MAINT: rebase, pick up changes from main

Author: ev-br

torch_np/_ndarray.py

@@ -493,26 +493,6 @@ def wrapped(x, *args, **kwds):
 ###### dtype routines
 
 
-def can_cast(from_, to, casting="safe"):
-    from_ = _extract_dtype(from_)
-    to_ = extract_dtype(to_)
-
-    return _dtypes_impl.can_cast_impl(from_.torch_dtype, to_.torch_dtype, casting)
-
-'''
-    # XXX: merge with _dtypes.can_cast. The Q is who converts from ndarray, if needed.
-    try:
-        from_dtype = asarray(from_).dtype
-    except (TypeError, RuntimeError):
-        # not an array_like; try convering to a dtype
-        from_dtype = _dtypes.dtype(from_)
-
-    try:
-        to_dtype = asarray(to).dtype
-    except (TypeError, RuntimeError):
-        to_dtype = _dtypes.dtype(to)
-'''
-
 def _extract_dtype(entry):
     try:
         dty = _dtypes.dtype(entry)
@@ -521,6 +501,13 @@ def _extract_dtype(entry):
     return dty
 
 
+def can_cast(from_, to, casting="safe"):
+    from_ = _extract_dtype(from_)
+    to_ = _extract_dtype(to)
+
+    return _dtypes_impl.can_cast_impl(from_.torch_dtype, to_.torch_dtype, casting)
+
+
 def result_type(*arrays_and_dtypes):
     dtypes = []
 

torch_np/_wrapper.py

@@ -293,14 +293,9 @@ def empty(shape, dtype=float, order="C", *, like=None):
     _util.subok_not_ok(like)
     if order != "C":
         raise NotImplementedError
-
     if dtype is None:
-        from ._detail._scalar_types import default_float_type
-
-        dtype = default_float_type.torch_dtype
-
+        dtype = _dtypes_impl.default_float_dtype
     result = torch.empty(shape, dtype=dtype)
-
     return asarray(result)
 
 
@@ -354,12 +349,8 @@ def ones(shape, dtype=None, order="C", *, like=None):
     if order != "C":
         raise NotImplementedError
     if dtype is None:
-        from ._detail._scalar_types import default_float_type
-
-        dtype = default_float_type.torch_dtype
-
+        dtype = _dtypes_impl.default_float_dtype
     result = torch.ones(shape, dtype=dtype)
-
     return asarray(result)