feat: added various training loggers using confit.Draft

.pre-commit-config.yaml

@@ -22,7 +22,7 @@ repos:
   # ruff
   - repo: https://github.com/charliermarsh/ruff-pre-commit
     # Ruff version.
-    rev: 'v0.6.4'
+    rev: 'v0.9.6'
     hooks:
       - id: ruff
         args: ['--config', 'pyproject.toml', '--fix', '--show-fixes']

docs/training/loggers.md

@@ -12,7 +12,7 @@ You can configure loggers in `edsnlp.train` via the `logger` parameter of the `t
         from edsnlp.training.loggers import CSVLogger
         from edsnlp.training import train
 
-        logger = CSVLogger()
+        logger = CSVLogger.draft()
         train(..., logger=logger)
         # or train(..., logger="csv")
         ```
@@ -34,7 +34,7 @@ You can configure loggers in `edsnlp.train` via the `logger` parameter of the `t
         from edsnlp.training.loggers import CSVLogger
         from edsnlp.training import train
 
-        loggers = ["tensorboard", CSVLogger(...)]
+        loggers = ["tensorboard", CSVLogger.draft(...)]
         train(..., logger=loggers)
         ```
 
@@ -48,8 +48,18 @@ You can configure loggers in `edsnlp.train` via the `logger` parameter of the `t
                 ...
         ```
 
-`edsnlp.train` will provide a default project name and logging dir for loggers that require these parameters, but it is
-recommended to set the project name explicitly in the logger configuration.
+!!! note "Draft objects"
+
+    `edsnlp.train` will provide a default project name and logging dir for loggers that require these parameters, but it is
+recommended to set the project name explicitly in the logger configuration. For these loggers, if you don't want to set
+the project name yourself, you can either:
+
+    - call `CSVLogger.draft(...)` without the normal init parameters minus the `project_name` or `logging_dir` parameters,
+      which will cause a `Draft[CSVLogger]` object to be returned if some required parameters are missing
+    - or use `"@loggers": csv` in the config file, which will also cause a `Draft[CSVLogger]` object to be returned if some required
+      parameters are missing
+
+    If you do not want a `Draft` object to be returned, call `CSVLogger` directly.
 
 The supported loggers are listed below.
 

edsnlp/core/pipeline.py

@@ -44,7 +44,7 @@
 from spacy.vocab import Vocab, create_vocab
 from typing_extensions import Literal, Self
 
-from ..core.registries import PIPE_META, FactoryMeta, PartialPipeFactory, registry
+from ..core.registries import PIPE_META, DraftPipe, FactoryMeta, registry
 from ..utils.collections import (
     FrozenDict,
     FrozenList,
@@ -238,9 +238,9 @@ def create_pipe(
                     **(config if config is not None else {}),
                 }
             ).resolve(registry=registry)
-            if isinstance(pipe, PartialPipeFactory):
+            if isinstance(pipe, DraftPipe):
                 if name is None:
-                    name = signature(pipe.func).parameters.get("name").default
+                    name = signature(pipe._func).parameters.get("name").default
                 if name is None or name == Parameter.empty:
                     name = factory
                 pipe = pipe.instantiate(nlp=self, path=(name,))
@@ -297,8 +297,8 @@ def add_pipe(
                 raise ValueError(
                     "Can't pass config or name with an instantiated component",
                 )
-            if isinstance(factory, PartialPipeFactory):
-                name = name or factory.kwargs.get("name")
+            if isinstance(factory, DraftPipe):
+                name = name or factory._kwargs.get("name")
                 factory = factory.instantiate(nlp=self, path=(name,))
 
             pipe = factory
@@ -585,13 +585,13 @@ def from_config(
     def _add_pipes(
         self,
         pipeline: Sequence[str],
-        components: Dict[str, PartialPipeFactory],
+        components: Dict[str, DraftPipe],
         exclude: Container[str],
         enable: Container[str],
         disable: Container[str],
     ):
         try:
-            components = PartialPipeFactory.instantiate(components, nlp=self)
+            components = DraftPipe.instantiate(components, nlp=self)
         except ConfitValidationError as e:
             e = ConfitValidationError(
                 e.raw_errors,
@@ -1277,9 +1277,9 @@ def load_from_huggingface(
     owner, model_name = repo_id.split("/")
     module_name = model_name.replace("-", "_")
 
