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from pathlib import Path
import pytest
from tests.helpers.run_if import RunIf
from tests.helpers.run_sh_command import run_sh_command
startfile = "src/train.py"
overrides = ["logger=[]"]
@RunIf(sh=True)
@pytest.mark.slow
def test_experiments(tmp_path: Path) -> None:
"""Test running all available experiment configs with `fast_dev_run=True.`
:param tmp_path: The temporary logging path.
"""
command = [
startfile,
"-m",
"experiment=glob(*)",
"hydra.sweep.dir=" + str(tmp_path),
"++trainer.fast_dev_run=true",
] + overrides
run_sh_command(command)
@RunIf(sh=True)
@pytest.mark.slow
def test_hydra_sweep(tmp_path: Path) -> None:
"""Test default hydra sweep.
:param tmp_path: The temporary logging path.
"""
command = [
startfile,
"-m",
"hydra.sweep.dir=" + str(tmp_path),
"model.optimizer.lr=0.005,0.01",
"++trainer.fast_dev_run=true",
] + overrides
run_sh_command(command)
@RunIf(sh=True)
@pytest.mark.slow
def test_hydra_sweep_ddp_sim(tmp_path: Path) -> None:
"""Test default hydra sweep with ddp sim.
:param tmp_path: The temporary logging path.
"""
command = [
startfile,
"-m",
"hydra.sweep.dir=" + str(tmp_path),
"trainer=ddp_sim",
"trainer.max_epochs=3",
"+trainer.limit_train_batches=0.01",
"+trainer.limit_val_batches=0.1",
"+trainer.limit_test_batches=0.1",
"model.optimizer.lr=0.005,0.01,0.02",
] + overrides
run_sh_command(command)
@RunIf(sh=True)
@pytest.mark.slow
def test_optuna_sweep(tmp_path: Path) -> None:
"""Test Optuna hyperparam sweeping.
:param tmp_path: The temporary logging path.
"""
command = [
startfile,
"-m",
"hparams_search=mnist_optuna",
"hydra.sweep.dir=" + str(tmp_path),
"hydra.sweeper.n_trials=10",
"hydra.sweeper.sampler.n_startup_trials=5",
"++trainer.fast_dev_run=true",
] + overrides
run_sh_command(command)
@RunIf(wandb=True, sh=True)
@pytest.mark.slow
def test_optuna_sweep_ddp_sim_wandb(tmp_path: Path) -> None:
"""Test Optuna sweep with wandb logging and ddp sim.
:param tmp_path: The temporary logging path.
"""
command = [
startfile,
"-m",
"hparams_search=mnist_optuna",
"hydra.sweep.dir=" + str(tmp_path),
"hydra.sweeper.n_trials=5",
"trainer=ddp_sim",
"trainer.max_epochs=3",
"+trainer.limit_train_batches=0.01",
"+trainer.limit_val_batches=0.1",
"+trainer.limit_test_batches=0.1",
"logger=wandb",
]
run_sh_command(command)
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