Merge branch 'main' into naip_analysis

Author: lillythomas

.binder/environment.yml

@@ -0,0 +1,36 @@
+name: claymodel
+channels:
+  - conda-forge
+  - pytorch
+  - nodefaults
+dependencies:
+  - conda-lock~=2.5.6
+  - einops~=0.7.0
+  - fiona~=1.9.5
+  - geopandas-base~=0.14.1
+  - h5netcdf~=1.3.0
+  - jupyter-book~=1.0.0
+  - jupyterlab~=4.0.7
+  - jsonargparse~=4.27.0
+  - lightning~=2.1.0
+  - matplotlib-base~=3.8.2
+  - planetary-computer~=1.0.0
+  - python-box~=7.1.0
+  - pytorch~=2.1.0
+  - cpuonly
+  - python~=3.11.0
+  - pyarrow~=16.1.0
+  - rioxarray~=0.15.0
+  - rasterio~=1.3.10
+  - s3fs~=2024.3.1
+  - scikit-image~=0.22.0
+  - scikit-learn~=1.4.0
+  - stackstac~=0.5.0
+  - timm~=0.9.16
+  - torchdata~=0.7.1
+  - torchvision~=0.16.1
+  - transformers~=4.35.2
+  - typeshed-client~=2.4.0
+  - vit-pytorch~=1.6.4
+  - wandb~=0.15.12
+  - zarr~=2.16.1

.github/workflows/test.yml

@@ -6,15 +6,13 @@
 
 An open source AI model and interface for Earth.
 
-# Getting started
-
 ## Quickstart
 
 Launch into a [JupyterLab](https://jupyterlab.readthedocs.io) environment on
 
-| [Binder](https://mybinder.readthedocs.io/en/latest) | [Planetary Computer](https://planetarycomputer.microsoft.com) | [SageMaker Studio Lab](https://studiolab.sagemaker.aws) |
-|:--:|:--:|:--:|
-| [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Clay-foundation/model/main) | [![Open on Planetary Computer](https://img.shields.io/badge/Open-Planetary%20Computer-black?style=flat&logo=microsoft)](https://pccompute.westeurope.cloudapp.azure.com/compute/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2FClay-foundation%2Fmodel&urlpath=lab%2Ftree%2Fmodel%2Fplaceholder.ipynb&branch=main) | [![Open in SageMaker Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/Clay-foundation/model/blob/main/placeholder.ipynb) |
+| [Binder](https://mybinder.readthedocs.io/en/latest) | [SageMaker Studio Lab](https://studiolab.sagemaker.aws) |
+|:--:|:--:|
+| [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Clay-foundation/model/main) | [![Open in SageMaker Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/Clay-foundation/model/blob/main/docs/tutorials/clay-v1-wall-to-wall.ipynb) |
 
 ## Installation
 
@@ -63,23 +61,37 @@ To check out the different options available, and look at the hyperparameter
 configurations, run:
 
     python trainer.py --help
-    python trainer.py test --print_config
 
 To quickly test the model on one batch in the validation set:
 
-    python trainer.py validate --trainer.fast_dev_run=True
-
-To train the model for a hundred epochs:
-
-    python trainer.py fit --trainer.max_epochs=100
+    python trainer.py fit --model ClayMAEModule --data ClayDataModule --config configs/config.yaml --trainer.fast_dev_run=True
 
-To generate embeddings from the pretrained model's encoder on 1024 images
-(stored as a GeoParquet file with spatiotemporal metadata):
+To train the model:
 
-    python trainer.py predict --ckpt_path=checkpoints/last.ckpt \
-                              --data.batch_size=1024 \
-                              --data.data_dir=s3://clay-tiles-02 \
-                              --trainer.limit_predict_batches=1
+    python trainer.py fit --model ClayMAEModule --data ClayDataModule --config configs/config.yaml
 
 More options can be found using `python trainer.py fit --help`, or at the
 [LightningCLI docs](https://lightning.ai/docs/pytorch/2.1.0/cli/lightning_cli.html).
+
+## Contributing
+
+### Writing documentation
+
+Our Documentation uses [Jupyter Book](https://jupyterbook.org/intro.html).
+
+Install it with:
+```bash
+pip install -U jupyter-book
+```
+
+Then build it with:
+```bash
+jupyter-book build docs/
+```
+
+You can preview the site locally with:
+```bash
+python -m http.server --directory _build/html
+```
+
+There is a GitHub Action on `./github/workflows/deploy-docs.yml` that builds the site and pushes it to GitHub Pages.

README.md

@@ -0,0 +1,32 @@
+"""
+Command line interface to run the neural network model!
+
+From the project root directory, do:
+
+    python classify.py fit --config configs/classify_eurosat.yaml
+
+References:
+- https://lightning.ai/docs/pytorch/2.1.0/cli/lightning_cli.html
+- https://pytorch-lightning.medium.com/introducing-lightningcli-v2-supercharge-your-training-c070d43c7dd6
+"""
+
+from lightning.pytorch.cli import LightningCLI
+
+from finetune.classify.eurosat_datamodule import EuroSATDataModule  # noqa: F401
+from finetune.classify.eurosat_model import EuroSATClassifier  # noqa: F401
+
+
+# %%
+def cli_main():
+    """
+    Command-line inteface to run ClayMAE with ClayDataModule.
+    """
+    cli = LightningCLI(EuroSATClassifier, EuroSATDataModule)
+    return cli
+
+
+# %%
+if __name__ == "__main__":
+    cli_main()
+
+    print("Done!")