CLN: Remove entry points for models, metrics. Fixes #601

Remove since they are basically unused
by anyone but us, but require maintenance, test, etc.

Squash commits:
- Remove vak/entry_points.py
- Remove import of entry_points from vak/__init__.py
- Remove model and metric entry points from pyproject.toml
- Rewrite models/models.py to not use entry points
- Fix use of models.find in config/validators.py
- Fix use of find in config/models.py
- Remove entry point test in
  tests/test_models/test_teenytweetynet.py
- Fix entry point test in tests/test_models/test_tweetynet.py

pyproject.toml

@@ -68,19 +68,10 @@ Documentation = "https://vak.readthedocs.io"
 [project.scripts]
 vak = 'vak.__main__:main'
 
-[project.entry-points."vak.models"]
-TeenyTweetyNetModel = 'vak.models.teenytweetynet:TeenyTweetyNet'
-TweetyNetModel = 'vak.models.tweetynet:TweetyNet'
-
-[project.entry-points."vak.metrics"]
-Accuracy = 'vak.metrics.Accuracy'
-Levenshtein = 'vak.metrics.Levenshtein'
-SegmentErrorRate = 'vak.metrics.SegmentErrorRate'
-
 [tool.flit.sdist]
 exclude = [
     "tests/data_for_tests"
 ]
 
 [tool.pytest.ini_options]
-filterwarnings = ["ignore:::.*torch.utils.tensorboard",]
+filterwarnings = ["ignore:::.*torch.utils.tensorboard",]

src/vak/__init__.py

@@ -20,7 +20,6 @@
     curvefit,
     datasets,
     device,
-    entry_points,
     files,
     io,
     labeled_timebins,
@@ -54,7 +53,6 @@
     "csv",
     "datasets",
     "device",
-    "entry_points",
     "files",
     "io",
     "labeled_timebins",

src/vak/config/models.py

@@ -49,16 +49,12 @@ def map_from_config_dict(config_dict, model_names):
     # to avoid circular dependencies
     # (user would be unable to import models in other packages
     # if the module in the other package needed to `import vak`)
-    MODELS = {model_name: model_builder for model_name, model_builder in models.find()}
+    MODEL_NAMES = list(models.models.BUILTIN_MODELS.keys())
     for model_name in model_names:
-        if model_name not in MODELS:
-            # try appending 'Model' to name
-            tmp_model_name = f"{model_name}Model"
-            if tmp_model_name not in MODELS:
-                raise ValueError(
-                    f"Did not find an installed model named {model_name} or {tmp_model_name}. "
-                    f"Installed models are: {list(MODELS.keys())}"
-                )
+        if model_name not in MODEL_NAMES:
+            raise ValueError(
+                f"Invalid model name: {model_name}.\nValid model names are: {MODEL_NAMES}"
+            )
 
     # now see if we can find corresponding sections in config
     sections = list(config_dict.keys())

src/vak/config/validators.py

@@ -26,11 +26,11 @@ def is_a_file(instance, attribute, value):
 
 
 def is_valid_model_name(instance, attribute, value):
-    MODEL_NAMES = [model_name for model_name, model_builder in models.find()]
+    MODEL_NAMES = list(models.models.BUILTIN_MODELS.keys())
     for model_name in value:
-        if model_name not in MODEL_NAMES and f"{model_name}Model" not in MODEL_NAMES:
+        if model_name not in MODEL_NAMES:
             raise ValueError(
-                f"Model {model_name} not found when importing installed models."
+                f"Invalid model name: {model_name}.\nValid model names are: {MODEL_NAMES}"
             )
 
 
@@ -91,7 +91,7 @@ def are_sections_valid(config_dict, toml_path=None):
             f"Please use just one command besides `prep` per .toml configuration file"
         )
 
-    MODEL_NAMES = [model_name for model_name, model_builder in models.find()]
+    MODEL_NAMES = list(models.models.BUILTIN_MODELS.keys())
     # add model names to valid sections so users can define model config in sections
     valid_sections = VALID_SECTIONS + MODEL_NAMES
     for section in sections:

src/vak/models/__init__.py

@@ -4,7 +4,7 @@
     definition,
 )
 from .base import Model
-from .models import find, from_model_config_map
+from .models import from_model_config_map
 from .teenytweetynet import TeenyTweetyNet
 from .tweetynet import TweetyNet
 from .windowed_frame_classification_model import WindowedFrameClassificationModel
@@ -14,7 +14,6 @@
     "base",
     "decorator",
     "definition",
-    "find",
     "from_model_config_map",
     "Model",
     "TeenyTweetyNet",

src/vak/models/models.py

@@ -1,43 +1,25 @@
-"""module that contains helper function to load models
+"""Helper function to load models"""
+from __future__ import annotations
 
