From 325f77cdf1ee46abd1c5d8057805b5f6c5583cef Mon Sep 17 00:00:00 2001 From: keisuke-umezawa Date: Wed, 16 Aug 2023 21:57:39 +0900 Subject: [PATCH 1/7] Copy pr 534 --- .coveragerc | 3 ++ .github/workflows/python-coverage.yml | 42 +++++++++++++++++++++++++++ .github/workflows/python-tests.yml | 8 +++-- .gitignore | 5 ++++ pyproject.toml | 12 ++++++++ 5 files changed, 67 insertions(+), 3 deletions(-) create mode 100644 .coveragerc create mode 100644 .github/workflows/python-coverage.yml diff --git a/.coveragerc b/.coveragerc new file mode 100644 index 00000000..26e44f99 --- /dev/null +++ b/.coveragerc @@ -0,0 +1,3 @@ +[run] +concurrency = multiprocessing,thread +source = optuna_dashboard/ diff --git a/.github/workflows/python-coverage.yml b/.github/workflows/python-coverage.yml new file mode 100644 index 00000000..d1d5d849 --- /dev/null +++ b/.github/workflows/python-coverage.yml @@ -0,0 +1,42 @@ +me: python coverage + +on: + push: + branches: + - master + pull_request: {} + +jobs: + coverage: + runs-on: ubuntu-latest + steps: + - name: Checkout + uses: actions/checkout@v3 + + - name: Setup Python + uses: actions/setup-python@v4 + with: + python-version: '3.10' + architecture: x64 + + - name: Install dependencies + run: | + python -m pip install --progress-bar off --upgrade pip setuptools + pip install --progress-bar off .[optional] + pip install --progress-bar off .[test] + pip install --progress-bar off "optuna>=3.0.0" + pip install --progress-bar off . + echo 'import coverage; coverage.process_startup()' > sitecustomize.py + - name: Tests + env: + PYTHONPATH: . # To invoke sitecutomize.py + COVERAGE_PROCESS_START: .coveragerc # https://coverage.readthedocs.io/en/6.4.1/subprocess.html + COVERAGE_COVERAGE: yes # https://github.com/nedbat/coveragepy/blob/65bf33fc03209ffb01bbbc0d900017614645ee7a/coverage/control.py#L255-L261 + run: | + coverage run --source=optuna_dashboard -m pytest python_tests + coverage combine + coverage xml + - name: Upload coverage to Codecov + uses: codecov/codecov-action@v3 + with: + file: ./coverage.xml diff --git a/.github/workflows/python-tests.yml b/.github/workflows/python-tests.yml index 612ddb59..26cb4b8b 100644 --- a/.github/workflows/python-tests.yml +++ b/.github/workflows/python-tests.yml @@ -1,4 +1,4 @@ -name: tests +me: tests on: pull_request: branches: @@ -45,7 +45,8 @@ jobs: # python_tests requires optuna>=3.0.0 since it imports FloatDistribution run: | python -m pip install --progress-bar off --upgrade pip setuptools - pip install streamlit boto3 moto[s3] pytest + pip install --progress-bar off .[optional] + pip install --progress-bar off .[test] pip install --progress-bar off "optuna>=3.0.0" pip install --progress-bar off . - run: pytest python_tests @@ -61,7 +62,8 @@ jobs: - name: Install dependencies run: | python -m pip install --progress-bar off --upgrade pip setuptools - pip install streamlit boto3 moto[s3] pytest + pip install --progress-bar off .[optional] + pip install --progress-bar off .[test] pip install --progress-bar off . python -m pip install --progress-bar off --upgrade git+https://github.com/optuna/optuna.git - run: pytest python_tests diff --git a/.gitignore b/.gitignore index dde468fc..d530dc27 100644 --- a/.gitignore +++ b/.gitignore @@ -28,6 +28,11 @@ docs/_generated/ rustlib/target/ rustlib/pkg/ +# Test +.coverage +.coverage.* +coverage.xml + # Others .envrc .idea/ diff --git a/pyproject.toml b/pyproject.toml index d9c0082c..2b4913db 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -33,6 +33,18 @@ dependencies = [ ] dynamic = ["version"] +[project.optional-dependencies] +test = [ + "coverage", + "pytest", + "moto[s3]", +] + +optional = [ + "streamlit", + "boto3", +] + [project.optional-dependencies] docs = [ "boto3", From 7140888553acd4d6e765d06449d7750edb7c9ee2 Mon Sep 17 00:00:00 2001 From: keisuke-umezawa Date: Wed, 16 Aug 2023 22:47:26 +0900 Subject: [PATCH 2/7] Fix typo --- .github/workflows/python-coverage.yml | 2 +- .github/workflows/python-tests.yml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/workflows/python-coverage.yml b/.github/workflows/python-coverage.yml index d1d5d849..a2e61bef 100644 --- a/.github/workflows/python-coverage.yml +++ b/.github/workflows/python-coverage.yml @@ -1,4 +1,4 @@ -me: python coverage +name: python coverage on: push: diff --git a/.github/workflows/python-tests.yml b/.github/workflows/python-tests.yml index 26cb4b8b..8fee4e44 100644 --- a/.github/workflows/python-tests.yml +++ b/.github/workflows/python-tests.yml @@ -1,4 +1,4 @@ -me: tests +name: tests on: pull_request: branches: From 54d4b51de8c57d0eb88febc1a4c1fccdde76de68 Mon Sep 17 00:00:00 2001 From: keisuke-umezawa Date: Wed, 16 Aug 2023 22:54:32 +0900 Subject: [PATCH 3/7] Fix error --- pyproject.toml | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 2b4913db..0555f701 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -34,6 +34,13 @@ dependencies = [ dynamic = ["version"] [project.optional-dependencies] +docs = [ + "boto3", + "streamlit", + "sphinx", + "sphinx_rtd_theme", +] + test = [ "coverage", "pytest", @@ -45,13 +52,6 @@ optional = [ "boto3", ] -[project.optional-dependencies] -docs = [ - "boto3", - "streamlit", - "sphinx", - "sphinx_rtd_theme", -] [project.scripts] optuna-dashboard = "optuna_dashboard._cli:main" From 4905890414aa9ecdc7a0a10e8d48601a9900adc8 Mon Sep 17 00:00:00 2001 From: