Skip to content

GitLab

Switch branch/tag
Find file Normal viewHistoryPermalink
test_pickle.py 3.63 KB
Newer Older
Gan Quan's avatar
Pickling support (#155)  
Gan Quan committed
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
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150 
import dgl
from dgl.frame import Frame, FrameRef, Column
from dgl.graph_index import create_graph_index
from dgl.utils import toindex
import dgl.backend as backend
import dgl.function as F
import utils as U
import torch
import pickle
import io

def _reconstruct_pickle(obj):
    f = io.BytesIO()
    pickle.dump(obj, f)
    f.seek(0)
    obj = pickle.load(f)
    f.close()

    return obj

def test_pickling_index():
    i = toindex([1, 2, 3])
    i.tousertensor()
    i.todgltensor() # construct a dgl tensor which is unpicklable

    i2 = _reconstruct_pickle(i)

    assert torch.equal(i2.tousertensor(), i.tousertensor())


def test_pickling_graph_index():
    gi = create_graph_index()
    gi.add_nodes(3)
    src_idx = toindex([0, 0])
    dst_idx = toindex([1, 2])
    gi.add_edges(src_idx, dst_idx)

    gi2 = _reconstruct_pickle(gi)

    assert gi2.number_of_nodes() == gi.number_of_nodes()
    src_idx2, dst_idx2, _ = gi2.edges()
    assert torch.equal(src_idx.tousertensor(), src_idx2.tousertensor())
    assert torch.equal(dst_idx.tousertensor(), dst_idx2.tousertensor())


def test_pickling_frame():
    x = torch.randn(3, 7)
    y = torch.randn(3, 5)

    c = Column(x)

    c2 = _reconstruct_pickle(c)
    assert U.allclose(c.data, c2.data)

    fr = Frame({'x': x, 'y': y})

    fr2 = _reconstruct_pickle(fr)
    assert U.allclose(fr2['x'].data, x)
    assert U.allclose(fr2['y'].data, y)

    fr = Frame()


def _assert_is_identical(g, g2):
    assert g.number_of_nodes() == g2.number_of_nodes()
    src, dst = g.all_edges()
    src2, dst2 = g2.all_edges()
    assert torch.equal(src, src2)
    assert torch.equal(dst, dst2)

    assert len(g.ndata) == len(g2.ndata)
    assert len(g.edata) == len(g2.edata)
    for k in g.ndata:
        assert U.allclose(g.ndata[k], g2.ndata[k])
    for k in g.edata:
        assert U.allclose(g.edata[k], g2.edata[k])


def _global_message_func(nodes):
    return {'x': nodes.data['x']}

def test_pickling_graph():
    # graph structures and frames are pickled
    g = dgl.DGLGraph()
    g.add_nodes(3)
    src = torch.LongTensor([0, 0])
    dst = torch.LongTensor([1, 2])
    g.add_edges(src, dst)

    x = torch.randn(3, 7)
    y = torch.randn(3, 5)
    a = torch.randn(2, 6)
    b = torch.randn(2, 4)

    g.ndata['x'] = x
    g.ndata['y'] = y
    g.edata['a'] = a
    g.edata['b'] = b

    # registered functions are pickled
    g.register_message_func(_global_message_func)
    reduce_func = F.sum('x', 'x')
    g.register_reduce_func(reduce_func)

    # custom attributes should be pickled
    g.foo = 2

    new_g = _reconstruct_pickle(g)

    _assert_is_identical(g, new_g)
    assert new_g.foo == 2
    assert new_g._message_func == _global_message_func
    assert isinstance(new_g._reduce_func, type(reduce_func))
    assert new_g._reduce_func._name == 'sum'
    assert new_g._reduce_func.op == backend.sum
    assert new_g._reduce_func.msg_field == 'x'
    assert new_g._reduce_func.out_field == 'x'

    # test batched graph with partial set case
    g2 = dgl.DGLGraph()
    g2.add_nodes(4)
    src2 = torch.LongTensor([0, 1])
    dst2 = torch.LongTensor([2, 3])
    g2.add_edges(src2, dst2)

    x2 = torch.randn(4, 7)
    y2 = torch.randn(3, 5)
    a2 = torch.randn(2, 6)
    b2 = torch.randn(2, 4)

    g2.ndata['x'] = x2
    g2.nodes[[0, 1, 3]].data['y'] = y2
    g2.edata['a'] = a2
    g2.edata['b'] = b2

    bg = dgl.batch([g, g2])

    bg2 = _reconstruct_pickle(bg)

    _assert_is_identical(bg, bg2)
    new_g, new_g2 = dgl.unbatch(bg2)
    _assert_is_identical(g, new_g)
    _assert_is_identical(g2, new_g2)


if __name__ == '__main__':
    test_pickling_index()
    test_pickling_graph_index()
    test_pickling_frame()
    test_pickling_graph()