test_serialize.py 13.8 KB
Newer Older
1
2
3
4
import os
import tempfile
import time
import unittest
5
import warnings
6

VoVAllen's avatar
VoVAllen committed
7
8
9
import backend as F

import dgl
10
import dgl.ndarray as nd
11
12
13
import numpy as np
import pytest
import scipy as sp
14
from dgl.data.utils import load_labels, load_tensors, save_tensors
VoVAllen's avatar
VoVAllen committed
15
16
17
18

np.random.seed(44)


19
def generate_rand_graph(n):
20
21
22
    arr = (sp.sparse.random(n, n, density=0.1, format="coo") != 0).astype(
        np.int64
    )
23
    return dgl.from_scipy(arr)
VoVAllen's avatar
VoVAllen committed
24
25


26
def construct_graph(n):
VoVAllen's avatar
VoVAllen committed
27
    g_list = []
28
29
    for _ in range(n):
        g = generate_rand_graph(30)
Hongzhi (Steve), Chen's avatar
Hongzhi (Steve), Chen committed
30
31
32
        g.edata["e1"] = F.randn((g.num_edges(), 32))
        g.edata["e2"] = F.ones((g.num_edges(), 32))
        g.ndata["n1"] = F.randn((g.num_nodes(), 64))
VoVAllen's avatar
VoVAllen committed
33
34
35
36
        g_list.append(g)
    return g_list


37
@unittest.skipIf(F._default_context_str == "gpu", reason="GPU not implemented")
38
def test_graph_serialize_with_feature():
VoVAllen's avatar
VoVAllen committed
39
40
41
42
    num_graphs = 100

    t0 = time.time()

43
    g_list = construct_graph(num_graphs)
VoVAllen's avatar
VoVAllen committed
44
45
46
47
48
49
50
51

    t1 = time.time()

    # create a temporary file and immediately release it so DGL can open it.
    f = tempfile.NamedTemporaryFile(delete=False)
    path = f.name
    f.close()

52
    dgl.save_graphs(path, g_list)
VoVAllen's avatar
VoVAllen committed
53
54
55

    t2 = time.time()
    idx_list = np.random.permutation(np.arange(num_graphs)).tolist()
56
    loadg_list, _ = dgl.load_graphs(path, idx_list)
VoVAllen's avatar
VoVAllen committed
57
58
59
60
61
62
63
64
65
66

    t3 = time.time()
    idx = idx_list[0]
    load_g = loadg_list[0]
    print("Save time: {} s".format(t2 - t1))
    print("Load time: {} s".format(t3 - t2))
    print("Graph Construction time: {} s".format(t1 - t0))

    assert F.allclose(load_g.nodes(), g_list[idx].nodes())

67
68
    load_edges = load_g.all_edges("uv", "eid")
    g_edges = g_list[idx].all_edges("uv", "eid")
VoVAllen's avatar
VoVAllen committed
69
70
    assert F.allclose(load_edges[0], g_edges[0])
    assert F.allclose(load_edges[1], g_edges[1])
71
72
73
    assert F.allclose(load_g.edata["e1"], g_list[idx].edata["e1"])
    assert F.allclose(load_g.edata["e2"], g_list[idx].edata["e2"])
    assert F.allclose(load_g.ndata["n1"], g_list[idx].ndata["n1"])
VoVAllen's avatar
VoVAllen committed
74
75
76
77

    os.unlink(path)


78
@unittest.skipIf(F._default_context_str == "gpu", reason="GPU not implemented")
79
def test_graph_serialize_without_feature():
VoVAllen's avatar
VoVAllen committed
80
    num_graphs = 100
81
    g_list = [generate_rand_graph(30) for _ in range(num_graphs)]
VoVAllen's avatar
VoVAllen committed
82
83
84
85
86
87

    # create a temporary file and immediately release it so DGL can open it.
    f = tempfile.NamedTemporaryFile(delete=False)
    path = f.name
    f.close()

88
    dgl.save_graphs(path, g_list)
VoVAllen's avatar
VoVAllen committed
89
90

    idx_list = np.random.permutation(np.arange(num_graphs)).tolist()
91
    loadg_list, _ = dgl.load_graphs(path, idx_list)
VoVAllen's avatar
VoVAllen committed
92
93
94
95
96
97

    idx = idx_list[0]
    load_g = loadg_list[0]

    assert F.allclose(load_g.nodes(), g_list[idx].nodes())

98
99
    load_edges = load_g.all_edges("uv", "eid")
    g_edges = g_list[idx].all_edges("uv", "eid")
VoVAllen's avatar
VoVAllen committed
100
101
102
103
104
    assert F.allclose(load_edges[0], g_edges[0])
    assert F.allclose(load_edges[1], g_edges[1])

    os.unlink(path)

105
106

@unittest.skipIf(F._default_context_str == "gpu", reason="GPU not implemented")
107
def test_graph_serialize_with_labels():
VoVAllen's avatar
VoVAllen committed
108
    num_graphs = 100
109
    g_list = [generate_rand_graph(30) for _ in range(num_graphs)]
VoVAllen's avatar
VoVAllen committed
110
111
112
113
114
115
116
    labels = {"label": F.zeros((num_graphs, 1))}

    # create a temporary file and immediately release it so DGL can open it.
    f = tempfile.NamedTemporaryFile(delete=False)
    path = f.name
    f.close()

