Files
lerobot/.github/workflows/nightly.yml
Pepijn e82e7a02e9 feat(train): add accelerate for multi gpu training (#2154)
* Enhance training and logging functionality with accelerator support

- Added support for multi-GPU training by introducing an `accelerator` parameter in training functions.
- Updated `update_policy` to handle gradient updates based on the presence of an accelerator.
- Modified logging to prevent duplicate messages in non-main processes.
- Enhanced `set_seed` and `get_safe_torch_device` functions to accommodate accelerator usage.
- Updated `MetricsTracker` to account for the number of processes when calculating metrics.
- Introduced a new feature in `pyproject.toml` for the `accelerate` library dependency.

* Initialize logging in training script for both main and non-main processes

- Added `init_logging` calls to ensure proper logging setup when using the accelerator and in standard training mode.
- This change enhances the clarity and consistency of logging during training sessions.

* add docs and only push model once

* Place  logging under accelerate and update docs

* fix pre commit

* only log in main process

* main logging

* try with local rank

* add tests

* change runner

* fix test

* dont push to hub in multi gpu tests

* pre download dataset in tests

* small fixes

* fix path optimizer state

* update docs, and small improvements in train

* simplify accelerate main process detection

* small improvements in train

* fix OOM bug

* change accelerate detection

* add some debugging

* always use accelerate

* cleanup update method

* cleanup

* fix bug

* scale lr decay if we reduce steps

* cleanup logging

* fix formatting

* encorperate feedback pr

* add min memory to cpu tests

* use accelerate to determin logging

* fix precommit and fix tests

* chore: minor details

---------

Co-authored-by: AdilZouitine <adilzouitinegm@gmail.com>
Co-authored-by: Steven Palma <steven.palma@huggingface.co>
2025-10-16 17:41:55 +02:00

