chore: import upstream snapshot with attribution
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---
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name: "🐛 Bug Report"
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about: Submit a bug report to help us improve MLC-LLM
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title: '[Bug] '
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labels: ['bug']
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assignees: ''
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---
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## 🐛 Bug
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<!-- A clear and concise description of what the bug is. -->
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## To Reproduce
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Steps to reproduce the behavior:
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1.
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1.
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1.
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<!-- If you have a code sample, error messages, stack traces, please provide it here as well -->
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## Expected behavior
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<!-- A clear and concise description of what you expected to happen. -->
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## Environment
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- Platform (e.g. WebGPU/Vulkan/IOS/Android/CUDA):
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- Operating system (e.g. Ubuntu/Windows/MacOS/...):
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- Device (e.g. iPhone 12 Pro, PC+RTX 3090, ...)
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- How you installed MLC-LLM (`conda`, source):
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- How you installed TVM (`pip`, source):
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- Python version (e.g. 3.10):
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- GPU driver version (if applicable):
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- CUDA/cuDNN version (if applicable):
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- TVM Hash Tag (`python -c "import tvm; print('\n'.join(f'{k}: {v}' for k, v in tvm.support.libinfo().items()))"`, applicable if you compile models):
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- Any other relevant information:
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## Additional context
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<!-- Add any other context about the problem here. -->
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blank_issues_enabled: false
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contact_links:
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- name: Check the MLC-LLM Documentation
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url: https://llm.mlc.ai/docs/
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about: Our documentation might provide answers to your questions.
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- name: Chat on Discord
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url: https://discord.gg/9Xpy2HGBuD
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about: Join the Discord Server to live chat with the community.
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@@ -0,0 +1,17 @@
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---
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name: "\U0001F4DA Documentation"
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about: Report an issue related to https://llm.mlc.ai/docs/
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title: '[Doc] '
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labels: ['documentation']
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assignees: ''
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---
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## 📚 Documentation
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### Suggestion
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<!-- Please leave your general suggestion to our documentation here. -->
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### Bug
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- Link to the buggy documentation/tutorial:
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- Description of the bug:
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@@ -0,0 +1,23 @@
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---
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name: "\U0001F680 Feature Request"
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about: Submit a proposal/request for a new MLC-LLM feature, or an enhancement on existing features.
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title: '[Feature Request] '
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labels: ['feature request']
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assignees: ''
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---
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## 🚀 Feature
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<!-- A brief description of the feature proposal -->
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## Motivation
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<!-- Please outline the motivation for the proposal, and how could this feature benefit the MLC-LLM project/community. -->
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## Alternatives
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<!-- A clear and concise description of any alternative solutions or features you've considered, if any. -->
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## Additional context
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<!-- Add any other context or screenshots about the feature request here. -->
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---
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name: "❓ General Questions"
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about: General questions you have about MLC-LLM.
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title: '[Question] '
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labels: ['question']
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assignees: ''
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---
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## ❓ General Questions
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<!-- Describe your questions -->
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---
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name: "️️⚙️ Model Request"
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about: Request a new model in MLC-LLM
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title: '[Model Request] '
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labels: ['new-models']
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assignees: ''
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---
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## ⚙️ Request New Models
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- Link to an existing implementation (e.g. Hugging Face/Github): <!-- Link to the model -->
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- Is this model architecture supported by MLC-LLM? (the list of [supported models](https://llm.mlc.ai/docs/prebuilt_models.html)) <!-- Yes/No -->
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## Additional context
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<!-- Add any other context that you think would be helpful for the community to add this model -->
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---
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name: " 🏎️ Speed Report"
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about: Submit a speed report of an model running in MLC-LLM
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title: '[Speed] '
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labels: ['performance']
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assignees: ''
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---
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# 🏎️ Speed Report
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<!-- Please search if there are existing issues discuss the speed of the model you are using, if there are, we encourage you reply in the existed issue instead of creating a new one. -->
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- The model code: <!-- e.g. vicuna-7b-1.1 -->
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- The model configuration (e.g. quantization mode, running data type, etc.):
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- Device (e.g. MacBook Pro M2, PC+RTX 3080):
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- OS (if applicable):
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- Encode speed (Token/s):
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- Decode speed (Token/s):
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- Memory usage (if applicable):
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<!-- Note that the measured speed might reflect peak performance if the prompt/chat history is short. -->
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---
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name: "Tracking"
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about: A tracking issue that tracks ongoing item in the project
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title: '[Tracking] '
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labels: ['status: tracking']
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assignees: ''
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---
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<!--
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A tracking issue contains a list of action items
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that can be executed to complete a feature or fix.