keisuke-umezawa Date: Sun, 20 Aug 2023 16:16:31 +0900 Subject: [PATCH 4/7] Devide test db in e2e tests --- Makefile | 2 +- e2e_tests/__init__.py | 0 e2e_tests/conftest.py | 245 ------------------ e2e_tests/mock_db.py | 35 +++ e2e_tests/test_usecases/__init__.py | 0 e2e_tests/test_usecases/test_study_history.py | 30 +++ e2e_tests/visual_regression_test.py | 220 ++++++++++++++++ 7 files changed, 286 insertions(+), 246 deletions(-) create mode 100644 e2e_tests/__init__.py create mode 100644 e2e_tests/mock_db.py create mode 100644 e2e_tests/test_usecases/__init__.py diff --git a/Makefile b/Makefile index f925bb78..4094fd57 100644 --- a/Makefile +++ b/Makefile @@ -45,7 +45,7 @@ docs: docs/conf.py $(RST_FILES) .PHONY: fmt fmt: npm run fmt - black ./optuna_dashboard/ ./python_tests/ + black ./optuna_dashboard/ ./python_tests/ ./e2e_tests/ isort . .PHONY: clean diff --git a/e2e_tests/__init__.py b/e2e_tests/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/e2e_tests/conftest.py b/e2e_tests/conftest.py index 8d8eac3b..ad1190cb 100644 --- a/e2e_tests/conftest.py +++ b/e2e_tests/conftest.py @@ -1,251 +1,6 @@ -import socket -import threading -from wsgiref.simple_server import make_server - -import optuna -from optuna_dashboard import wsgi import pytest -study_names = [ - "single", - "single-trial", - "single-1-param", - "single-dynamic", - "single-inf", - "multi-objective", - "multi-dynamic", - "single-pruned-without-report", - "single-inf-report", - "issue-410", - "single-no-trials", - "multi-no-trials", -] - - -def make_dummy_storage(study_name: str) -> optuna.storages.InMemoryStorage: - storage = optuna.storages.InMemoryStorage() - sampler = optuna.samplers.RandomSampler(seed=0) - - # Sinble objective study - if study_name == "single": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_single(trial: optuna.Trial) -> float: - x1 = trial.suggest_float("x1", 0, 10) - x2 = trial.suggest_float("x2", 0, 10) - return (x1 - 2) ** 2 + (x2 - 5) ** 2 - - study.optimize(objective_single, n_trials=50) - - # A single objective study with a single trial - # Refs: https://github.com/optuna/optuna-dashboard/issues/401 - elif study_name == "single-trial": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_single(trial: optuna.Trial) -> float: - x1 = trial.suggest_float("x1", 0, 10) - x2 = trial.suggest_float("x2", 0, 10) - return (x1 - 2) ** 2 + (x2 - 5) ** 2 - - study.optimize(objective_single, n_trials=1) - - # Single-objective study with 1 parameter - elif study_name == "single-1-param": - study = optuna.create_study( - study_name=study_name, storage=storage, direction="maximize", sampler=sampler - ) - - def objective_single_with_1param(trial: optuna.Trial) -> float: - x1 = trial.suggest_float("x1", 0, 10) - return -((x1 - 2) ** 2) - - study.optimize(objective_single_with_1param, n_trials=50) - - # Single-objective study with dynamic search space - elif study_name == "single-dynamic": - study = optuna.create_study( - study_name=study_name, storage=storage, direction="maximize", sampler=sampler - ) - - def objective_single_dynamic(trial: optuna.Trial) -> float: - category = trial.suggest_categorical("category", ["foo", "bar"]) - if category == "foo": - return (trial.suggest_float("x1", 0, 10) - 2) ** 2 - else: - return -((trial.suggest_float("x2", -10, 0) + 5) ** 2) - - study.optimize(objective_single_dynamic, n_trials=50) - - # Single objective study with 'inf', '-inf', or 'nan' value - elif study_name == "single-inf": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_single_inf(trial: optuna.Trial) -> float: - x = trial.suggest_float("x", -10, 10) - if trial.number % 3 == 0: - return float("inf") - elif trial.number % 3 == 1: - return float("-inf") - else: - return x**2 - - study.optimize(objective_single_inf, n_trials=50) - - # Multi-objective study - elif study_name == "multi-objective": - study = optuna.create_study( - study_name=study_name, - storage=storage, - directions=["minimize", "minimize"], - sampler=sampler, - ) - - def objective_multi(trial: optuna.Trial) -> tuple[float, float]: - x = trial.suggest_float("x", 0, 5) - y = trial.suggest_float("y", 0, 3) - v0 = 4 * x**2 + 4 * y**2 - v1 = (x - 5) ** 2 + (y - 5) ** 2 - return v0, v1 - - study.optimize(objective_multi, n_trials=50) - - # Multi-objective study with dynamic search space - elif study_name == "multi-dynamic": - study = optuna.create_study( - study_name=study_name, - storage=storage, - directions=["minimize", "minimize"], - sampler=sampler, - ) - - def objective_multi_dynamic(trial: optuna.Trial) -> tuple[float, float]: - category = trial.suggest_categorical("category", ["foo", "bar"]) - if category == "foo": - x = trial.suggest_float("x1", 0, 5) - y = trial.suggest_float("y1", 0, 3) - v0 = 4 * x**2 + 4 * y**2 - v1 = (x - 5) ** 2 + (y - 5) ** 2 - return v0, v1 - else: - x = trial.suggest_float("x2", 0, 5) - y = trial.suggest_float("y2", 0, 3) - v0 = 2 * x**2 + 2 * y**2 - v1 = (x - 2) ** 2 + (y - 3) ** 2 - return v0, v1 - - study.optimize(objective_multi_dynamic, n_trials=50) - - # Pruning with no intermediate values - elif study_name == "single-pruned-without-report": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_prune_without_report(trial: optuna.Trial) -> float: - x = trial.suggest_float("x", -15, 30) - y = trial.suggest_float("y", -15, 30) - v = x**2 + y**2 - if v > 100: - raise optuna.TrialPruned() - return