
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python -m fme.ace.inference fme/docs/inference-config.yaml
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```
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## Configuration options
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See the `InferenceConfig` class in [this file](fme/fme/fcn_training/inference/inference.py) for
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description of configuration options. The [example config](examples/config-inference.yaml)
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shows some useful defaults for performing a 400-step simulation (100 days, with the 6-hour time step).
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## Performance
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While inference can be performed without a GPU, it may be very slow in that case. In addition,
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I/O performance is critical for fast inference due to loading of forcing data and target data
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during inference.
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## Analyzing output
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Various climate performance metrics are computed online by the inference code. These can be viewed via
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[wandb](https://wandb.ai) by setting `logging.log_to_wandb` to true and updating `logging.entity`
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to your wandb entity. Additionally, raw output data is saved to netCDF by the inference code.
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## Available datasets
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Two versions of the dataset described in [arxiv:2310.02074](https://arxiv.org/abs/2310.02074)
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are available:

‎constraints.txt‎

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torch==2.1.2 # minor version matches torch in Docker image

‎docker/Dockerfile‎

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FROM nvcr.io/nvidia/pytorch:22.08-py3
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FROM nvcr.io/nvidia/pytorch:23.08-py3
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ENV FME_DIR=/full-model
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ENV DGLBACKEND=pytorch
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# Install gcloud
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# Install gcloud- used for monthly netcdf data processing script
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# https://cloud.google.com/sdk/docs/install#deb
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RUN echo "deb [signed-by=/usr/share/keyrings/cloud.google.gpg] http://packages.cloud.google.com/apt cloud-sdk main" | \
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tee -a /etc/apt/sources.list.d/google-cloud-sdk.list && curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | \
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apt-key --keyring /usr/share/keyrings/cloud.google.gpg add - && apt-get update -y && apt-get install google-cloud-cli -y
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# install python deps
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COPY requirements_except_torch.txt /tmp/requirements.txt
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COPY requirements_no_deps.txt /tmp/requirements_no_deps.txt
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COPY fme/requirements.txt /tmp/requirements.txt
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RUN python3 -m pip install -r /tmp/requirements.txt
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RUN python3 -m pip install --no-deps -r /tmp/requirements_no_deps.txt
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# copy local code
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# copy local code and install
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COPY fme ${FME_DIR}/fme
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COPY install_local_packages.sh ${FME_DIR}/install_local_packages.sh
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RUN cd $FME_DIR && pip install --no-deps -e fme
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# install packages in full-model repo
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RUN cd $FME_DIR && ./install_local_packages.sh
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# copy after install so editing scripts does not trigger reinstall
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COPY scripts ${FME_DIR}/scripts

‎examples/config-inference.yaml‎

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