remove elle, we'll bring it back later. bunch of other small cleanups

Author: geospatial-jeff

.github/workflows/ci.yml

@@ -21,7 +21,7 @@ jobs:
       - run: uv sync --locked --all-extras --group dev
       - run: uv run ruff check . --exclude "*.ipynb"
       - run: uv run ruff format --check . --exclude "*.ipynb"
-      - run: uv run ty check claymodel training finetune trainer.py tests --exclude "*.ipynb"
+      - run: uv run ty check claymodel tests --exclude "*.ipynb"
 
   test:
     runs-on: ubuntu-latest
@@ -35,4 +35,4 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
       - run: uv sync --locked --all-extras --group dev
-      - run: uv run pytest tests/ -v --cov=claymodel --cov-report=term-missing
+      - run: uv run pytest tests/ -v --cov=claymodel --cov-report=term-missing --cov-fail-under=90

claymodel/api.py

@@ -2,15 +2,13 @@
 
 __all__ = ["EmbeddingResult", "embed", "load_metadata", "load_model", "normalize"]
 
-import warnings
 from dataclasses import dataclass, field
 from importlib.resources import files
 from pathlib import Path
 
 import numpy as np
 import torch
 
-from claymodel.inference.elle import ELLEProbe
 from claymodel.metadata import PlatformMetadata, load_metadata_yaml
 from claymodel.module import ClayMAEModule
 
@@ -125,7 +123,6 @@ def embed(  # noqa: PLR0913
     device: str = "cpu",
     time: torch.Tensor | None = None,
     latlon: torch.Tensor | None = None,
-    quality: bool = False,
     metadata: dict[str, PlatformMetadata] | None = None,
 ) -> EmbeddingResult:
     """Embed pixels or a GeoTIFF with a Clay model."""
@@ -181,21 +178,9 @@ def embed(  # noqa: PLR0913
         encoded, *_ = model.encoder(datacube)
         cls_embeddings = encoded[:, 0, :]
 
-    result = EmbeddingResult(
+    return EmbeddingResult(
         embeddings=cls_embeddings,
         sensor=sensor,
         gsd=float(sensor_meta.gsd),
         metadata={"latlon": latlon, "time": time},
     )
-
-    if quality:
-        try:
-            probe = ELLEProbe.default()
-            result.metadata["quality_score"] = probe.score(cls_embeddings)
-        except FileNotFoundError:
-            warnings.warn(
-                "ELLE probe not available. Install or provide probe weights.",
-                stacklevel=2,
-            )
-
-    return result

claymodel/inference/__init__.py

@@ -1,7 +1,6 @@
 """Inference utilities for Clay Foundation Model."""
 
 from claymodel.inference.deterministic import DeterministicInference
-from claymodel.inference.elle import ELLEProbe
 from claymodel.inference.masking import PatchAnalyzer
 
-__all__ = ["DeterministicInference", "ELLEProbe", "PatchAnalyzer"]
+__all__ = ["DeterministicInference", "PatchAnalyzer"]

claymodel/inference/elle.py

@@ -143,7 +143,6 @@ known-first-party = ["claymodel", "training", "finetune"]
 "claymodel/__init__.py" = ["PLR0911"]
 "claymodel/api.py" = ["PLR0912", "PLR0915", "PLR2004"]
 "claymodel/module.py" = ["PLR2004"]
-"claymodel/inference/elle.py" = ["PLC0415"]
 "claymodel/inference/masking.py" = ["PLR2004"]
 "tests/*.py" = [
     "ANN001",

pyproject.toml

@@ -1,6 +1,5 @@
 """Test the high-level API."""
 
-import warnings
 from importlib.resources import files
 
 import numpy as np
@@ -176,19 +175,6 @@ def test_embed_sentinel1_db_conversion():
     assert not torch.isnan(result.embeddings).any()
 
 
-def test_embed_quality_warns_when_probe_missing():
-    """quality=True should warn, not error, when probe weights missing."""
-    model = _make_tiny_module()
-    pixels = torch.randn(1, 10, 64, 64)
-    with warnings.catch_warnings(record=True) as w:
-        warnings.simplefilter("always")
-        result = embed(pixels, sensor="sentinel-2-l2a", model=model, quality=True)
-        assert result.embeddings.shape == (1, 192)
-        # Should have warned about missing probe
-        probe_warned = any("ELLE" in str(w_.message) or "probe" in str(w_.message) for w_ in w)
-        assert probe_warned
-
-
 def test_normalize_output_device_matches_input():
     """Normalized output should be on the same device as input."""
     pixels = torch.randn(1, 10, 64, 64)

tests/test_api.py

@@ -12,7 +12,7 @@
     clay_mae_tiny,
     load_metadata,
 )
-from claymodel.inference import DeterministicInference, ELLEProbe, PatchAnalyzer
+from claymodel.inference import DeterministicInference, PatchAnalyzer
 
 
 def test_version_is_string():
@@ -54,5 +54,4 @@ def test_import_unknown_raises_attribute_error():
 
 def test_inference_package_exports():
     assert callable(DeterministicInference)
-    assert ELLEProbe is not None
     assert PatchAnalyzer is not None

tests/test_elle.py

@@ -20,5 +20,3 @@ def cli_main() -> LightningCLI:
 
 if __name__ == "__main__":
     cli_main()
-
-    print("Done!")