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We use tracking issues when we have a clear list of action items
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related to feature items as they provide fine-grained
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view of action items and provide clarity on what it takes to implement a feature.
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When to open a tracking issue: Open a new tracking issue when you have
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clear, actionable items (as a rule of thumb, make sure action items
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items can be carried through if you are assigned to work on it and
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you can provide enough guides to others who plan to work on these actions).
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-->
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## Overview
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<!-- A brief overview of the task -->
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## Action Items
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<!-- Please list set of action items to complete -->
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- [ ]
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## Links to Related Issues and PRs
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<!-- Cross link feature requests bug report issues related to the tracking item -->
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<!-- When there are new PRs, open up new PRs -->
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name: Build 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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jobs:
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test_linux:
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name: Deploy Docs
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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with:
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submodules: recursive
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- name: Configuring build Environment
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run: |
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sudo apt-get update
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python -m pip install -U pip wheel
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- name: Setup Ruby
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uses: ruby/setup-ruby@v1
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with:
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ruby-version: '3.0'
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- name: Installing dependencies
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run: |
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python -m pip install -r docs/requirements.txt
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gem install jekyll jekyll-remote-theme
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- name: Deploying on GitHub Pages
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if: github.ref == 'refs/heads/main'
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run: |
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git remote set-url origin https://x-access-token:${{ secrets.MLC_GITHUB_TOKEN }}@github.com/$GITHUB_REPOSITORY
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git config --global user.email "mlc-gh-actions-bot@nomail"
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git config --global user.name "mlc-gh-actions-bot"
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./scripts/gh_deploy_site.sh
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name: Lint
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on:
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push:
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branches: [main]
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pull_request:
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branches: [main]
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concurrency:
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group: Lint-${{ github.event.pull_request.number || github.sha }}
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cancel-in-progress: true
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jobs:
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lint:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
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with:
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fetch-depth: 0
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fetch-tags: true
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- name: Set up uv
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uses: astral-sh/setup-uv@b75a909f75acd358c2196fb9a5f1299a9a8868a4 # v6.7.0
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- name: Set up Python environment
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run: uv sync --group lint --no-install-project
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- uses: pre-commit/action@2c7b3805fd2a0fd8c1884dcaebf91fc102a13ecd # v3.0.1
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@@ -0,0 +1,32 @@
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name: 'Relax Submodule Sync'
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on:
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workflow_dispatch:
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jobs:
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sync:
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name: 'Relax Submodule Sync'
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runs-on: ubuntu-latest
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defaults:
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run:
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shell: bash
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steps:
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- name: Checkout
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uses: actions/checkout@v4
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with:
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submodules: true
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- name: Git Sumbodule Update
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run: |
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git submodule update --remote 3rdparty/tvm
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- name: Commit update
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env:
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GITHUB_TOKEN: ${{ secrets.MLC_GITHUB_TOKEN }}
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run: |
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git config --global user.name 'Git bot'
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git config --global user.email 'bot@noreply.github.com'
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git remote set-url origin https://$GITHUB_TOKEN@github.com/mlc-ai/mlc-llm
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git commit -am "Auto updated submodule references" && git push || echo "No changes to commit"
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# GH actions.
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# We use it to cover windows builds
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# Jenkins is still the primary CI
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name: Windows CI
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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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Windows:
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runs-on: windows-latest
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defaults:
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run:
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shell: 'cmd /C call {0}'
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steps:
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- name: Git config
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run: >-
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git config --system core.longpaths true
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- uses: actions/checkout@v3
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with:
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submodules: 'recursive'
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- uses: conda-incubator/setup-miniconda@v3
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with:
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activate-environment: mlc-llm-build
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channel-priority: strict
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environment-file: ci/build-environment.yaml
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auto-activate-base: false
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- name: Conda info
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run: |
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conda info
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conda list
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python --version
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# The wheel is built with scikit-build-core, which uses the Ninja
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# generator on Windows. Ninja needs cl.exe on PATH, so activate the MSVC
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# developer environment before building (otherwise CMake aborts with
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# "CMAKE_C_COMPILER not set, after EnableLanguage").
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- name: Set up MSVC developer environment
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uses: ilammy/msvc-dev-cmd@v1
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with:
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arch: x64
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- name: Build MLC-LLM
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run: >-
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ci/task/build_win.bat
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