Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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64 行
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version: 2.0
jobs:
build:
docker:
- image: circleci/python:3.6.1
working_directory: ~/repo
steps:
- checkout
- restore_cache:
keys:
- v1-dependencies-{{ checksum "ml-agents/setup.py" }}
# fallback to using the latest cache if no exact match is found
- v1-dependencies-
- run:
name: Install Dependencies
command: |
python3 -m venv venv
. venv/bin/activate
pip install --upgrade pip
pip install --upgrade setuptools
cd ml-agents-envs && pip install -e .
cd ../ml-agents && pip install -e .
pip install pre-commit pytest-cov==2.6.1
cd ../gym-unity && pip install -e .
- save_cache:
paths:
- ./venv
key: v1-dependencies-{{ checksum "ml-agents/setup.py" }}
- run:
name: Run Tests for ml-agents and gym_unity
command: |
. venv/bin/activate
mkdir test-reports
pytest --cov=ml-agents --cov=ml-agents-envs --cov=gym-unity --cov-report html --junitxml=test-reports/junit.xml -p no:warnings
- run:
name: Check Code Style using pre-commit
command: |
. venv/bin/activate
pre-commit run --show-diff-on-failure --all-files
- run:
name: Verify there are no hidden/missing metafiles.
# Renaming files or deleting files can leave metafiles behind that makes Unity very unhappy.
command: |
. venv/bin/activate
python utils/validate_meta_files.py
- store_test_results:
path: test-reports
- store_artifacts:
path: test-reports
destination: test-reports
- store_artifacts:
path: htmlcov
destination: htmlcov