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# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# This workflow handles nightly testing & docker images publishing.
name: Nightly
permissions:
contents: read
on:
# Allows running this workflow manually from the Actions tab
workflow_dispatch:
# Runs at 02:00
schedule:
- cron: "0 2 * * *"
# Sets up the environment variables
env:
UV_VERSION: "0.8.0"
PYTHON_VERSION: "3.10"
DOCKER_IMAGE_NAME_CPU: huggingface/lerobot-cpu:latest
DOCKER_IMAGE_NAME_GPU: huggingface/lerobot-gpu:latest
# Ensures that only the latest commit is built, canceling older runs.
concurrency:
group: ${{ github.workflow }}-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
# This job builds a CPU image for testing & distribution
build-docker-cpu-nightly:
name: Build CPU Docker for Nightly
runs-on:
group: aws-general-8-plus
outputs:
image_tag: ${{ env.DOCKER_IMAGE_NAME_CPU }}
steps:
- name: Install Git LFS
run: |
sudo apt-get update
sudo apt-get install git-lfs
git lfs install
- uses: actions/checkout@v4
with:
lfs: true
persist-credentials: false
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3 # zizmor: ignore[unpinned-uses]
with:
cache-binary: false
- name: Login to Docker Hub
uses: docker/login-action@v3 # zizmor: ignore[unpinned-uses]
with:
username: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
password: ${{ secrets.DOCKERHUB_LEROBOT_PASSWORD }}
- name: Build and push Docker image CPU
uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
with:
context: .
file: ./docker/Dockerfile.user
push: true
tags: ${{ env.DOCKER_IMAGE_NAME_CPU }}
# This job builds a GPU image for testing & distribution
build-docker-gpu-nightly:
name: Build GPU Docker for Nightly
runs-on:
group: aws-general-8-plus
outputs:
image_tag: ${{ env.DOCKER_IMAGE_NAME_GPU }}
steps:
- name: Install Git LFS
run: |
sudo apt-get update
sudo apt-get install git-lfs
git lfs install
- uses: actions/checkout@v4
with:
lfs: true
persist-credentials: false
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3 # zizmor: ignore[unpinned-uses]
with:
cache-binary: false
- name: Login to Docker Hub
uses: docker/login-action@v3 # zizmor: ignore[unpinned-uses]
with:
username: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
password: ${{ secrets.DOCKERHUB_LEROBOT_PASSWORD }}
- name: Build and push Docker image GPU
uses: docker/build-push-action@v6 # zizmor: ignore[unpinned-uses]
with:
context: .
file: ./docker/Dockerfile.internal
push: true
tags: ${{ env.DOCKER_IMAGE_NAME_GPU }}
# This job runs the E2E tests + pytest with all extras in the CPU image
nightly-cpu-tests:
name: Nightly CPU Tests
needs: [build-docker-cpu-nightly]
runs-on:
group: aws-g6-4xlarge-plus
env:
HF_HOME: /home/user_lerobot/.cache/huggingface
HF_LEROBOT_HOME: /home/user_lerobot/.cache/huggingface/lerobot
TORCH_HOME: /home/user_lerobot/.cache/torch
TRITON_CACHE_DIR: /home/user_lerobot/.cache/triton
container:
image: ${{ needs.build-docker-cpu-nightly.outputs.image_tag }} # zizmor: ignore[unpinned-images]
options: --shm-size "16gb"
credentials:
username: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
password: ${{ secrets.DOCKERHUB_LEROBOT_PASSWORD }}
defaults:
run:
shell: bash
working-directory: /lerobot
steps:
- name: Run pytest on CPU
run: pytest tests -vv --maxfail=10
- name: Run end-to-end tests
run: make test-end-to-end
# This job runs the E2E tests + pytest with all extras in the GPU image
nightly-gpu-tests:
name: Nightly GPU Tests
needs: [build-docker-gpu-nightly]
runs-on:
group: aws-g6-4xlarge-plus
env:
HF_HOME: /home/user_lerobot/.cache/huggingface
HF_LEROBOT_HOME: /home/user_lerobot/.cache/huggingface/lerobot
TORCH_HOME: /home/user_lerobot/.cache/torch
TRITON_CACHE_DIR: /home/user_lerobot/.cache/triton
container:
image: ${{ needs.build-docker-gpu-nightly.outputs.image_tag }} # zizmor: ignore[unpinned-images]
options: --gpus all --shm-size "16gb"
credentials:
username: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
password: ${{ secrets.DOCKERHUB_LEROBOT_PASSWORD }}
defaults:
run:
shell: bash
working-directory: /lerobot
steps:
- name: Run pytest on GPU
run: pytest tests -vv --maxfail=10
- name: Run end-to-end tests
run: make test-end-to-end
# This job runs multi-GPU training tests with 4 GPUs
nightly-multi-gpu-tests:
name: Nightly Multi-GPU Tests
needs: [build-docker-gpu-nightly]
runs-on:
group: aws-g4dn-12xlarge # Instance with 4 GPUs
env:
HF_HOME: /home/user_lerobot/.cache/huggingface
HF_LEROBOT_HOME: /home/user_lerobot/.cache/huggingface/lerobot
TORCH_HOME: /home/user_lerobot/.cache/torch
TRITON_CACHE_DIR: /home/user_lerobot/.cache/triton
CUDA_VISIBLE_DEVICES: "0,1,2,3"
container:
image: ${{ needs.build-docker-gpu-nightly.outputs.image_tag }} # zizmor: ignore[unpinned-images]
options: --gpus all --shm-size "16gb"
credentials:
username: ${{ secrets.DOCKERHUB_LEROBOT_USERNAME }}
password: ${{ secrets.DOCKERHUB_LEROBOT_PASSWORD }}
defaults:
run:
shell: bash
working-directory: /lerobot
steps:
- name: Verify GPU availability
run: |
nvidia-smi
python -c "import torch; print(f'PyTorch CUDA available: {torch.cuda.is_available()}'); print(f'Number of GPUs: {torch.cuda.device_count()}')"
- name: Run multi-GPU training tests
run: pytest tests/training/test_multi_gpu.py -vv --maxfail=3
timeout-minutes: 10