-Models in separate packages should make themselves available to vak by including
-'vak.models' in the entry_points of their setup.py file.
+from .tweetynet import TweetyNet
+from .teenytweetynet import TeenyTweetyNet
 
-For example, if you had a package `grunet` containing a model
-that was instantiated by a function `GRUnet`,
-then that package would include the following in its setup.py file:
 
-setup(
-    ...
-    entry_points={'vak.models': 'GRUnet = grunet:GRUnet'},
-    ...
-)
+# TODO: Replace constant with decorator that registers models, https://github.com/vocalpy/vak/issues/623
+BUILTIN_MODELS = {
+    'TweetyNet': TweetyNet,
+    'TeenyTweetyNet': TeenyTweetyNet
+}
 
-For more detail on entry points in Python, see:
-https://packaging.python.org/guides/creating-and-discovering-plugins/#using-package-metadata
-https://setuptools.readthedocs.io/en/latest/setuptools.html#dynamic-discovery-of-services-and-plugins
-https://amir.rachum.com/blog/2017/07/28/python-entry-points/
-"""
-from .. import entry_points
+MODEL_NAMES = list(BUILTIN_MODELS.keys())
 
-MODELS_ENTRY_POINT = "vak.models"
 
-
-def find():
-    """find installed vak.models
-
-    returns generator that yields model name and function for loading
-    """
-    for entrypoint in entry_points._iter(MODELS_ENTRY_POINT):
-        yield entrypoint.name, entrypoint.load()
-
-
-def from_model_config_map(model_config_map,
+def from_model_config_map(model_config_map: dict[str: dict],
                           # TODO: move num_classes / input_shape into model configs
-                          num_classes,
-                          input_shape,
-                          labelmap):
-    """get models that are ready to train, given their names and configurations.
+                          num_classes: int,
+                          input_shape: tuple[int, int, int],
+                          labelmap: dict) -> dict:
+    """Get models that are ready to train, given their names and configurations.
 
     Given a dictionary that maps model names to configurations,
     along with the number of classes they should be trained to discriminate and their input shape,
@@ -66,7 +48,7 @@ def from_model_config_map(model_config_map,
     models_map : dict
         where keys are model names and values are instances of the models, ready for training
     """
-    MODELS = {model_name: model_builder for model_name, model_builder in find()}
+    import vak.models
 
     models_map = {}
     for model_name, model_config in model_config_map.items():
@@ -77,12 +59,15 @@ def from_model_config_map(model_config_map,
             num_classes=num_classes,
             input_shape=input_shape,
         )
+
         try:
-            model = MODELS[model_name].from_config(config=model_config, labelmap=labelmap)
-        except KeyError:
-            model = MODELS[f"{model_name}Model"].from_config(
-                config=model_config,
-                labelmap=labelmap
-            )
+            model_class = getattr(vak.models, model_name)
+        except AttributeError as e:
+            raise ValueError(
+                f"Invalid model name: '{model_name}'.\nValid model names are: {MODEL_NAMES}"
+            ) from e
+
+        model = model_class.from_config(config=model_config, labelmap=labelmap)
         models_map[model_name] = model
+
     return models_map

tests/test_models/test_teenytweetynet.py

@@ -8,16 +8,6 @@
 from .test_tweetynet import TEST_INIT_ARGVALS
 
 
-def test_installed():
-    # makes sure the entry point loads properly
-    if "vak" in sys.modules:
-        sys.modules.pop("vak")
-    import vak
-
-    models = [name for name, class_ in sorted(vak.models.find())]
-    assert "TeenyTweetyNetModel" in models
-
-
 class TestTeenyTweetyNet:
     def test_model_is_decorated(self):
         assert issubclass(vak.models.TeenyTweetyNet,

tests/test_models/test_tweetynet.py

@@ -31,16 +31,6 @@
 TEST_INIT_ARGVALS = itertools.product(LABELMAPS, INPUT_SHAPES)
 
 
-def test_installed():
-    # makes sure the entry point loads properly
-    if "vak" in sys.modules:
-        sys.modules.pop("vak")
-    import vak
-
-    models = [name for name, class_ in sorted(vak.models.find())]
-    assert "TweetyNetModel" in models
-
-
 class TestTweetyNet:
     def test_model_is_decorated(self):
         assert issubclass(vak.models.TweetyNet,