mirror of https://github.com/coqui-ai/TTS.git
API tests (#2790)
* Separate API tests and only run when uplifted * Make style
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@ -0,0 +1,53 @@
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name: api_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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jobs:
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check_skip:
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runs-on: ubuntu-latest
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if: "! contains(github.event.head_commit.message, '[ci skip]')"
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steps:
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- run: echo "${{ github.event.head_commit.message }}"
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test:
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runs-on: ubuntu-latest
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strategy:
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fail-fast: false
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matrix:
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python-version: [3.9, "3.10", "3.11"]
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experimental: [false]
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steps:
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- uses: actions/checkout@v3
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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architecture: x64
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cache: 'pip'
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cache-dependency-path: 'requirements*'
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- name: check OS
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run: cat /etc/os-release
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- name: set ENV
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run: |
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export TRAINER_TELEMETRY=0
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- name: Install dependencies
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run: |
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sudo apt-get update
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sudo apt-get install -y --no-install-recommends git make gcc
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sudo apt-get install espeak-ng
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make system-deps
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- name: Install/upgrade Python setup deps
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run: python3 -m pip install --upgrade pip setuptools wheel
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- name: Replace scarf urls
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run: |
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sed -i 's/https:\/\/coqui.gateway.scarf.sh\//https:\/\/github.com\/coqui-ai\/TTS\/releases\/download\//g' TTS/.models.json
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- name: Install TTS
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run: |
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python3 -m pip install .[all]
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python3 setup.py egg_info
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- name: Unit tests
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run: make api_tests
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env:
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COQUI_STUDIO_TOKEN: ${{ secrets.COQUI_STUDIO_TOKEN }}
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@ -51,5 +51,3 @@ jobs:
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python3 setup.py egg_info
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- name: Unit tests
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run: make inference_tests
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env:
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COQUI_STUDIO_TOKEN: ${{ secrets.COQUI_STUDIO_TOKEN }}
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3
Makefile
3
Makefile
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@ -29,6 +29,9 @@ test_zoo: ## run zoo tests.
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inference_tests: ## run inference tests.
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nose2 -F -v -B --with-coverage --coverage TTS tests.inference_tests
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api_tests: ## run api tests.
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nose2 -F -v -B --with-coverage --coverage TTS tests.api_tests
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data_tests: ## run data tests.
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nose2 -F -v -B --with-coverage --coverage TTS tests.data_tests
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@ -136,7 +136,9 @@ def generate_voice(
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hubert_model = CustomHubert(checkpoint_path=model.config.LOCAL_MODEL_PATHS["hubert"]).to(model.device)
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# Load the CustomTokenizer model
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tokenizer = HubertTokenizer.load_from_checkpoint(model.config.LOCAL_MODEL_PATHS["hubert_tokenizer"], map_location=model.device)
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tokenizer = HubertTokenizer.load_from_checkpoint(
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model.config.LOCAL_MODEL_PATHS["hubert_tokenizer"], map_location=model.device
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)
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# semantic_tokens = model.text_to_semantic(
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# text, max_gen_duration_s=seconds, top_k=50, top_p=0.95, temp=0.7
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# ) # not 100%
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