v - - study.optimize(objective_prune_without_report, n_trials=100) - - # Single objective pruned after reported 'inf', '-inf', or 'nan' - elif study_name == "single-inf-report": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_single_inf_report(trial: optuna.Trial) -> float: - x = trial.suggest_float("x", -10, 10) - if trial.number % 3 == 0: - trial.report(float("inf"), 1) - elif trial.number % 3 == 1: - trial.report(float("-inf"), 1) - else: - trial.report(float("nan"), 1) - - if x > 0: - raise optuna.TrialPruned() - else: - return x**2 - - study.optimize(objective_single_inf_report, n_trials=50) - - # Issue 410 - elif study_name == "issue-410": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_issue_410(trial: optuna.Trial) -> float: - trial.suggest_categorical("resample_rate", ["50ms"]) - trial.suggest_categorical("channels", ["all"]) - trial.suggest_categorical("window_size", [256]) - if trial.number > 15: - raise Exception("Unexpected error") - trial.suggest_categorical("cbow", [True]) - trial.suggest_categorical("model", ["m1"]) - - trial.set_user_attr("epochs", 0) - trial.set_user_attr("deterministic", True) - if trial.number > 10: - raise Exception("unexpeccted error") - trial.set_user_attr("folder", "/path/to/folder") - trial.set_user_attr("resample_type", "foo") - trial.set_user_attr("run_id", "0001") - return 1.0 - - study.optimize(objective_issue_410, n_trials=20, catch=(Exception,)) - - # No trials single-objective study - elif study_name == "single-no-trials": - optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - # No trials multi-objective study - elif study_name == "multi-no-trials": - optuna.create_study( - study_name=study_name, - storage=storage, - directions=["minimize", "maximize"], - sampler=sampler, - ) - else: - assert False, f"No study configuration of {study_name} in conftest.py" - - return storage - - -def get_free_port() -> int: - tcp = socket.socket(socket.AF_INET, socket.SOCK_STREAM) - tcp.bind(("", 0)) - _, port = tcp.getsockname() - tcp.close() - return port - - -@pytest.fixture(scope="session", params=study_names) -def storage(request: pytest.FixtureRequest) -> optuna.storages.InMemoryStorage: - study_name = request.param - storage = make_dummy_storage(study_name) - return storage - - -@pytest.fixture(scope="session") -def server_url(request: pytest.FixtureRequest, storage: optuna.storages.InMemoryStorage) -> str: - addr = "127.0.0.1" - port = get_free_port() - app = wsgi(storage) - httpd = make_server(addr, port, app) - thread = threading.Thread(target=httpd.serve_forever) - thread.start() - - def stop_server() -> None: - httpd.shutdown() - httpd.server_close() - thread.join() - - request.addfinalizer(stop_server) - - return f"http://{addr}:{port}/dashboard" - - @pytest.fixture(scope="session") def browser_context_args(browser_context_args: dict) -> dict: return { diff --git a/e2e_tests/mock_db.py b/e2e_tests/mock_db.py new file mode 100644 index 00000000..b6d14734 --- /dev/null +++ b/e2e_tests/mock_db.py @@ -0,0 +1,35 @@ +import socket +import threading +from wsgiref.simple_server import make_server + +import optuna +from optuna_dashboard import wsgi +import pytest + + +def get_free_port() -> int: + tcp = socket.socket(socket.AF_INET, socket.SOCK_STREAM) + tcp.bind(("", 0)) + _, port = tcp.getsockname() + tcp.close() + return port + + +def make_test_server( + request: pytest.FixtureRequest, storage: optuna.storages.InMemoryStorage +) -> str: + addr = "127.0.0.1" + port = get_free_port() + app = wsgi(storage) + httpd = make_server(addr, port, app) + thread = threading.Thread(target=httpd.serve_forever) + thread.start() + + def stop_server() -> None: + httpd.shutdown() + httpd.server_close() + thread.join() + + request.addfinalizer(stop_server) + + return f"http://{addr}:{port}/dashboard" diff --git a/e2e_tests/test_usecases/__init__.py b/e2e_tests/test_usecases/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/e2e_tests/test_usecases/test_study_history.py b/e2e_tests/test_usecases/test_study_history.py index f34d35e6..aef0fa1b 100644 --- a/e2e_tests/test_usecases/test_study_history.py +++ b/e2e_tests/test_usecases/test_study_history.py @@ -1,5 +1,35 @@ import optuna from playwright.sync_api import Page +import pytest + +from ..mock_db import make_test_server + + +def make_dummy_storage() -> optuna.storages.InMemoryStorage: + storage = optuna.storages.InMemoryStorage() + sampler = optuna.samplers.RandomSampler(seed=0) + + study = optuna.create_study(study_name="single", storage=storage, sampler=sampler) + + def objective_single(trial: optuna.Trial) -> float: + x1 = trial.suggest_float("x1", 0, 10) + x2 = trial.suggest_float("x2", 0, 10) + return (x1 - 2) ** 2 + (x2 - 5) ** 2 + + study.optimize(objective_single, n_trials=50) + + return storage + + +@pytest.fixture +def storage() -> optuna.storages.InMemoryStorage: + storage = make_dummy_storage() + return storage + + +@pytest.fixture +def server_url(request: pytest.FixtureRequest, storage: optuna.storages.InMemoryStorage) -> str: + return make_test_server(request, storage) def test_history_xaxis_click( diff --git a/e2e_tests/visual_regression_test.py b/e2e_tests/visual_regression_test.py index 706ec2f3..568ebab3 100644 --- a/e2e_tests/visual_regression_test.py +++ b/e2e_tests/visual_regression_test.py @@ -1,5 +1,225 @@ import optuna from playwright.sync_api import