MAINT: remove return annotation, rework out= arg handling

Author: ev-br

torch_np/_binary_ufuncs.py

@@ -4,14 +4,7 @@
 
 from . import _helpers
 from ._detail import _binary_ufuncs
-from ._normalizations import (
-    ArrayLike,
-    DTypeLike,
-    NDArray,
-    OutArray,
-    SubokLike,
-    normalizer,
-)
+from ._normalizations import ArrayLike, DTypeLike, NDArray, SubokLike, normalizer
 
 __all__ = [
     name
@@ -40,7 +33,7 @@ def wrapped(
         subok: SubokLike = False,
         signature=None,
         extobj=None,
-    ) -> OutArray:
+    ):
         tensors = _helpers.ufunc_preprocess(
             (x1, x2), out, where, casting, order, dtype, subok, signature, extobj
         )
@@ -51,7 +44,7 @@ def wrapped(
             tensors = tuple(torch.broadcast_to(t, shape) for t in tensors)
 
         result = torch_func(*tensors)
-        return result, out
+        return result
 
     return wrapped
 
@@ -75,7 +68,7 @@ def matmul(
     extobj=None,
     axes=None,
     axis=None,
-) -> OutArray:
+):
     tensors = _helpers.ufunc_preprocess(
         (x1, x2), out, True, casting, order, dtype, subok, signature, extobj
     )
@@ -84,7 +77,7 @@ def matmul(
 
     # NB: do not broadcast input tensors against the out=... array
     result = _binary_ufuncs.matmul(*tensors)
-    return result, out
+    return result
 
 
 #

torch_np/_funcs.py

@@ -10,7 +10,6 @@
     AxisLike,
     DTypeLike,
     NDArray,
-    OutArray,
     SubokLike,
     normalizer,
 )
@@ -42,11 +41,11 @@ def clip(
     min: Optional[ArrayLike] = None,
     max: Optional[ArrayLike] = None,
     out: Optional[NDArray] = None,
-) -> OutArray:
+):
     # np.clip requires both a_min and a_max not None, while ndarray.clip allows
     # one of them to be None. Follow the more lax version.
     result = _impl.clip(a, min, max)
-    return result, out
+    return result
 
 
 @normalizer
@@ -79,9 +78,9 @@ def trace(
     axis2=1,
     dtype: DTypeLike = None,
     out: Optional[NDArray] = None,
-) -> OutArray:
+):
     result = _impl.trace(a, offset, axis1, axis2, dtype)
-    return result, out
+    return result
 
 
 @normalizer
@@ -134,9 +133,9 @@ def vdot(a: ArrayLike, b: ArrayLike, /):
 
 
 @normalizer
-def dot(a: ArrayLike, b: ArrayLike, out: Optional[NDArray] = None) -> OutArray:
+def dot(a: ArrayLike, b: ArrayLike, out: Optional[NDArray] = None):
     result = _impl.dot(a, b)
-    return result, out
+    return result
 
 
 # ### sort and partition ###
@@ -233,9 +232,9 @@ def imag(a: ArrayLike):
 
 
 @normalizer
-def round_(a: ArrayLike, decimals=0, out: Optional[NDArray] = None) -> OutArray:
+def round_(a: ArrayLike, decimals=0, out: Optional[NDArray] = None):
     result = _impl.round(a, decimals)
-    return result, out
+    return result
 
 
 around = round_
@@ -254,11 +253,11 @@ def sum(
     keepdims=NoValue,
     initial=NoValue,
     where=NoValue,
-) -> OutArray:
+):
     result = _impl.sum(
         a, axis=axis, dtype=dtype, initial=initial, where=where, keepdims=keepdims
     )
-    return result, out
+    return result
 
 
 @normalizer
@@ -270,11 +269,11 @@ def prod(
     keepdims=NoValue,
     initial=NoValue,
     where=NoValue,
-) -> OutArray:
+):
     result = _impl.prod(
         a, axis=axis, dtype=dtype, initial=initial, where=where, keepdims=keepdims
     )
-    return result, out
+    return result
 
 
 product = prod
@@ -289,9 +288,9 @@ def mean(
     keepdims=NoValue,
     *,
     where=NoValue,
-) -> OutArray:
+):
     result = _impl.mean(a, axis=axis, dtype=dtype, where=NoValue, keepdims=keepdims)
-    return result, out
+    return result
 
