__init__.py 4.27 KB
Newer Older
quyuanhao123's avatar
quyuanhao123 committed
1
2
3
4
5
6
import os
import importlib
import os.path as osp

import torch

limm's avatar
limm committed
7
__version__ = '2.1.0'
quyuanhao123's avatar
quyuanhao123 committed
8
9

for library in ['_version', '_scatter', '_segment_csr', '_segment_coo']:
limm's avatar
limm committed
10
11
    cuda_spec = importlib.machinery.PathFinder().find_spec(
        f'{library}_cuda', [osp.dirname(__file__)])
quyuanhao123's avatar
quyuanhao123 committed
12
13
    cpu_spec = importlib.machinery.PathFinder().find_spec(
        f'{library}_cpu', [osp.dirname(__file__)])
limm's avatar
limm committed
14
    spec = cuda_spec or cpu_spec
quyuanhao123's avatar
quyuanhao123 committed
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
    if spec is not None:
        torch.ops.load_library(spec.origin)
    elif os.getenv('BUILD_DOCS', '0') != '1':  # pragma: no cover
        raise ImportError(f"Could not find module '{library}_cpu' in "
                          f"{osp.dirname(__file__)}")
    else:  # pragma: no cover
        from .placeholder import cuda_version_placeholder
        torch.ops.torch_scatter.cuda_version = cuda_version_placeholder

        from .placeholder import scatter_placeholder
        torch.ops.torch_scatter.scatter_mul = scatter_placeholder

        from .placeholder import scatter_arg_placeholder
        torch.ops.torch_scatter.scatter_min = scatter_arg_placeholder
        torch.ops.torch_scatter.scatter_max = scatter_arg_placeholder

        from .placeholder import segment_csr_placeholder
        from .placeholder import segment_csr_arg_placeholder
        from .placeholder import gather_csr_placeholder
        torch.ops.torch_scatter.segment_sum_csr = segment_csr_placeholder
        torch.ops.torch_scatter.segment_mean_csr = segment_csr_placeholder
        torch.ops.torch_scatter.segment_min_csr = segment_csr_arg_placeholder
        torch.ops.torch_scatter.segment_max_csr = segment_csr_arg_placeholder
        torch.ops.torch_scatter.gather_csr = gather_csr_placeholder

        from .placeholder import segment_coo_placeholder
        from .placeholder import segment_coo_arg_placeholder
        from .placeholder import gather_coo_placeholder
        torch.ops.torch_scatter.segment_sum_coo = segment_coo_placeholder
        torch.ops.torch_scatter.segment_mean_coo = segment_coo_placeholder
        torch.ops.torch_scatter.segment_min_coo = segment_coo_arg_placeholder
        torch.ops.torch_scatter.segment_max_coo = segment_coo_arg_placeholder
        torch.ops.torch_scatter.gather_coo = gather_coo_placeholder

cuda_version = torch.ops.torch_scatter.cuda_version()
limm's avatar
limm committed
50
51
52
is_not_hip = torch.version.hip is None
is_cuda = torch.version.cuda is not None
if is_not_hip and is_cuda and cuda_version != -1:  # pragma: no cover
quyuanhao123's avatar
quyuanhao123 committed
53
54
55
56
    if cuda_version < 10000:
        major, minor = int(str(cuda_version)[0]), int(str(cuda_version)[2])
    else:
        major, minor = int(str(cuda_version)[0:2]), int(str(cuda_version)[3])
limm's avatar
limm committed
57
58
59
60
61
62
63
64
65
    t_major, t_minor = [int(x) for x in torch.version.cuda.split('.')]

    if t_major != major:
        raise RuntimeError(
            f'Detected that PyTorch and torch_scatter were compiled with '
            f'different CUDA versions. PyTorch has CUDA version '
            f'{t_major}.{t_minor} and torch_scatter has CUDA version '
            f'{major}.{minor}. Please reinstall the torch_scatter that '
            f'matches your PyTorch install.')
quyuanhao123's avatar
quyuanhao123 committed
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

from .scatter import scatter_sum, scatter_add, scatter_mul  # noqa
from .scatter import scatter_mean, scatter_min, scatter_max, scatter  # noqa
from .segment_csr import segment_sum_csr, segment_add_csr  # noqa
from .segment_csr import segment_mean_csr, segment_min_csr  # noqa
from .segment_csr import segment_max_csr, segment_csr, gather_csr  # noqa
from .segment_coo import segment_sum_coo, segment_add_coo  # noqa
from .segment_coo import segment_mean_coo, segment_min_coo  # noqa
from .segment_coo import segment_max_coo, segment_coo, gather_coo  # noqa
from .composite import scatter_std, scatter_logsumexp  # noqa
from .composite import scatter_softmax, scatter_log_softmax  # noqa

__all__ = [
    'scatter_sum',
    'scatter_add',
    'scatter_mul',
    'scatter_mean',
    'scatter_min',
    'scatter_max',
    'scatter',
    'segment_sum_csr',
    'segment_add_csr',
    'segment_mean_csr',
    'segment_min_csr',
    'segment_max_csr',
    'segment_csr',
    'gather_csr',
    'segment_sum_coo',
    'segment_add_coo',
    'segment_mean_coo',
    'segment_min_coo',
    'segment_max_coo',
    'segment_coo',
    'gather_coo',
    'scatter_std',
    'scatter_logsumexp',
    'scatter_softmax',
    'scatter_log_softmax',
    'torch_scatter',
    '__version__',
]