Page +import pytest + +from .mock_db import make_test_server + + +study_names = [ + "single", + "single-trial", + "single-1-param", + "single-dynamic", + "single-inf", + "multi-objective", + "multi-dynamic", + "single-pruned-without-report", + "single-inf-report", + "issue-410", + "single-no-trials", + "multi-no-trials", +] + + +def make_dummy_storage(study_name: str) -> optuna.storages.InMemoryStorage: + storage = optuna.storages.InMemoryStorage() + sampler = optuna.samplers.RandomSampler(seed=0) + + # Sinble objective study + if study_name == "single": + study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) + + def objective_single(trial: optuna.Trial) -> float: + x1 = trial.suggest_float("x1", 0, 10) + x2 = trial.suggest_float("x2", 0, 10) + return (x1 - 2) ** 2 + (x2 - 5) ** 2 + + study.optimize(objective_single, n_trials=50) + + # A single objective study with a single trial + # Refs: https://github.com/optuna/optuna-dashboard/issues/401 + elif study_name == "single-trial": + study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) + + def objective_single(trial: optuna.Trial) -> float: + x1 = trial.suggest_float("x1", 0, 10) + x2 = trial.suggest_float("x2", 0, 10) + return (x1 - 2) ** 2 + (x2 - 5) ** 2 + + study.optimize(objective_single, n_trials=1) + + # Single-objective study with 1 parameter + elif study_name == "single-1-param": + study = optuna.create_study( + study_name=study_name, storage=storage, direction="maximize", sampler=sampler + ) + + def objective_single_with_1param(trial: optuna.Trial) -> float: + x1 = trial.suggest_float("x1", 0, 10) + return -((x1 - 2) ** 2) + + study.optimize(objective_single_with_1param, n_trials=50) + + # Single-objective study with dynamic search space + elif study_name == "single-dynamic": + study = optuna.create_study( + study_name=study_name, storage=storage, direction="maximize", sampler=sampler + ) + + def objective_single_dynamic(trial: optuna.Trial) -> float: + category = trial.suggest_categorical("category", ["foo", "bar"]) + if category == "foo": + return (trial.suggest_float("x1", 0, 10) - 2) ** 2 + else: + return -((trial.suggest_float("x2", -10, 0) + 5) ** 2) + + study.optimize(objective_single_dynamic, n_trials=50) + + # Single objective study with 'inf', '-inf', or 'nan' value + elif study_name == "single-inf": + study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) + + def objective_single_inf(trial: optuna.Trial) -> float: + x = trial.suggest_float("x", -10, 10) + if trial.number % 3 == 0: + return float("inf") + elif trial.number % 3 == 1: + return float("-inf") + else: + return x**2 + + study.optimize(objective_single_inf, n_trials=50) + + # Multi-objective study + elif study_name == "multi-objective": + study = optuna.create_study( + study_name=study_name, + storage=storage, + directions=["minimize", "minimize"], + sampler=sampler, + ) + + def objective_multi(trial: optuna.Trial) -> tuple[float, float]: + x = trial.suggest_float("x", 0, 5) + y = trial.suggest_float("y", 0, 3) + v0 = 4 * x**2 + 4 * y**2 + v1 = (x - 5) ** 2 + (y - 5) ** 2 + return v0, v1 + + study.optimize(objective_multi, n_trials=50) + + # Multi-objective study with dynamic search space + elif study_name == "multi-dynamic": + study = optuna.create_study( + study_name=study_name, + storage=storage, + directions=["minimize", "minimize"], + sampler=sampler, + ) + + def objective_multi_dynamic(trial: optuna.Trial) -> tuple[float, float]: + category = trial.suggest_categorical("category", ["foo", "bar"]) + if category == "foo": + x = trial.suggest_float("x1", 0, 5) + y = trial.suggest_float("y1", 0, 3) + v0 = 4 * x**2 + 4 * y**2 + v1 = (x - 5) ** 2 + (y - 5) ** 2 + return v0, v1 + else: + x = trial.suggest_float("x2", 0, 5) + y = trial.suggest_float("y2", 0, 3) + v0 = 2 * x**2 + 2 * y**2 + v1 = (x - 2) ** 2 + (y - 3) ** 2 + return v0, v1 + + study.optimize(objective_multi_dynamic, n_trials=50) + + # Pruning with no intermediate values + elif study_name == "single-pruned-without-report": + study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) + + def objective_prune_without_report(trial: optuna.Trial) -> float: + x = trial.suggest_float("x", -15, 30) + y = trial.suggest_float("y", -15, 30) + v = x**2 + y**2 + if v > 100: + raise optuna.TrialPruned() + return v + + study.optimize(objective_prune_without_report, n_trials=100) + + # Single objective pruned after reported 'inf', '-inf', or 'nan' + elif study_name == "single-inf-report": + study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) + + def objective_single_inf_report(trial: optuna.Trial) -> float: + x = trial.suggest_float("x", -10, 10) + if trial.number % 3 == 0: + trial.report(float("inf"), 1) + elif trial.number % 3 == 1: + trial.report(float("-inf"), 1) + else: + trial.report(float("nan"), 1) + + if x > 0: + raise optuna.TrialPruned() + else: + return x**2 + + study.optimize(objective_single_inf_report, n_trials=50) + + # Issue 410 + elif study_name == "issue-410": + study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) + + def objective_issue_410(trial: optuna.Trial) -> float: + trial.suggest_categorical("resample_rate", ["50ms"]) + trial.suggest_categorical("channels", ["all"]) + trial.suggest_categorical("window_size", [256]) + if trial.number > 15: + raise Exception("Unexpected error") + trial.suggest_categorical("cbow", [True]) + trial.suggest_categorical("model", ["m1"]) + + trial.set_user_attr("epochs", 