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+1,9 @@ # Training and evaluating models on OCP datasets -- [Getting Started](#getting-started) -- [OC20](#oc20) - - [Initial Structure to Relaxed Energy (IS2RE)](#initial-structure-to-relaxed-energy-prediction-is2re) - - [IS2RE Relaxations](#is2re-relaxations) - - [Structure to Energy and Forces (S2EF)](#structure-to-energy-and-forces-s2ef) - - [Training OC20 models with total energies (IS2RE/S2EF)](#training-oc20-models-with-total-energies-is2res2ef) - - [Overriding YAML config parameters from the command line](#overriding-yaml-config-parameters-from-the-command-line) - - [Initial Structure to Relaxed Structure (IS2RS)](#initial-structure-to-relaxed-structure-is2rs) - - [Create EvalAI submission files](#create-evalai-oc20-submission-files) - - [S2EF/IS2RE](#s2efis2re) - - [IS2RS](#is2rs) -- [OC22](#oc22) - - [Initial Structure to Total Relaxed Energy (IS2RE-Total)](#initial-structure-to-total-relaxed-energy-is2re-total) - - [Structure to Total Energy and Forces (S2EF-Total)](#structure-to-total-energy-and-forces-s2ef-total) - - [Joint Training](#joint-training) - - [Create EvalAI submission files](#create-evalai-oc22-submission-files) - - [S2EF-Total/IS2RE-Total](#s2ef-totalis2re-total) -- [Using Your Own Data](#using-your-own-data) - - [Writing an LMDB](#writing-an-lmdb) - - [Using an ASE Database](#using-an-ase-database) - - [Using ASE-Readable Files](#using-ase-readable-files) - - [Single-Structure Files](#single-structure-files) - - [Multi-Structure Files](#multi-structure-files) ## Getting Started -The [Open Catalyst Project](https://opencatalystproject.org/) consists of three -distinct tasks: +The [Open Catalyst Project](https://opencatalystproject.org/) consists of three distinct tasks: - Initial Structure to Relaxed Energy prediction (IS2RE) - Structure to Energy and Forces (S2EF) - Initial Structure to Relaxed Structure (IS2RS) diff --git a/_sources/core/README.md b/_sources/index.md similarity index 100% rename from _sources/core/README.md rename to _sources/index.md diff --git a/_sources/tutorial/OCP-introduction.md b/_sources/tutorial/OCP-introduction.md index 405757c52..e1a184a15 100644 --- a/_sources/tutorial/OCP-introduction.md +++ b/_sources/tutorial/OCP-introduction.md @@ -11,7 +11,7 @@ kernelspec: name: python3 --- -Introduction to using OCP in molecular simulations +Simple simulations using the OCP ASE calculator ================================================== To introduce OCP we start with using it to calculate adsorption energies for a simple, atomic adsorbate where we specify the site we want to the adsorption energy for. Conceptually, you do this like you would do it with density functional theory. You create a slab model for the surface, place an adsorbate on it as an initial guess, run a relaxation to get the lowest energy geometry, and then compute the adsorption energy using reference states for the adsorbate. diff --git a/_sources/tutorial/intro.md b/_sources/tutorial/intro.md index aa2bf3db3..ca0ae7395 100644 --- a/_sources/tutorial/intro.md +++ b/_sources/tutorial/intro.md @@ -11,7 +11,7 @@ kernelspec: name: python3 --- -Utilizing large, graph-based, pre-trained machine learned potentials in atomistic simulations +Intro and background on OCP and DFT ---------- # Abstract @@ -38,26 +38,13 @@ The [Open Catalyst Project (OCP)](https://github.com/Open-Catalyst-Project) is a ## Models -OCP provides several [models](https://github.com/Open-Catalyst-Project/ocp/blob/main/MODELS.md). Each model represents a different approach to featurization, and a different machine learning architecture. The models can be used for different tasks, and you will find different checkpoints associated with different datasets and tasks. - -- CGCNN [[`arXiv`](https://arxiv.org/abs/1710.10324)] [[`code`](https://github.com/Open-Catalyst-Project/ocp/blob/main/ocpmodels/models/cgcnn.py)] -- SchNet [[`arXiv`](https://arxiv.org/abs/1706.08566)] [[`code`](https://github.com/Open-Catalyst-Project/ocp/blob/main/ocpmodels/models/schnet.py)] -- DimeNet [[`arXiv`](https://arxiv.org/abs/2003.03123)] [[`code`](https://github.com/Open-Catalyst-Project/ocp/blob/main/ocpmodels/models/dimenet.py)] -- ForceNet [[`arXiv`](https://arxiv.org/abs/2103.01436)] [[`code`](https://github.com/Open-Catalyst-Project/ocp/blob/main/ocpmodels/models/forcenet.py)] -- DimeNet++ [[`arXiv`](https://arxiv.org/abs/2011.14115)] [[`code`](https://github.com/Open-Catalyst-Project/ocp/blob/main/ocpmodels/models/dimenet_plus_plus.py)] -- SpinConv [[`arXiv`](https://arxiv.org/abs/2106.09575)] [[`code`](https://github.com/Open-Catalyst-Project/ocp/blob/main/ocpmodels/models/spinconv.py)] -- GemNet-dT [[`arXiv`](https://arxiv.org/abs/2106.08903)] [[`code`](https://github.com/Open-Catalyst-Project/ocp/tree/main/ocpmodels/models/gemnet)] -- PaiNN [[`arXiv`](https://arxiv.org/abs/2102.03150)] [[`code`](https://github.com/Open-Catalyst-Project/ocp/tree/main/ocpmodels/models/painn)] -- Graph Parallelism [[`arXiv`](https://arxiv.org/abs/2203.09697)] [[`code`](https://github.com/Open-Catalyst-Project/ocp/tree/main/ocpmodels/models/gemnet_gp)] -- GemNet-OC [[`arXiv`](https://arxiv.org/abs/2204.02782)] [[`code`](https://github.com/Open-Catalyst-Project/ocp/tree/main/ocpmodels/models/gemnet_oc)] -- SCN [[`arXiv`](https://arxiv.org/abs/2206.14331)] [[`code`](https://github.com/Open-Catalyst-Project/ocp/tree/main/ocpmodels/models/scn)] -- eSCN [[`arXiv`](https://arxiv.org/abs/2302.03655)] [[`code`](https://github.com/Open-Catalyst-Project/ocp/tree/main/ocpmodels/models/escn)] +OCP provides several [models](../core/MODELS). Each model represents a different approach to featurization, and a different machine learning architecture. The models can be used for different tasks, and you will find different checkpoints associated with different datasets and tasks. +++ ## Datasets / Tasks -OCP provides several different [datasets](https://github.com/Open-Catalyst-Project/ocp/blob/main/DATASET.md) that correspond to different tasks that range from predicting energy and forces from structures to Bader charges, relaxation energies, and others. +OCP provides several different datasets like [OC20](../core/datasets/oc20) that correspond to different tasks that range from predicting energy and forces from structures to Bader charges, relaxation energies, and others. +++ diff --git a/autoapi/index.html b/autoapi/index.html index 170ed85c3..0d1825310 100644 --- a/autoapi/index.html +++ b/autoapi/index.html @@ -140,7 +140,7 @@ -

Catalysis Tutorials