Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fixed learning_rate_scheduler params in automl #3203

Merged
merged 7 commits into from
Mar 4, 2023
Merged

Fixed learning_rate_scheduler params in automl #3203

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
7 commits
Select commit Hold shift + click to select a range
3c19f0c
Fixed learning_rate_scheduler params in automl
tgaddair Mar 3, 2023
2e1f156
Cleanup
tgaddair Mar 3, 2023
0b36d85
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Mar 3, 2023
a4ec8eb
Fixed imports
tgaddair Mar 4, 2023
f4179f3
Merge branch 'fix-automl' of https://github.com/ludwig-ai/ludwig into…
tgaddair Mar 4, 2023
de1c733
Increase test timeout
tgaddair Mar 4, 2023
322b26c
Merge branch 'master' into fix-automl
tgaddair Mar 4, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion .github/workflows/pytest.yml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -59,7 +59,7 @@ jobs:
ports:
- 9000:9000

timeout-minutes: 90
timeout-minutes: 120
steps:
- name: Setup ludwigai/ludwig-ray container for local testing with act.
if: ${{ env.ACT }}
Expand Down
4 changes: 2 additions & 2 deletions ludwig/automl/defaults/combiner/tabnet_config.yaml
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -16,10 +16,10 @@ hyperopt:
trainer.learning_rate:
space: choice
categories: [0.005, 0.01, 0.02, 0.025]
trainer.decay_rate:
trainer.learning_rate_scheduler.decay_rate:
space: choice
categories: [0.8, 0.9, 0.95]
trainer.decay_steps:
trainer.learning_rate_scheduler.decay_steps:
space: choice
categories: [500, 2000, 8000, 10000, 20000]
combiner.size:
Expand Down
4 changes: 2 additions & 2 deletions ludwig/benchmarking/examples/process_config.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -36,9 +36,9 @@ def process_config(ludwig_config: dict, experiment_dict: dict) -> dict:
"categories": ["fill_with_const", "fill_with_mean"],
},
"combiner.type": {"space": "choice", "categories": ["tabnet", "concat"]},
"trainer.decay": {"space": "choice", "categories": [True, False]},
"trainer.learning_rate_scheduler.decay": {"space": "choice", "categories": [True, False]},
"trainer.learning_rate": {"space": "loguniform", "lower": 0.0001, "upper": 0.1},
"trainer.decay_rate": {"space": "uniform", "lower": 0.4, "upper": 0.96},
"trainer.learning_rate_scheduler.decay_rate": {"space": "uniform", "lower": 0.4, "upper": 0.96},
"trainer.batch_size": {"space": "randint", "lower": 32, "upper": 2048},
},
"search_alg": {"type": "hyperopt"},
Expand Down
23 changes: 22 additions & 1 deletion tests/integration_tests/test_automl.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -27,8 +27,14 @@
ray = pytest.importorskip("ray")

import dask.dataframe as dd # noqa
from ray.tune.experiment.trial import Trial # noqa

from ludwig.automl import create_auto_config, create_auto_config_with_dataset_profile, train_with_config # noqa
from ludwig.automl import ( # noqa
auto_train,
create_auto_config,
create_auto_config_with_dataset_profile,
train_with_config,
)
from ludwig.hyperopt.execution import RayTuneExecutor # noqa

pytestmark = pytest.mark.distributed
Expand Down Expand Up @@ -299,6 +305,21 @@ def test_train_with_config(time_budget, test_data_tabular_large, ray_cluster_2cp
_run_train_with_config(time_budget, test_data_tabular_large, tmpdir)


@pytest.mark.distributed
def test_auto_train(test_data_tabular_large, ray_cluster_2cpu, tmpdir):
_, ofeatures, dataset_csv = test_data_tabular_large
results = auto_train(
dataset=dataset_csv,
target=ofeatures[0][NAME],
time_limit_s=120,
user_config={"hyperopt": {"executor": {"num_samples": 2}}},
)

analysis = results.experiment_analysis
for trial in analysis.trials:
assert trial.status != Trial.ERROR, f"Error in trial {trial}"


@pytest.mark.parametrize("fs_protocol,bucket", [private_param(("s3", "ludwig-tests"))], ids=["s3"])
def test_train_with_config_remote(fs_protocol, bucket, test_data_tabular_large, ray_cluster_2cpu):
backend = {
Expand Down