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-rw-r--r--numpy/array_api/tests/test_asarray.py46
1 files changed, 33 insertions, 13 deletions
diff --git a/numpy/array_api/tests/test_asarray.py b/numpy/array_api/tests/test_asarray.py
index bd1859d71..fdcc77506 100644
--- a/numpy/array_api/tests/test_asarray.py
+++ b/numpy/array_api/tests/test_asarray.py
@@ -1,24 +1,44 @@
import numpy as np
-def test_fast_return():
- """"""
- a = np.array([1, 2, 3], dtype='i')
- assert np.asarray(a) is a
- assert np.asarray(a, dtype='i') is a
- # This may produce a new view or a copy, but is never the same object.
- assert np.asarray(a, dtype='l') is not a
+def test_dtype_identity():
+ """Confirm the intended behavior for ``asarray`` results.
+ The result of ``asarray()`` should have the dtype provided through the
+ keyword argument, when used. This forces unique array handles to be
+ produced for unique np.dtype objects, but (for equivalent dtypes), the
+ underlying data (the base object) is shared with the original array object.
+
+ Ref https://github.com/numpy/numpy/issues/1468
+ """
+ int_array = np.array([1, 2, 3], dtype='i')
+ assert np.asarray(int_array) is int_array
+
+ # The character code resolves to the singleton dtype object provided
+ # by the numpy package.
+ assert np.asarray(int_array, dtype='i') is int_array
+
+ # Derive a dtype from n.dtype('i'), but add a metadata object to force
+ # the dtype to be distinct.
unequal_type = np.dtype('i', metadata={'spam': True})
- b = np.asarray(a, dtype=unequal_type)
- assert b is not a
- assert b.base is a
+ annotated_int_array = np.asarray(int_array, dtype=unequal_type)
+ assert annotated_int_array is not int_array
+ assert annotated_int_array.base is int_array
+
+ # These ``asarray()`` calls may produce a new view or a copy,
+ # but never the same object.
+ long_int_array = np.asarray(int_array, dtype='l')
+ assert long_int_array is not int_array
+ assert np.asarray(int_array, dtype='q') is not int_array
+ assert np.asarray(long_int_array, dtype='q') is not long_int_array
+ assert np.asarray(int_array, dtype='l') is not np.asarray(int_array, dtype='l')
+ assert np.asarray(int_array, dtype='l').base is np.asarray(int_array, dtype='l').base
equivalent_requirement = np.dtype('i', metadata={'spam': True})
- c = np.asarray(b, dtype=equivalent_requirement)
+ annotated_int_array_alt = np.asarray(annotated_int_array, dtype=equivalent_requirement)
# The descriptors are equivalent, but we have created
# distinct dtype instances.
assert unequal_type == equivalent_requirement
assert unequal_type is not equivalent_requirement
- assert c is not b
- assert c.dtype is equivalent_requirement
+ assert annotated_int_array_alt is not annotated_int_array
+ assert annotated_int_array_alt.dtype is equivalent_requirement