1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
| import pytest
|
| import numpy as np
|
| info = np.__array_namespace_info__()
|
|
| def test_capabilities():
| caps = info.capabilities()
| assert caps["boolean indexing"] is True
| assert caps["data-dependent shapes"] is True
|
| # This will be added in the 2024.12 release of the array API standard.
|
| # assert caps["max rank"] == 64
| # np.zeros((1,)*64)
| # with pytest.raises(ValueError):
| # np.zeros((1,)*65)
|
|
| def test_default_device():
| assert info.default_device() == "cpu" == np.asarray(0).device
|
|
| def test_default_dtypes():
| dtypes = info.default_dtypes()
| assert dtypes["real floating"] == np.float64 == np.asarray(0.0).dtype
| assert dtypes["complex floating"] == np.complex128 == \
| np.asarray(0.0j).dtype
| assert dtypes["integral"] == np.intp == np.asarray(0).dtype
| assert dtypes["indexing"] == np.intp == np.argmax(np.zeros(10)).dtype
|
| with pytest.raises(ValueError, match="Device not understood"):
| info.default_dtypes(device="gpu")
|
|
| def test_dtypes_all():
| dtypes = info.dtypes()
| assert dtypes == {
| "bool": np.bool_,
| "int8": np.int8,
| "int16": np.int16,
| "int32": np.int32,
| "int64": np.int64,
| "uint8": np.uint8,
| "uint16": np.uint16,
| "uint32": np.uint32,
| "uint64": np.uint64,
| "float32": np.float32,
| "float64": np.float64,
| "complex64": np.complex64,
| "complex128": np.complex128,
| }
|
|
| dtype_categories = {
| "bool": {"bool": np.bool_},
| "signed integer": {
| "int8": np.int8,
| "int16": np.int16,
| "int32": np.int32,
| "int64": np.int64,
| },
| "unsigned integer": {
| "uint8": np.uint8,
| "uint16": np.uint16,
| "uint32": np.uint32,
| "uint64": np.uint64,
| },
| "integral": ("signed integer", "unsigned integer"),
| "real floating": {"float32": np.float32, "float64": np.float64},
| "complex floating": {"complex64": np.complex64, "complex128":
| np.complex128},
| "numeric": ("integral", "real floating", "complex floating"),
| }
|
|
| @pytest.mark.parametrize("kind", dtype_categories)
| def test_dtypes_kind(kind):
| expected = dtype_categories[kind]
| if isinstance(expected, tuple):
| assert info.dtypes(kind=kind) == info.dtypes(kind=expected)
| else:
| assert info.dtypes(kind=kind) == expected
|
|
| def test_dtypes_tuple():
| dtypes = info.dtypes(kind=("bool", "integral"))
| assert dtypes == {
| "bool": np.bool_,
| "int8": np.int8,
| "int16": np.int16,
| "int32": np.int32,
| "int64": np.int64,
| "uint8": np.uint8,
| "uint16": np.uint16,
| "uint32": np.uint32,
| "uint64": np.uint64,
| }
|
|
| def test_dtypes_invalid_kind():
| with pytest.raises(ValueError, match="unsupported kind"):
| info.dtypes(kind="invalid")
|
|
| def test_dtypes_invalid_device():
| with pytest.raises(ValueError, match="Device not understood"):
| info.dtypes(device="gpu")
|
|
| def test_devices():
| assert info.devices() == ["cpu"]
|
|