 
 @normalizer
@@ -304,11 +303,11 @@ def var(
     keepdims=NoValue,
     *,
     where=NoValue,
-) -> OutArray:
+):
     result = _impl.var(
         a, axis=axis, dtype=dtype, ddof=ddof, where=where, keepdims=keepdims
     )
-    return result, out
+    return result
 
 
 @normalizer
@@ -321,11 +320,11 @@ def std(
     keepdims=NoValue,
     *,
     where=NoValue,
-) -> OutArray:
+):
     result = _impl.std(
         a, axis=axis, dtype=dtype, ddof=ddof, where=where, keepdims=keepdims
     )
-    return result, out
+    return result
 
 
 @normalizer
@@ -335,9 +334,9 @@ def argmin(
     out: Optional[NDArray] = None,
     *,
     keepdims=NoValue,
-) -> OutArray:
+):
     result = _impl.argmin(a, axis=axis, keepdims=keepdims)
-    return result, out
+    return result
 
 
 @normalizer
@@ -347,9 +346,9 @@ def argmax(
     out: Optional[NDArray] = None,
     *,
     keepdims=NoValue,
-) -> OutArray:
+):
     result = _impl.argmax(a, axis=axis, keepdims=keepdims)
-    return result, out
+    return result
 
 
 @normalizer
@@ -360,9 +359,9 @@ def amax(
     keepdims=NoValue,
     initial=NoValue,
     where=NoValue,
-) -> OutArray:
+):
     result = _impl.max(a, axis=axis, initial=initial, where=where, keepdims=keepdims)
-    return result, out
+    return result
 
 
 max = amax
@@ -376,9 +375,9 @@ def amin(
     keepdims=NoValue,
     initial=NoValue,
     where=NoValue,
-) -> OutArray:
+):
     result = _impl.min(a, axis=axis, initial=initial, where=where, keepdims=keepdims)
-    return result, out
+    return result
 
 
 min = amin
@@ -387,9 +386,9 @@ def amin(
 @normalizer
 def ptp(
     a: ArrayLike, axis: AxisLike = None, out: Optional[NDArray] = None, keepdims=NoValue
-) -> OutArray:
+):
     result = _impl.ptp(a, axis=axis, keepdims=keepdims)
-    return result, out
+    return result
 
 
 @normalizer
@@ -400,9 +399,9 @@ def all(
     keepdims=NoValue,
     *,
     where=NoValue,
-) -> OutArray:
+):
     result = _impl.all(a, axis=axis, where=where, keepdims=keepdims)
-    return result, out
+    return result
 
 
 @normalizer
@@ -413,9 +412,9 @@ def any(
     keepdims=NoValue,
     *,
     where=NoValue,
-) -> OutArray:
+):
     result = _impl.any(a, axis=axis, where=where, keepdims=keepdims)
-    return result, out
+    return result
 
 
 @normalizer
@@ -430,9 +429,9 @@ def cumsum(
     axis: AxisLike = None,
     dtype: DTypeLike = None,
     out: Optional[NDArray] = None,
-) -> OutArray:
+):
     result = _impl.cumsum(a, axis=axis, dtype=dtype)
-    return result, out
+    return result
 
 
 @normalizer
@@ -441,9 +440,9 @@ def cumprod(
     axis: AxisLike = None,
     dtype: DTypeLike = None,
     out: Optional[NDArray] = None,
-) -> OutArray:
+):
     result = _impl.cumprod(a, axis=axis, dtype=dtype)
-    return result, out
+    return result
 
 
 cumproduct = cumprod
@@ -460,7 +459,7 @@ def quantile(
     keepdims=False,
     *,
     interpolation=None,
-) -> OutArray:
+):
     result = _impl.quantile(
         a,
         q,
@@ -470,7 +469,7 @@ def quantile(
         keepdims=keepdims,
         interpolation=interpolation,
     )
-    return result, out
+    return result
 
 
 @normalizer(promote_scalar_result=True)
@@ -484,7 +483,7 @@ def percentile(
     keepdims=False,
     *,
     interpolation=None,
-) -> OutArray:
+):
     result = _impl.percentile(
         a,
         q,
@@ -494,7 +493,7 @@ def percentile(
         keepdims=keepdims,
         interpolation=interpolation,
     )
-    return result, out
+    return result
 
 
 def median(