0) + trial.set_user_attr("deterministic", True) + if trial.number > 10: + raise Exception("unexpeccted error") + trial.set_user_attr("folder", "/path/to/folder") + trial.set_user_attr("resample_type", "foo") + trial.set_user_attr("run_id", "0001") + return 1.0 + + study.optimize(objective_issue_410, n_trials=20, catch=(Exception,)) + + # No trials single-objective study + elif study_name == "single-no-trials": + optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) + + # No trials multi-objective study + elif study_name == "multi-no-trials": + optuna.create_study( + study_name=study_name, + storage=storage, + directions=["minimize", "maximize"], + sampler=sampler, + ) + else: + assert False, f"No study configuration of {study_name} in conftest.py" + + return storage + + +@pytest.fixture(params=study_names) +def storage(request: pytest.FixtureRequest) -> optuna.storages.InMemoryStorage: + study_name = request.param + storage = make_dummy_storage(study_name) + return storage + + +@pytest.fixture(params=study_names) +def server_url(request: pytest.FixtureRequest, storage: optuna.storages.InMemoryStorage) -> str: + return make_test_server(request, storage) def test_study_list( From 9296fc2bbeaa7c1dad0f11d6d706b3cb27f2f9a6 Mon Sep 17 00:00:00 2001 From: keisuke-umezawa Date: Sun, 20 Aug 2023 16:29:53 +0900 Subject: [PATCH 5/7] Rename some functions --- e2e_tests/{mock_db.py => test_server.py} | 0 e2e_tests/test_usecases/test_study_history.py | 6 +++--- e2e_tests/visual_regression_test.py | 6 +++--- 3 files changed, 6 insertions(+), 6 deletions(-) rename e2e_tests/{mock_db.py => test_server.py} (100%) diff --git a/e2e_tests/mock_db.py b/e2e_tests/test_server.py similarity index 100% rename from e2e_tests/mock_db.py rename to e2e_tests/test_server.py diff --git a/e2e_tests/test_usecases/test_study_history.py b/e2e_tests/test_usecases/test_study_history.py index aef0fa1b..e37b8f5a 100644 --- a/e2e_tests/test_usecases/test_study_history.py +++ b/e2e_tests/test_usecases/test_study_history.py @@ -2,10 +2,10 @@ import optuna from playwright.sync_api import Page import pytest -from ..mock_db import make_test_server +from ..test_server import make_test_server -def make_dummy_storage() -> optuna.storages.InMemoryStorage: +def make_test_storage() -> optuna.storages.InMemoryStorage: storage = optuna.storages.InMemoryStorage() sampler = optuna.samplers.RandomSampler(seed=0) @@ -23,7 +23,7 @@ def make_dummy_storage() -> optuna.storages.InMemoryStorage: @pytest.fixture def storage() -> optuna.storages.InMemoryStorage: - storage = make_dummy_storage() + storage = make_test_storage() return storage diff --git a/e2e_tests/visual_regression_test.py b/e2e_tests/visual_regression_test.py index 568ebab3..0ffd448b 100644 --- a/e2e_tests/visual_regression_test.py +++ b/e2e_tests/visual_regression_test.py @@ -2,7 +2,7 @@ import optuna from playwright.sync_api import Page import pytest -from .mock_db import make_test_server +from .test_server import make_test_server study_names = [ @@ -21,7 +21,7 @@ study_names = [ ] -def make_dummy_storage(study_name: str) -> optuna.storages.InMemoryStorage: +def make_test_storage(study_name: str) -> optuna.storages.InMemoryStorage: storage = optuna.storages.InMemoryStorage() sampler = optuna.samplers.RandomSampler(seed=0) @@ -213,7 +213,7 @@ def make_dummy_storage(study_name: str) -> optuna.storages.InMemoryStorage: @pytest.fixture(params=study_names) def storage(request: pytest.FixtureRequest) -> optuna.storages.InMemoryStorage: study_name = request.param - storage = make_dummy_storage(study_name) + storage = make_test_storage(study_name) return storage From 3aba421d63a731f6f0020a27192ecea3379a25c6 Mon Sep 17 00:00:00 2001 From: keisuke-umezawa Date: Wed, 30 Aug 2023 22:05:17 +0900 Subject: [PATCH 6/7] Add codecov token --- .github/workflows/python-coverage.yml | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/.github/workflows/python-coverage.yml b/.github/workflows/python-coverage.yml index a2e61bef..4bda6350 100644 --- a/.github/workflows/python-coverage.yml +++ b/.github/workflows/python-coverage.yml @@ -9,6 +9,10 @@ on: jobs: coverage: runs-on: ubuntu-latest + + # Not intended for forks. + if: github.repository == 'optuna/optuna-dashboard' + steps: - name: Checkout uses: actions/checkout@v3 @@ -39,4 +43,6 @@ jobs: - name: Upload coverage to Codecov uses: codecov/codecov-action@v3 with: + token: ${{ secrets.CODECOV_TOKEN }} file: ./coverage.xml + fail_ci_if_error: true From 0a3987f811d66b76188ad3587d25042b056fce21 Mon Sep 17 00:00:00 2001 From: keisuke-umezawa Date: Sun, 3 Sep 2023 15:28:39 +0900 Subject: [PATCH 7/7] Follow review comments --- e2e_tests/visual_regression_test.py | 499 +++++++++++++++------------- 1 file changed, 275 insertions(+), 224 deletions(-) diff --git a/e2e_tests/visual_regression_test.py b/e2e_tests/visual_regression_test.py index 0ffd448b..d83fbb5f 100644 --- a/e2e_tests/visual_regression_test.py +++ b/e2e_tests/visual_regression_test.py @@ -1,3 +1,5 @@ +from typing import Callable + import optuna from playwright.sync_api import Page import pytest @@ -5,231 +7,268 @@ import pytest from .test_server import make_test_server -study_names = [ - "single", - "single-trial", - "single-1-param", - "single-dynamic", - "single-inf", - "multi-objective", - "multi-dynamic", - "single-pruned-without-report", - "single-inf-report", - "issue-410", - "single-no-trials", - "multi-no-trials", -] - - -def make_test_storage(study_name: str) -> optuna.storages.InMemoryStorage: +@pytest.fixture +def storage() -> optuna.storages.InMemoryStorage: storage = optuna.storages.InMemoryStorage() - sampler = optuna.samplers.RandomSampler(seed=0) - - # Sinble objective study - if study_name == "single": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_single(trial: optuna.Trial) -> float: - x1 = trial.suggest_float("x1", 0, 10) - x2 = trial.suggest_float("x2", 0, 10) - return (x1 - 2) ** 2 + (x2 - 5) ** 2 - - study.optimize(objective_single, n_trials=50) - - # A single objective study with a single trial - # Refs: https://github.com/optuna/optuna-dashboard/issues/401 - elif study_name == "single-trial": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_single(trial: optuna.Trial) -> float: - x1 = trial.suggest_float("x1", 0, 10) - x2 = trial.suggest_float("x2", 0, 10) - return (x1 - 2) ** 2 + (x2 - 5) ** 2 - - study.optimize(objective_single, n_trials=1) - - # Single-objective study with 1 parameter - elif study_name == "single-1-param": - study = optuna.create_study( - study_name=study_name, storage=storage, direction="maximize", sampler=sampler - ) - - def objective_single_with_1param(trial: optuna.Trial) -> float: - x1 = trial.suggest_float("x1", 0, 10) - return -((x1 - 2) ** 2) - - study.optimize(objective_single_with_1param, n_trials=50) - - # Single-objective study with dynamic search space - elif study_name == "single-dynamic": - study = optuna.create_study( - study_name=study_name, storage=storage, direction="maximize", sampler=sampler - ) - - def objective_single_dynamic(trial: optuna.Trial) -> float: - category = trial.suggest_categorical("category", ["foo", "bar"]) - if category == "foo": - return (trial.suggest_float("x1", 0, 10) - 2) ** 2 - else: - return -((trial.suggest_float("x2", -10, 0) + 5) ** 2) - - study.optimize(objective_single_dynamic, n_trials=50) - - # Single objective study with 'inf', '-inf', or 'nan' value - elif study_name == "single-inf": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_single_inf(trial: optuna.Trial) -> float: - x = trial.suggest_float("x", -10, 10) - if trial.number % 3 == 0: - return float("inf") - elif trial.number % 3 == 1: - return float("-inf") - else: - return x**2 - - study.optimize(objective_single_inf, n_trials=50) - - # Multi-objective study - elif study_name == "multi-objective": - study = optuna.create_study( - study_name=study_name, - storage=storage, - directions=["minimize", "minimize"], - sampler=sampler, - ) - - def objective_multi(trial: optuna.Trial) -> tuple[float, float]: - x = trial.suggest_float("x", 0, 5) - y = trial.suggest_float("y", 0, 3) - v0 = 4 * x**2 + 4 * y**2 - v1 = (x - 5) ** 2 + (y - 5) ** 2 - return v0, v1 - - study.optimize(objective_multi, n_trials=50) - - # Multi-objective study with dynamic search space - elif study_name == "multi-dynamic": - study = optuna.create_study( - study_name=study_name, - storage=storage, - directions=["minimize", "minimize"], - sampler=sampler, - ) - - def objective_multi_dynamic(trial: optuna.Trial) -> tuple[float, float]: - category = trial.suggest_categorical("category", ["foo", "bar"]) - if category == "foo": - x = trial.suggest_float("x1", 0, 5) - y = trial.suggest_float("y1", 0, 3) - v0 = 4 * x**2 + 4 * y**2 - v1 = (x - 5) ** 2 + (y - 5) ** 2 - return v0, v1 - else: - x = trial.suggest_float("x2", 0, 5) - y = trial.suggest_float("y2", 0, 3) - v0 = 2 * x**2 + 2 * y**2 - v1 = (x - 2) ** 2 + (y - 3) ** 2 - return v0, v1 - - study.optimize(objective_multi_dynamic, n_trials=50) - - # Pruning with no intermediate values - elif study_name == "single-pruned-without-report": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_prune_without_report(trial: optuna.Trial) -> float: - x = trial.suggest_float("x", -15, 30) - y = trial.suggest_float("y", -15, 30) - v = x**2 + y**2 - if v > 100: - raise optuna.TrialPruned() - return v - - study.optimize(objective_prune_without_report, n_trials=100) - - # Single objective pruned after reported 'inf', '-inf', or 'nan' - elif study_name == "single-inf-report": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_single_inf_report(trial: optuna.Trial) -> float: - x = trial.suggest_float("x", -10, 10) - if trial.number % 3 == 0: - trial.report(float("inf"), 1) - elif trial.number % 3 == 1: - trial.report(float("-inf"), 1) - else: - trial.report(float("nan"), 1) - - if x > 0: - raise optuna.TrialPruned() - else: - return x**2 - - study.optimize(objective_single_inf_report, n_trials=50) - - # Issue 410 - elif study_name == "issue-410": - study = optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - def objective_issue_410(trial: optuna.Trial) -> float: - trial.suggest_categorical("resample_rate", ["50ms"]) - trial.suggest_categorical("channels", ["all"]) - trial.suggest_categorical("window_size", [256]) - if trial.number > 15: - raise Exception("Unexpected error") - trial.suggest_categorical("cbow", [True]) - trial.suggest_categorical("model", ["m1"]) - - trial.set_user_attr("epochs", 0) - trial.set_user_attr("deterministic", True) - if trial.number > 10: - raise Exception("unexpeccted error") - trial.set_user_attr("folder", "/path/to/folder") - trial.set_user_attr("resample_type", "foo") - trial.set_user_attr("run_id", "0001") - return 