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

Jump to bottom

Add more benchmarking documentation #822

Merged
merged 7 commits into from
Dec 4, 2023
Merged

Add more benchmarking documentation #822

Show file tree
Hide file tree
Changes from 6 commits
Commits
Show all changes
7 commits
Select commit Hold shift + click to select a range
eb92458
Embedd the benchmarking README in the Sphinx documentation.
ernestum Nov 28, 2023
1505128
Add the benchmark summary from the release to the Sphinx documentation.
ernestum Nov 28, 2023
ebff2be
Add link to benchmark results to README.md
ernestum Nov 30, 2023
545a21d
Fix formatting issues in docs/conf.py and improve inline comment.
ernestum Nov 30, 2023
166799f
Fix typing issue due to new SB3 version.
ernestum Nov 30, 2023
e2a53e0
Black fixes.
ernestum Nov 30, 2023
6b2c89b
Improve formatting in benchmarking README.md
ernestum Dec 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: 2 additions & 0 deletions README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,8 @@ Currently, we have implementations of the algorithms below. 'Discrete' and 'Cont

You can find [the documentation here](https://imitation.readthedocs.io/en/latest/).

You can read the latest benchmark results [here](https://imitation.readthedocs.io/en/latest/main-concepts/benchmark_summary.html).

## Installation

### Prerequisites
Expand Down
4 changes: 2 additions & 2 deletions benchmarking/README.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -120,7 +120,7 @@ python sacred_output_to_csv.py output/sacred > summary.csv

This generates a csv file like this:

```csv
```
algo, env, score, expert_score
gail, seals/Walker2d-v1, 2298.883520464286, 2502.8930135576925
gail, seals/Swimmer-v1, 287.33667667857145, 295.40472964423077
Expand Down Expand Up @@ -187,7 +187,7 @@ where:
If `your_runs_dir` contains runs for more than one algorithm, you will have to
disambiguate using the `--algo` option.

# Tuning Hyperparameters
## Tuning Hyperparameters

The hyperparameters of any algorithm in imitation can be tuned using `src/imitation/scripts/tuning.py`.
The benchmarking hyperparameter configs were generated by tuning the hyperparameters using
Expand Down
17 changes: 17 additions & 0 deletions docs/conf.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,10 @@


# -- Project information -----------------------------------------------------
import io
import os
import urllib.request
import zipfile
from importlib import metadata

project = "imitation"
Expand Down Expand Up @@ -132,3 +135,17 @@ def setup(app):
"autodoc-process-docstring",
no_namedtuple_attrib_docstring,
)


# -- Download the latest benchmark summary -------------------------------------
download_url = (
"https://github.com/HumanCompatibleAI/imitation/releases/latest/"
Copy link
Collaborator

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

using /latest redirects to the most recent release, which I think means we'll need to provide benchmark_runs.zip on every subsequent release — is that something we're committed to doing?

Copy link
Collaborator Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I would be. What do you think @AdamGleave ? I eventually would love to make this part of the release pipeline.

"download/benchmark_runs.zip"
)

# Download the benchmark data, extract the summary and place it in the documentation
with urllib.request.urlopen(download_url) as url:
with zipfile.ZipFile(io.BytesIO(url.read())) as z:
with z.open("benchmark_runs/summary.md") as f:
with open("main-concepts/benchmark_summary.md", "wb") as out:
out.write(f.read())
2 changes: 2 additions & 0 deletions docs/index.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -57,6 +57,8 @@ If you use ``imitation`` in your research project, please cite our paper to help
main-concepts/trajectories
main-concepts/reward_networks
main-concepts/variable_horizon
main-concepts/benchmarks
main-concepts/benchmark_summary


.. toctree::
Expand Down
1 change: 1 addition & 0 deletions docs/main-concepts/benchmarks.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1 @@
../../benchmarking/README.md
ernestum marked this conversation as resolved.
Show resolved Hide resolved
3 changes: 2 additions & 1 deletion src/imitation/algorithms/mce_irl.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@
import torch as th
from seals import base_envs
from stable_baselines3.common import policies
from stable_baselines3.common import type_aliases as sb3_types

from imitation.algorithms import base
from imitation.data import rollout, types
Expand Down Expand Up @@ -196,7 +197,7 @@ def set_pi(self, pi: np.ndarray) -> None:
assert np.all(pi >= 0), "policy has negative probabilities"
self.pi = pi

def _predict(self, observation: th.Tensor, deterministic: bool = False):
def _predict(self, observation: sb3_types.PyTorchObs, deterministic: bool = False):
raise NotImplementedError("Should never be called as predict overridden.")

def forward(
Expand Down
Loading