tweaks to separate -> None from -> Signature.empty

python/cog/predictor.py

@@ -8,6 +8,7 @@
 import uuid
 from abc import ABC, abstractmethod
 from collections.abc import Iterator
+from inspect import Signature
 from pathlib import Path
 from typing import (
     Any,
@@ -267,7 +268,7 @@ def validate_input_type(
     type: Type[Any],  # pylint: disable=redefined-builtin
     name: str,
 ) -> None:
-    if type is inspect.Signature.empty:
+    if type is Signature.empty:
         raise TypeError(
             f"No input type provided for parameter `{name}`. Supported input types are: {readable_types_list(ALLOWED_INPUT_TYPES)}, or a Union or List of those types."
         )
@@ -284,7 +285,7 @@ def validate_input_type(
 
 
 def get_input_create_model_kwargs(
-    signature: inspect.Signature, input_types: Dict[str, Any]
+    signature: Signature, input_types: Dict[str, Any]
 ) -> Dict[str, Any]:
     create_model_kwargs = {}
 
@@ -296,7 +297,7 @@ def get_input_create_model_kwargs(
         validate_input_type(InputType, name)
 
         # if no default is specified, create an empty, required input
-        if parameter.default is inspect.Signature.empty:
+        if parameter.default is Signature.empty:
             default = Input()
         else:
             default = parameter.default
@@ -374,14 +375,11 @@ class Input(BaseModel):
     )  # type: ignore
 
 
-def get_return_annotation(fn: Callable[..., Any]) -> Optional[Type[Any]]:
+def get_return_annotation(fn: Callable[..., Any]) -> "Type[Any]|Signature.empty":
     try:
-        return get_type_hints(fn).get("return", None)
+        return get_type_hints(fn).get("return", Signature.empty)
     except TypeError:
-        return_annotation = inspect.signature(fn).return_annotation
-        if return_annotation is inspect.Signature.empty:
-            return None
-        return return_annotation
+        return inspect.signature(fn).return_annotation
 
 
 def get_output_type(predictor: BasePredictor) -> Type[BaseModel]:
@@ -392,7 +390,7 @@ def get_output_type(predictor: BasePredictor) -> Type[BaseModel]:
     predict = get_predict(predictor)
     maybe_output_type = get_return_annotation(predict)
 
-    if maybe_output_type is None:
+    if maybe_output_type is Signature.empty:
         raise TypeError(
             """You must set an output type. If your model can return multiple output types, you can explicitly set `Any` as the output type.
 
@@ -496,7 +494,7 @@ def get_training_output_type(predictor: BasePredictor) -> Type[BaseModel]:
     train = get_train(predictor)
 
     TrainingOutputType = get_return_annotation(train)  # pylint: disable=invalid-name
-    if not TrainingOutputType:
+    if TrainingOutputType is Signature.empty:
         raise TypeError(
             """You must set an output type. If your model can return multiple output types, you can explicitly set `Any` as the output type.
 

test-integration/test_integration/test_predict.py

@@ -299,6 +299,7 @@ def test_predict_works_with_deferred_annotations():
         timeout=DEFAULT_TIMEOUT,
     )
 
+
 def test_predict_works_with_partial_wrapper():
     project_dir = Path(__file__).parent / "fixtures/partial-predict-project"