-    assert (
-        len(repo_id.split("/")) == 2
-    ), "Invalid repo_id format (expected 'owner/repo_name' format)"
+    assert len(repo_id.split("/")) == 2, (
+        "Invalid repo_id format (expected 'owner/repo_name' format)"
+    )
     path = None
     mtime = None
     try:

edsnlp/core/registries.py

@@ -19,7 +19,7 @@
 import spacy
 from confit import Config, Registry, RegistryCollection, set_default_registry
 from confit.errors import ConfitValidationError, patch_errors
-from confit.registry import Partial
+from confit.registry import Draft
 from spacy.pipe_analysis import validate_attrs
 
 import edsnlp
@@ -71,14 +71,13 @@ class FactoryMeta:
 T = TypeVar("T")
 
 
-class PartialPipeFactory(Partial[T]):
+class DraftPipe(Draft[T]):
     def __init__(self, func, kwargs):
         super().__init__(func, kwargs)
-        self.func = func
         self.instantiated = None
         self.error = None
 
-    def maybe_nlp(self) -> Union["PartialPipeFactory", Any]:
+    def maybe_nlp(self) -> Union["DraftPipe", Any]:
         """
         If the factory requires an nlp argument and the user has explicitly
         provided it (this is unusual, we usually expect the factory to be
@@ -91,7 +90,7 @@ def maybe_nlp(self) -> Union["PartialPipeFactory", Any]:
         """
         from edsnlp.core.pipeline import Pipeline, PipelineProtocol
 
-        sig = inspect.signature(self.func)
+        sig = inspect.signature(self._func)
         if (
             not (
                 "nlp" in sig.parameters
@@ -100,23 +99,23 @@ def maybe_nlp(self) -> Union["PartialPipeFactory", Any]:
                     or sig.parameters["nlp"].annotation in (Pipeline, PipelineProtocol)
                 )
             )
-            or "nlp" in self.kwargs
-        ) and not self.search_curried_factory(self.kwargs):
-            return self.func(**self.kwargs)
+            or "nlp" in self._kwargs
+        ) and not self.search_nested_drafts(self._kwargs):
+            return self._func(**self._kwargs)
         return self
 
     @classmethod
-    def search_curried_factory(cls, obj):
-        if isinstance(obj, PartialPipeFactory):
+    def search_nested_drafts(cls, obj):
+        if isinstance(obj, DraftPipe):
             return obj
         elif isinstance(obj, dict):
             for value in obj.values():
-                result = cls.search_curried_factory(value)
+                result = cls.search_nested_drafts(value)
                 if result is not None:
                     return result
         elif isinstance(obj, (tuple, list, set)):
             for value in obj:
-                result = cls.search_curried_factory(value)
+                result = cls.search_nested_drafts(value)
                 if result is not None:
                     return result
         return None
@@ -131,7 +130,7 @@ def instantiate(
         passing in the nlp object and name to factories. Since they can be
         nested, we need to add them to every factory in the config.
         """
-        if isinstance(self, PartialPipeFactory):
+        if isinstance(self, DraftPipe):
             if self.error is not None:
                 raise self.error
 
