def test_double_validation_loop():
"""Test running 1 epoch with validation loop twice per epoch."""
command = [
"run.py",
"++trainer.max_epochs=1",
"++trainer.val_check_interval=0.5",
]
run_command(command)
def test_gpu():
"""Test running 1 epoch on GPU."""
command = [
"run.py",
"++trainer.max_epochs=1",
"++trainer.gpus=1",
]
run_command(command)
def test_default_gpu():
"""Test default configuration on GPU."""
command = [
"run.py",
"trainer.max_epochs=1",
"trainer.gpus=1",
"datamodule.pin_memory=True",
]
run_command(command)
def test_mixed_precision():
"""Test running 1 epoch with native pytorch mixed precision."""
command = [
"run.py",
"++trainer.max_epochs=1",
"++trainer.gpus=1",
"++trainer.precision=16",
]
run_command(command)
def test_gradient_accumulation():
"""Train 1 epoch with gradient accumulation."""
command = [
"run.py",
"trainer=default",
"trainer.max_epochs=1",
"trainer.accumulate_grad_batches=10",
]
run_command(command)
def test_limit_batches():
"""Test running 1 epoch on 25% of data."""
command = [
"run.py",
"++trainer.max_epochs=1",
"++trainer.limit_train_batches=0.25",
"++trainer.limit_val_batches=0.25",
"++trainer.limit_test_batches=0.25",
]
run_command(command)
def test_csv_logger():
"""Train 5 epochs with 5 batches with CSVLogger."""
command = [
"run.py",
"trainer=default",
"trainer.max_epochs=5",
"trainer.limit_train_batches=5",
"logger=csv",
]
run_command(command)
def test_overfit_batches():
"""Overfit to 10 batches over 10 epochs."""
command = [
"run.py",
"trainer=default",
"trainer.min_epochs=10",
"trainer.max_epochs=10",
"trainer.overfit_batches=10",
]
run_command(command)
def test_optuna_sweep():
"""Test Optuna sweeper."""
command = [
"run.py",
"-m",
"hparams_search=mnist_optuna",
"trainer=default",
"trainer.fast_dev_run=true",
]
run_command(command)
def test_tensorboard_logger():
"""Train 5 epochs with 5 batches with TensorboardLogger."""
command = [
"run.py",
"trainer=default",
"trainer.max_epochs=5",
"trainer.limit_train_batches=5",
"logger=tensorboard",
]
run_command(command)
def test_wandb_callbacks():
"""Test wandb callbacks."""
command = [
"run.py",
"trainer=default",
"trainer.max_epochs=3",
"logger=wandb",
"logger.wandb.project=template-tests",
"callbacks=wandb",
]
run_command(command)
def test_default_sweep():
"""Test default Hydra sweeper."""
command = [
"run.py",
"-m",
"datamodule.batch_size=64,128",
"model.lr=0.01,0.02",
"trainer=default",
"trainer.fast_dev_run=true",
]
run_command(command)
def test_limit_batches():
"""Train 1 epoch on 25% of data."""
command = [
"run.py",
"trainer=default",
"trainer.max_epochs=1",
"trainer.limit_train_batches=0.25",
"trainer.limit_val_batches=0.25",
"trainer.limit_test_batches=0.25",
]
run_command(command)
def test_apex_01():
"""Test mixed-precision level 01."""
command = [
"run.py",
"trainer=default",
"trainer.max_epochs=1",
"trainer.gpus=1",
"trainer.amp_backend=apex",
"trainer.amp_level=O1",
"trainer.precision=16",
]
run_command(command)
def test_wandb_optuna_sweep():
"""Test wandb logging with Optuna sweep."""
command = [
"run.py",
"-m",
"hparams_search=mnist_optuna",
"trainer=default",
"trainer.max_epochs=10",
"trainer.limit_train_batches=20",
"logger=wandb",
"logger.wandb.project=template-tests",
"logger.wandb.group=Optuna_SimpleDenseNet_MNIST",
"hydra.sweeper.n_trials=5",
]
run_command(command)
def test_fast_dev_run():
"""Run 1 train, val, test batch."""
command = ["run.py", "trainer=default", "trainer.fast_dev_run=true"]
run_command(command)
def test_ax_sweep():
"""Test Ax sweeper."""
command = ["run.py", "-m", "hparams_search=mnist_ax", "trainer.fast_dev_run=true"]
run_command(command)
def test_default_cpu():
"""Test default configuration on CPU."""
command = ["run.py", "trainer.max_epochs=1", "trainer.gpus=0"]
run_command(command)
def test_experiments():
"""Train 1 epoch with all experiment configs."""
command = ["run.py", "-m", "experiment=glob(*)", "trainer.max_epochs=1"]
run_command(command)
def test_fast_dev_run():
"""Test running for 1 train, val and test batch."""
command = ["run.py", "++trainer.fast_dev_run=true"]
run_command(command)
def test_experiments():
"""Test running all available experiment configs for 1 epoch."""
command = ["run.py", "-m", "experiment=glob(*)", "++trainer.max_epochs=1"]
run_command(command)