1.0 - - study.optimize(objective_issue_410, n_trials=20, catch=(Exception,)) - - # No trials single-objective study - elif study_name == "single-no-trials": - optuna.create_study(study_name=study_name, storage=storage, sampler=sampler) - - # No trials multi-objective study - elif study_name == "multi-no-trials": - optuna.create_study( - study_name=study_name, - storage=storage, - directions=["minimize", "maximize"], - sampler=sampler, - ) - else: - assert False, f"No study configuration of {study_name} in conftest.py" - return storage -@pytest.fixture(params=study_names) -def storage(request: pytest.FixtureRequest) -> optuna.storages.InMemoryStorage: - study_name = request.param - storage = make_test_storage(study_name) - return storage - - -@pytest.fixture(params=study_names) +@pytest.fixture def server_url(request: pytest.FixtureRequest, storage: optuna.storages.InMemoryStorage) -> str: return make_test_server(request, storage) +def run_single_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study(study_name="single", storage=storage, sampler=sampler) + + def objective(trial: optuna.Trial) -> float: + x1 = trial.suggest_float("x1", 0, 10) + x2 = trial.suggest_float("x2", 0, 10) + return (x1 - 2) ** 2 + (x2 - 5) ** 2 + + study.optimize(objective, n_trials=50) + return study + + +def run_single_trial_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # A single objective study with a single trial + # Refs: https://github.com/optuna/optuna-dashboard/issues/401 + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study(study_name="single-trial", storage=storage, sampler=sampler) + + def objective(trial: optuna.Trial) -> float: + x1 = trial.suggest_float("x1", 0, 10) + x2 = trial.suggest_float("x2", 0, 10) + return (x1 - 2) ** 2 + (x2 - 5) ** 2 + + study.optimize(objective, n_trials=1) + return study + + +def run_single_1param_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study( + study_name="single-1-param", storage=storage, direction="maximize", sampler=sampler + ) + + def objective(trial: optuna.Trial) -> float: + x1 = trial.suggest_float("x1", 0, 10) + return -((x1 - 2) ** 2) + + study.optimize(objective, n_trials=50) + return study + + +def run_single_dynamic_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # Single-objective study with dynamic search space + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study( + study_name="single-dynamic", storage=storage, direction="maximize", sampler=sampler + ) + + def objective(trial: optuna.Trial) -> float: + category = trial.suggest_categorical("category", ["foo", "bar"]) + if category == "foo": + return (trial.suggest_float("x1", 0, 10) - 2) ** 2 + else: + return -((trial.suggest_float("x2", -10, 0) + 5) ** 2) + + study.optimize(objective, n_trials=50) + return study + + +def run_single_inf_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # Single objective study with 'inf', '-inf', or 'nan' value + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study(study_name="single-inf", storage=storage, sampler=sampler) + + def objective(trial: optuna.Trial) -> float: + x = trial.suggest_float("x", -10, 10) + if trial.number % 3 == 0: + return float("inf") + elif trial.number % 3 == 1: + return float("-inf") + else: + return x**2 + + study.optimize(objective, n_trials=50) + return study + + +def run_multi_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # Multi-objective study + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study( + study_name="multi-objective", + storage=storage, + directions=["minimize", "minimize"], + sampler=sampler, + ) + + def objective(trial: optuna.Trial) -> tuple[float, float]: + x = trial.suggest_float("x", 0, 5) + y = trial.suggest_float("y", 0, 3) + v0 = 4 * x**2 + 4 * y**2 + v1 = (x - 5) ** 2 + (y - 5) ** 2 + return v0, v1 + + study.optimize(objective, n_trials=50) + return study + + +def run_multi_dynamic_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # Multi-objective study with dynamic search space + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study( + study_name="multi-dynamic", + storage=storage, + directions=["minimize", "minimize"], + sampler=sampler, + ) + + def objective(trial: optuna.Trial) -> tuple[float, float]: + category = trial.suggest_categorical("category", ["foo", "bar"]) + if category == "foo": + x = trial.suggest_float("x1", 0, 5) + y = trial.suggest_float("y1", 0, 3) + v0 = 4 * x**2 + 4 * y**2 + v1 = (x - 5) ** 2 + (y - 5) ** 2 + return v0, v1 + else: + x = trial.suggest_float("x2", 0, 5) + y = trial.suggest_float("y2", 0, 3) + v0 = 2 * x**2 + 2 * y**2 + v1 = (x - 2) ** 2 + (y - 3) ** 2 + return v0, v1 + + study.optimize(objective, n_trials=50) + return study + + +def run_single_pruned_without_report_objective_study( + storage: optuna.storages.InMemoryStorage, +) -> optuna.Study: + # Pruning with no intermediate values + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study( + study_name="single-pruned-without-report", storage=storage, sampler=sampler + ) + + def objective(trial: optuna.Trial) -> float: + x = trial.suggest_float("x", -15, 30) + y = trial.suggest_float("y", -15, 30) + v = x**2 + y**2 + if v > 100: + raise optuna.TrialPruned() + return v + + study.optimize(objective, n_trials=100) + return study + + +def run_single_inf_report_objective_study( + storage: