Docs/pipx

README.md

@@ -19,6 +19,9 @@ In order to use th file `pyproject.toml` it is necessary to guarantee `pip>=21.8
 For a stable point-release, use `pip install terratorch`. 
 If you prefer to get the most recent version of the main branch, install the library with `pip install git+https://github.com/IBM/terratorch.git`.
 
+Another alternative is to install using [pipx](https://github.com/pypa/pipx) via `pipx install terratorch`, which creates an isolated environment and allows the user to run the application as 
+a common CLI tool, with no need of installing dependencies or activating environments. 
+
 TerraTorch requires gdal to be installed, which can be quite a complex process. If you don't have GDAL set up on your system, we reccomend using a conda environment and installing it with `conda install -c conda-forge gdal`.
 
 To install as a developer (e.g. to extend the library) clone this repo, install dependencies using `pip install -r requirements.txt` and run `pip install -e .`

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = 'setuptools.build_meta'
 
 [project]
 name = "terratorch"
-version = "0.99.0"
+version = "0.99.1"
 description = "TerraTorch - A model training toolkit for geospatial tasks"
 license = { "text" = "Apache License, Version 2.0" }
 readme = "README.md"
@@ -144,7 +144,7 @@ exclude_lines = [
 ]
 
 [tool.bumpver]
-current_version = "0.99.0"
+current_version = "0.99.1"
 version_pattern = "MAJOR.MINOR.PATCH[PYTAGNUM]"
 commit_message = "Bump version {old_version} -> {new_version}"
 commit = true

tests/test_backbones.py

@@ -1,6 +1,7 @@
 import pytest
 import timm
 import torch
+import importlib
 
 import terratorch  # noqa: F401
 
@@ -49,7 +50,16 @@ def test_vit_models_accept_multitemporal(model_name, input_224_multitemporal):
     backbone = timm.create_model(model_name, pretrained=False, num_frames=NUM_FRAMES)
     backbone(input_224_multitemporal)
 
+# Swin IS NOT on HuggingFace
+@pytest.mark.parametrize("model_name", ["prithvi_swin_L", "prithvi_swin_B"])
+def test_swin_instantiation(model_name):
+     base_module = "terratorch.models.backbones.prithvi_swin"
+     module = importlib.import_module(base_module)
+     model_class = getattr(module, model_name) 
 
+     model = model_class(pretrained=False, pretrained_bands=[0,1,2,3,4,5,6,7,8,9],
+                         bands=[1,2,3,4,5,6])
+
 #def test_swin_models_accept_non_divisible_by_patch_size(input_386):
 #    backbone = timm.create_model("prithvi_swin_90_us", pretrained=False, num_frames=NUM_FRAMES)
 #    backbone(input_386)