@@ -140,30 +139,30 @@ def instantiate(
 
             name = path[0] if len(path) == 1 else None
             parameters = (
-                inspect.signature(self.func.__init__).parameters
-                if isinstance(self.func, type)
-                else inspect.signature(self.func).parameters
+                inspect.signature(self._func.__init__).parameters
+                if isinstance(self._func, type)
+                else inspect.signature(self._func).parameters
             )
             kwargs = {
-                key: PartialPipeFactory.instantiate(
+                key: DraftPipe.instantiate(
                     self=value,
                     nlp=nlp,
                     path=(*path, key),
                 )
-                for key, value in self.kwargs.items()
+                for key, value in self._kwargs.items()
             }
             try:
                 if nlp and "nlp" in parameters:
                     kwargs["nlp"] = nlp
                 if name and "name" in parameters:
                     kwargs["name"] = name
-                self.instantiated = self.func(**kwargs)
+                self.instantiated = self._func(**kwargs)
             except ConfitValidationError as e:
                 self.error = e
                 raise ConfitValidationError(
                     patch_errors(e.raw_errors, path, model=e.model),
                     model=e.model,
-                    name=self.func.__module__ + "." + self.func.__qualname__,
+                    name=self._func.__module__ + "." + self._func.__qualname__,
                 )  # .with_traceback(None)
             # except Exception as e:
             #     obj.error = e
@@ -174,7 +173,7 @@ def instantiate(
             errors = []
             for key, value in self.items():
                 try:
-                    instantiated[key] = PartialPipeFactory.instantiate(
+                    instantiated[key] = DraftPipe.instantiate(
                         self=value,
                         nlp=nlp,
                         path=(*path, key),
@@ -190,7 +189,7 @@ def instantiate(
             for i, value in enumerate(self):
                 try:
                     instantiated.append(
-                        PartialPipeFactory.instantiate(value, nlp, (*path, str(i)))
+                        DraftPipe.instantiate(value, nlp, (*path, str(i)))
                     )
                 except ConfitValidationError as e:  # pragma: no cover
                     errors.append(e.raw_errors)
@@ -200,9 +199,9 @@ def instantiate(
         else:
             return self
 
-    def _raise_partial_error(self):
+    def _raise_draft_error(self):
         raise TypeError(
-            f"This component PartialFactory({self.func}) has not been instantiated "
+            f"This {self} component has not been instantiated "
             f"yet, likely because it was missing an `nlp` pipeline argument. You "
             f"should either:\n"
             f"- add it to a pipeline: `pipe = nlp.add_pipe(pipe)`\n"
@@ -277,9 +276,7 @@ def check_and_return():
 
             if catalogue.check_exists(*registry_path):
                 func = catalogue._get(registry_path)
-                return lambda **kwargs: PartialPipeFactory(
-                    func, kwargs=kwargs
-                ).maybe_nlp()
+                return lambda **kwargs: DraftPipe(func, kwargs=kwargs).maybe_nlp()
 
         # Steps 1 & 2
         func = check_and_return()
@@ -432,7 +429,7 @@ def invoke(validated_fn, kwargs):
 
             @wraps(fn)
             def curried_registered_fn(**kwargs):
-                return PartialPipeFactory(registered_fn, kwargs).maybe_nlp()
+                return DraftPipe(registered_fn, kwargs).maybe_nlp()
 
             return (
                 curried_registered_fn

edsnlp/pipes/base.py

@@ -12,7 +12,7 @@
 from spacy.tokens import Doc, Span
 
 from edsnlp.core import PipelineProtocol
-from edsnlp.core.registries import PartialPipeFactory
+from edsnlp.core.registries import DraftPipe
 from edsnlp.utils.span_getters import (
     SpanGetter,  # noqa: F401
     SpanGetterArg,  # noqa: F401
@@ -52,7 +52,7 @@ def __call__(cls, nlp=inspect.Signature.empty, *args, **kwargs):
                 and sig.parameters["nlp"].default is sig.empty
                 and bound.arguments.get("nlp", sig.empty) is sig.empty
             ):
-                return PartialPipeFactory(cls, bound.arguments)
+                return DraftPipe(cls, bound.arguments)
             if nlp is inspect.Signature.empty:
                 bound.arguments.pop("nlp", None)
         except TypeError:  # pragma: no cover