optuna.storages.InMemoryStorage, +) -> optuna.Study: + # Single objective pruned after reported 'inf', '-inf', or 'nan' + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study(study_name="single-inf-report", storage=storage, sampler=sampler) + + def objective(trial: optuna.Trial) -> float: + x = trial.suggest_float("x", -10, 10) + if trial.number % 3 == 0: + trial.report(float("inf"), 1) + elif trial.number % 3 == 1: + trial.report(float("-inf"), 1) + else: + trial.report(float("nan"), 1) + + if x > 0: + raise optuna.TrialPruned() + else: + return x**2 + + study.optimize(objective, n_trials=50) + return study + + +def run_issue_410_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # Issue 410 + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study(study_name="issue-410", storage=storage, sampler=sampler) + + def objective(trial: optuna.Trial) -> float: + trial.suggest_categorical("resample_rate", ["50ms"]) + trial.suggest_categorical("channels", ["all"]) + trial.suggest_categorical("window_size", [256]) + if trial.number > 15: + raise Exception("Unexpected error") + trial.suggest_categorical("cbow", [True]) + trial.suggest_categorical("model", ["m1"]) + + trial.set_user_attr("epochs", 0) + trial.set_user_attr("deterministic", True) + if trial.number > 10: + raise Exception("unexpeccted error") + trial.set_user_attr("folder", "/path/to/folder") + trial.set_user_attr("resample_type", "foo") + trial.set_user_attr("run_id", "0001") + return 1.0 + + study.optimize(objective, n_trials=20, catch=(Exception,)) + return study + + +def run_single_no_trials_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # No trials single-objective study + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study(study_name="single-no-trials", storage=storage, sampler=sampler) + + return study + + +def run_multi_no_trials_objective_study(storage: optuna.storages.InMemoryStorage) -> optuna.Study: + # No trials multi-objective study + sampler = optuna.samplers.RandomSampler(seed=0) + study = optuna.create_study( + study_name="multi-no-trials", + storage=storage, + directions=["minimize", "maximize"], + sampler=sampler, + ) + return study + + +parameterize_studies = pytest.mark.parametrize( + "run_study", + [ + run_single_objective_study, + run_single_trial_objective_study, + run_single_1param_objective_study, + run_single_dynamic_objective_study, + run_single_inf_objective_study, + run_multi_objective_study, + run_multi_dynamic_objective_study, + run_single_pruned_without_report_objective_study, + run_single_inf_report_objective_study, + run_issue_410_objective_study, + run_single_no_trials_objective_study, + run_multi_no_trials_objective_study, + ], +) + + +@parameterize_studies def test_study_list( page: Page, storage: optuna.storages.InMemoryStorage, server_url: str, + run_study: Callable[[optuna.storages.InMemoryStorage], optuna.Study], ) -> None: - summaries = optuna.get_all_study_summaries(storage) - study_id = summaries[0]._study_id - study_name = summaries[0].study_name + study = run_study(storage) + + study_id = study._study_id + study_name = study.study_name page.goto(server_url) page.click(f"a[href='/dashboard/studies/{study_id}']") @@ -242,14 +281,17 @@ def test_study_list( assert study_name in title +@parameterize_studies def test_study_analytics( page: Page, storage: optuna.storages.InMemoryStorage, server_url: str, + run_study: Callable[[optuna.storages.InMemoryStorage], optuna.Study], ) -> None: - summaries = optuna.get_all_study_summaries(storage) - study_id = summaries[0]._study_id - study_name = summaries[0].study_name + study = run_study(storage) + + study_id = study._study_id + study_name = study.study_name url = f"{server_url}/studies/{study_id}" page.goto(url) @@ -263,14 +305,17 @@ def test_study_analytics( assert study_name in title +@parameterize_studies def test_trial_list( page: Page, storage: optuna.storages.InMemoryStorage, server_url: str, + run_study: Callable[[optuna.storages.InMemoryStorage], optuna.Study], ) -> None: - summaries = optuna.get_all_study_summaries(storage) - study_id = summaries[0]._study_id - study_name = summaries[0].study_name + study = run_study(storage) + + study_id = study._study_id + study_name = study.study_name url = f"{server_url}/studies/{study_id}" page.goto(url) @@ -284,14 +329,17 @@ def test_trial_list( assert study_name in title +@parameterize_studies def test_trial_table( page: Page, storage: optuna.storages.InMemoryStorage, server_url: str, + run_study: Callable[[optuna.storages.InMemoryStorage], optuna.Study], ) -> None: - summaries = optuna.get_all_study_summaries(storage) - study_id = summaries[0]._study_id - study_name = summaries[0].study_name + study = run_study(storage) + + study_id = study._study_id + study_name = study.study_name url = f"{server_url}/studies/{study_id}" page.goto(url) @@ -305,14 +353,17 @@ def test_trial_table( assert study_name in title +@parameterize_studies def test_trial_note( page: Page, storage: optuna.storages.InMemoryStorage, server_url: str, + run_study: Callable[[optuna.storages.InMemoryStorage], optuna.Study], ) -> None: - summaries = optuna.get_all_study_summaries(storage) - study_id = summaries[0]._study_id - study_name = summaries[0].study_name + study = run_study(storage) + + study_id = study._study_id + study_name = study.study_name url = f"{server_url}/studies/{study_id}" page.goto(url)