Inlined extracted function.

Inlined in order to not violate API boundaries. Trying to put this in a good place ends up leading to a circular import issue.
cubed-dev · Sep 21, 2024 · b8ce6ec · b8ce6ec
1 parent dbefff4
commit b8ce6ec
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Showing 3 changed files with 53 additions and 36 deletions.
diff --git a/cubed/array_api/statistical_functions.py b/cubed/array_api/statistical_functions.py
@@ -5,9 +5,18 @@
     _numeric_dtypes,
     _real_floating_dtypes,
     _real_numeric_dtypes,
+    _signed_integer_dtypes,
+    _unsigned_integer_dtypes,
+    complex64,
+    complex128,
+    float32,
+    float64,
+    int32,
+    uint32,
+    int64,
+    uint64,
 )
-from cubed.backend_array_api import namespace as nxp
-from cubed.array_api.utility_functions import operator_default_dtype
+from cubed.backend_array_api import namespace as nxp, PRECISION
 from cubed.core import reduction
 
 
@@ -122,7 +131,16 @@ def prod(
     if x.dtype not in _numeric_dtypes and x.dtype not in _boolean_dtypes:
         raise TypeError("Only numeric or boolean dtypes are allowed in prod")
     if dtype is None:
-        dtype = operator_default_dtype(x)
+        if x.dtype in _signed_integer_dtypes:
+            dtype = int64 if PRECISION == 64 else int32
+        elif x.dtype in _unsigned_integer_dtypes:
+            dtype = uint64 if PRECISION == 64 else uint32
+        elif x.dtype == float32 and PRECISION == 64:
+            dtype = float64
+        elif x.dtype == complex64 and PRECISION == 64:
+            dtype = complex128
+        else:
+            dtype = x.dtype
     extra_func_kwargs = dict(dtype=dtype)
     return reduction(
         x,
@@ -143,7 +161,16 @@ def sum(
     if x.dtype not in _numeric_dtypes and x.dtype not in _boolean_dtypes:
         raise TypeError("Only numeric or boolean dtypes are allowed in sum")
     if dtype is None:
-        dtype = operator_default_dtype(x)
+        if x.dtype in _signed_integer_dtypes:
+            dtype = int64 if PRECISION == 64 else int32
+        elif x.dtype in _unsigned_integer_dtypes:
+            dtype = uint64 if PRECISION == 64 else uint32
+        elif x.dtype == float32 and PRECISION == 64:
+            dtype = float64
+        elif x.dtype == complex64 and PRECISION == 64:
+            dtype = complex128
+        else:
+            dtype = x.dtype
     extra_func_kwargs = dict(dtype=dtype)
     return reduction(
         x,

diff --git a/cubed/array_api/utility_functions.py b/cubed/array_api/utility_functions.py
@@ -1,17 +1,5 @@
 from cubed.array_api.creation_functions import asarray
-from cubed.array_api.dtypes import (
-    _signed_integer_dtypes,
-    _unsigned_integer_dtypes,
-    int32,
-    uint32,
-    int64,
-    uint64,
-    float32,
-    float64,
-    complex64,
-    complex128,
-)
-from cubed.backend_array_api import namespace as nxp, namespace, PRECISION
+from cubed.backend_array_api import namespace as nxp
 from cubed.core import reduction
 
 
@@ -41,19 +29,3 @@ def any(x, /, *, axis=None, keepdims=False, use_new_impl=True, split_every=None)
         use_new_impl=use_new_impl,
         split_every=split_every,
     )
-
-
-def operator_default_dtype(x: namespace.ndarray) -> namespace.dtype:
-    """Derive the correct default data type for operators."""
-    if x.dtype in _signed_integer_dtypes:
-        dtype = int64 if PRECISION == 64 else int32
-    elif x.dtype in _unsigned_integer_dtypes:
-        dtype = uint64 if PRECISION == 64 else uint32
-    elif x.dtype == float32 and PRECISION == 64:
-        dtype = float64
-    elif x.dtype == complex64 and PRECISION == 64:
-        dtype = complex128
-    else:
-        dtype = x.dtype
-
-    return dtype
diff --git a/cubed/nan_functions.py b/cubed/nan_functions.py
@@ -2,9 +2,18 @@
 
 from cubed.array_api.dtypes import (
     _numeric_dtypes,
+    _signed_integer_dtypes,
+    _unsigned_integer_dtypes,
+    complex64,
+    complex128,
+    float32,
+    float64,
+    int32,
+    uint32,
+    int64,
+    uint64,
 )
-from cubed.backend_array_api import namespace as nxp
-from cubed.array_api.utility_functions import operator_default_dtype
+from cubed.backend_array_api import namespace as nxp, PRECISION
 from cubed.core import reduction
 
 # TODO: refactor once nan functions are standardized:
@@ -61,7 +70,16 @@ def nansum(
     if x.dtype not in _numeric_dtypes:
         raise TypeError("Only numeric dtypes are allowed in nansum")
     if dtype is None:
-        dtype = operator_default_dtype(x)
+        if x.dtype in _signed_integer_dtypes:
+            dtype = int64 if PRECISION == 64 else int32
+        elif x.dtype in _unsigned_integer_dtypes:
+            dtype = uint64 if PRECISION == 64 else uint32
+        elif x.dtype == float32 and PRECISION == 64:
+            dtype = float64
+        elif x.dtype == complex64 and PRECISION == 64:
+            dtype = complex128
+        else:
+            dtype = x.dtype
     return reduction(
         x,
         nxp.nansum,