ENH: Add default losses to KerasClassifier and KerasRegressor

.github/workflows/tests.yaml

@@ -22,7 +22,6 @@ jobs:
       - uses: pre-commit/action@v2.0.0
 
   TestStable:
-    needs: Linting
     name: Ubuntu / Python ${{ matrix.python-version }} / TensorFlow Stable / Scikit-Learn Stable
     runs-on: ubuntu-latest
     strategy:
@@ -55,7 +54,6 @@ jobs:
       - uses: codecov/codecov-action@v1
 
   TestDev:
-    needs: Linting
     name: Ubuntu / Python ${{ matrix.python-version }} / TensorFlow Nightly / Scikit-Learn Nightly
     runs-on: ubuntu-latest
     strategy:
@@ -98,7 +96,6 @@ jobs:
       - uses: codecov/codecov-action@v1
 
   TestOldest:
-    needs: Linting
     name: Ubuntu / Python ${{ matrix.python-version }} / TF ${{ matrix.tf-version }} / Scikit-Learn ${{ matrix.sklearn-version }}
     runs-on: ubuntu-latest
     strategy:
@@ -135,7 +132,6 @@ jobs:
       - uses: codecov/codecov-action@v1
 
   TestOSs:
-    needs: Linting
     name: ${{ matrix.os }} / Python ${{ matrix.python-version }} / TF Stable / Scikit-Learn Stable
     runs-on: ${{ matrix.os }}-latest
     strategy:

docs/source/notebooks/DataTransformers.md

@@ -316,7 +316,6 @@ from sklearn.metrics import accuracy_score
 
 
 class MultiOutputClassifier(KerasClassifier):
-
     @property
     def target_encoder(self):
         return MultiOutputTransformer()

scikeras/_types.py

@@ -0,0 +1,18 @@
+from typing import Callable, List, Type, Union
+
+import numpy as np
+import tensorflow as tf
+import tensorflow.keras as keras
+
+from tensorflow.keras.callbacks import Callback as TF_Callback
+from tensorflow.keras.losses import Loss as TF_Loss
+from tensorflow.keras.metrics import Metric as TF_Metric
+from tensorflow.keras.optimizers import Optimizer as TF_Optimizer
+
+
+Model = Union[Callable[..., keras.Model], keras.Model]
+RandomState = Union[int, np.random.RandomState]
+Optimizer = Union[str, TF_Optimizer, Type[TF_Optimizer]]
+Loss = Union[str, TF_Loss, Type[TF_Loss], Callable]
+Metrics = Union[List[Union[str, TF_Metric, Type[TF_Metric], Callable]]]
+Callbacks = Union[List[Union[TF_Callback, Type[TF_Callback]]]]

scikeras/utils/__init__.py

@@ -14,7 +14,7 @@ def _camel2snake(s: str) -> str:
     return "".join(["_" + c.lower() if c.isupper() else c for c in s]).lstrip("_")
 
 
-def loss_name(loss: Union[str, Loss, Callable]) -> str:
+def loss_name(loss: Union[str, Loss, Callable]) -> Union[None, str]:
     """Retrieves a loss's full name (eg: "mean_squared_error").
 
     Parameters
@@ -26,7 +26,8 @@ def loss_name(loss: Union[str, Loss, Callable]) -> str:
     Returns
     -------
     str
-        String name of the loss.
+        String name of the loss (e.g., "mse") or None if the
+        input is not a string, Metric or callable.
 
     Notes
     -----
@@ -43,26 +44,20 @@ def loss_name(loss: Union[str, Loss, Callable]) -> str:
     'binary_crossentropy'
     >>> loss_name(losses.binary_crossentropy)
     'binary_crossentropy'
-
-    Raises
-    ------
-    TypeError
-        If loss is not a string, tf.keras.losses.Loss instance or a callable.
+    >>> loss_name({"out1": "mse", "out2": "mae"})
+    None
     """
     if isclass(loss):
         loss = loss()
     if not (isinstance(loss, (str, Loss)) or callable(loss)):
-        raise TypeError(
-            "``loss`` must be a string, a function, an instance of ``tf.keras.losses.Loss``"
-            " or a type inheriting from ``tf.keras.losses.Loss``"
-        )
+        return None
     fn_or_cls = keras_loss_get(loss)
     if isinstance(fn_or_cls, Loss):
         return _camel2snake(fn_or_cls.__class__.__name__)
     return fn_or_cls.__name__
 
 
-def metric_name(metric: Union[str, Metric, Callable]) -> str:
+def metric_name(metric: Union[str, Metric, Callable]) -> Union[None, str]:
     """Retrieves a metric's full name (eg: "mean_squared_error").
 
     Parameters
@@ -74,7 +69,8 @@ def metric_name(metric: Union[str, Metric, Callable]) -> str:
     Returns
     -------
     str
-        Full name for Keras metric. Ex: "mean_squared_error".
+        Full name for Keras metric (e.g., "mean_squared_error") or None if the
+        input is not a string, Metric or callable.
 
     Notes
     -----
@@ -91,21 +87,13 @@ def metric_name(metric: Union[str, Metric, Callable]) -> str:
     'BinaryCrossentropy'
     >>> metric_name(metrics.binary_crossentropy)
     'binary_crossentropy'
-
-    Raises
-    ------
-    TypeError
-        If metric is not a string, a tf.keras.metrics.Metric instance a class
-        inheriting from tf.keras.metrics.Metric.
+    >>> metric_name({"out1": "bce", "out2": "hinge"})
+    None
     """
     if isclass(metric):
         metric = metric()  # get_metric accepts instances, not classes
     if not (isinstance(metric, (str, Metric)) or callable(metric)):
-        raise TypeError(
-            "``metric`` must be a string, a function, an instance of"
-            " ``tf.keras.metrics.Metric`` or a type inheriting from"
-            " ``tf.keras.metrics.Metric``"
-        )
+        return None
     fn_or_cls = keras_metric_get(metric)
     if isinstance(fn_or_cls, Metric):
         return _camel2snake(fn_or_cls.__class__.__name__)