Rebuttal (#15)

* pg+nuplan train

* Need map

* use gym wrapper

* use createGymWrapper

* doc

* use all scenarios!

* update 80000 scenario

* train script

documentation/source/conf.py

@@ -0,0 +1,55 @@
+# Configuration file for the Sphinx documentation builder.
+#
+# This file only contains a selection of the most common options. For a full
+# list see the documentation:
+# https://www.sphinx-doc.org/en/master/usage/configuration.html
+
+# -- Path setup --------------------------------------------------------------
+
+# If extensions (or modules to documentation with autodoc) are in another directory,
+# add these directories to sys.path here. If the directory is relative to the
+# documentation root, use os.path.abspath to make it absolute, like shown here.
+#
+# import os
+# import sys
+# sys.path.insert(0, os.path.abspath('.'))
+
+
+# -- Project information -----------------------------------------------------
+
+project = 'ScenarioNet'
+copyright = 'MetaDriverse'
+author = 'MetaDriverse'
+
+# The full version, including alpha/beta/rc tags
+release = '0.1.1'
+
+# -- General configuration ---------------------------------------------------
+
+# Add any Sphinx extension module names here, as strings. They can be
+# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
+# ones.
+extensions = [
+    "sphinx.ext.autosectionlabel",
+    "sphinx_rtd_theme"
+]
+
+# Add any paths that contain templates here, relative to this directory.
+templates_path = ['_templates']
+
+# List of patterns, relative to source directory, that match files and
+# directories to ignore when looking for source files.
+# This pattern also affects html_static_path and html_extra_path.
+exclude_patterns = []
+
+# -- Options for HTML output -------------------------------------------------
+
+# The theme to use for HTML and HTML Help pages.  See the documentation for
+# a list of builtin themes.
+#
+html_theme = 'sphinx_rtd_theme'
+
+# Add any paths that contain custom static files (such as style sheets) here,
+# relative to this directory. They are copied after the builtin static files,
+# so a file named "default.css" will overwrite the builtin "default.css".
+html_static_path = []

documentation/source/index.rst

@@ -0,0 +1,33 @@
+########################
+ScenarioNet Documentation
+########################
+
+
+Welcome to the ScenarioNet documentation!
+ScenarioNet is an open-sourced platform for large-scale traffic scenario modeling and simulation with the following features:
+
+* ScenarioNet defines a unified scenario description format containing HD maps and detailed object annotations.
+* ScenarioNet provides tools to build and manage databases built from various data sources including real-world datasets like Waymo, nuScenes, Lyft L5, and nuPlan datasets and synthetic datasets like the procedural generated ones and safety-critical ones.
+* Scenarios recorded in this format can be replayed in the digital twins with multiple views, ranging from Bird-Eye-View layout to realistic 3D rendering.
+
+It can thus support several applications including large-scale scenario generation, AD testing, imitation learning, and reinforcement learning in both single-agent and multi-agent settings. The results imply scaling up the training data brings new research opportunities in machine learning and autonomous driving.
+
+This documentation brings you the information on installation, usages and more of ScenarioNet!
+You can also visit the `GitHub repo <https://github.com/metadriverse/scenarionet>`_ and `Webpage <https://metadriverse.github.io/scenarionet/>`_ for code and videos.
+Please feel free to contact us if you have any suggestions or ideas!
+
+
+Citation
+########
+
+You can read `our white paper <https://arxiv.org/pdf/2306.12241.pdf>`_ describing the details of ScenarioNet! If you use ScenarioNet in your own work, please cite:
+
+.. code-block:: latex
+
+    @article{li2023scenarionet,
+      title={ScenarioNet: Open-Source Platform for Large-Scale Traffic Scenario Simulation and Modeling},
+      author={Li, Quanyi and Peng, Zhenghao and Feng, Lan and Duan, Chenda and Mo, Wenjie and Zhou, Bolei and others},
+      journal={arXiv preprint arXiv:2306.12241},
+      year={2023}
+    }
+