117
    dgl.save_graphs(path, g_list, labels)
VoVAllen's avatar
VoVAllen committed
118
119

    idx_list = np.random.permutation(np.arange(num_graphs)).tolist()
120
    loadg_list, l_labels0 = dgl.load_graphs(path, idx_list)
VoVAllen's avatar
VoVAllen committed
121
    l_labels = load_labels(path)
122
123
    assert F.allclose(l_labels["label"], labels["label"])
    assert F.allclose(l_labels0["label"], labels["label"])
VoVAllen's avatar
VoVAllen committed
124
125
126
127
128
129

    idx = idx_list[0]
    load_g = loadg_list[0]

    assert F.allclose(load_g.nodes(), g_list[idx].nodes())

130
131
    load_edges = load_g.all_edges("uv", "eid")
    g_edges = g_list[idx].all_edges("uv", "eid")
VoVAllen's avatar
VoVAllen committed
132
133
134
135
136
137
    assert F.allclose(load_edges[0], g_edges[0])
    assert F.allclose(load_edges[1], g_edges[1])

    os.unlink(path)


138
139
140
141
142
143
def test_serialize_tensors():
    # create a temporary file and immediately release it so DGL can open it.
    f = tempfile.NamedTemporaryFile(delete=False)
    path = f.name
    f.close()

144
145
146
147
    tensor_dict = {
        "a": F.tensor([1, 3, -1, 0], dtype=F.int64),
        "1@1": F.tensor([1.5, 2], dtype=F.float32),
    }
148
149
150
151
152
153
154
155

    save_tensors(path, tensor_dict)

    load_tensor_dict = load_tensors(path)

    for key in tensor_dict:
        assert key in load_tensor_dict
        assert np.array_equal(
156
157
            F.asnumpy(load_tensor_dict[key]), F.asnumpy(tensor_dict[key])
        )
158
159
160
161
162
163
164

    load_nd_dict = load_tensors(path, return_dgl_ndarray=True)

    for key in tensor_dict:
        assert key in load_nd_dict
        assert isinstance(load_nd_dict[key], nd.NDArray)
        assert np.array_equal(
165
166
            load_nd_dict[key].asnumpy(), F.asnumpy(tensor_dict[key])
        )
167
168
169

    os.unlink(path)

170

171
172
173
174
175
176
177
178
179
180
181
182
def test_serialize_empty_dict():
    # create a temporary file and immediately release it so DGL can open it.
    f = tempfile.NamedTemporaryFile(delete=False)
    path = f.name
    f.close()

    tensor_dict = {}

    save_tensors(path, tensor_dict)

    load_tensor_dict = load_tensors(path)
    assert isinstance(load_tensor_dict, dict)
183
    assert len(load_tensor_dict) == 0
184
185

    os.unlink(path)
186

187

188
189
190
191
192
193
def load_old_files(files):
    with warnings.catch_warnings():
        warnings.simplefilter("ignore", category=UserWarning)
        return dgl.load_graphs(os.path.join(os.path.dirname(__file__), files))


194
def test_load_old_files1():
195
    loadg_list, _ = load_old_files("data/1.bin")
196
    idx, num_nodes, edge0, edge1, edata_e1, edata_e2, ndata_n1 = np.load(
197
198
        os.path.join(os.path.dirname(__file__), "data/1.npy"), allow_pickle=True
    )
199
200

    load_g = loadg_list[idx]
201
    load_edges = load_g.all_edges("uv", "eid")
202
203
204

    assert np.allclose(F.asnumpy(load_edges[0]), edge0)
    assert np.allclose(F.asnumpy(load_edges[1]), edge1)
205
206
207
    assert np.allclose(F.asnumpy(load_g.edata["e1"]), edata_e1)
    assert np.allclose(F.asnumpy(load_g.edata["e2"]), edata_e2)
    assert np.allclose(F.asnumpy(load_g.ndata["n1"]), ndata_n1)
208
209
210


def test_load_old_files2():
211
    loadg_list, labels0 = load_old_files("data/2.bin")
212
213
214
215
216
217
    labels1 = load_labels(os.path.join(os.path.dirname(__file__), "data/2.bin"))
    idx, edges0, edges1, np_labels = np.load(
        os.path.join(os.path.dirname(__file__), "data/2.npy"), allow_pickle=True
    )
    assert np.allclose(F.asnumpy(labels0["label"]), np_labels)
    assert np.allclose(F.asnumpy(labels1["label"]), np_labels)
218
219

    load_g = loadg_list[idx]
220
    print(load_g)
221
    load_edges = load_g.all_edges("uv", "eid")
222
223
224
225
    assert np.allclose(F.asnumpy(load_edges[0]), edges0)
    assert np.allclose(F.asnumpy(load_edges[1]), edges1)


226
def create_heterographs(idtype):
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
    g_x = dgl.heterograph(
        {("user", "follows", "user"): ([0, 1, 2], [1, 2, 3])}, idtype=idtype
    )
    g_y = dgl.heterograph(
        {("user", "knows", "user"): ([0, 2], [2, 3])}, idtype=idtype
    ).formats("csr")
    g_x.ndata["h"] = F.randn((4, 3))
    g_x.edata["w"] = F.randn((3, 2))
    g_y.ndata["hh"] = F.ones((4, 5))
    g_y.edata["ww"] = F.randn((2, 10))
    g = dgl.heterograph(
        {
            ("user", "follows", "user"): ([0, 1, 2], [1, 2, 3]),
            ("user", "knows", "user"): ([0, 2], [2, 3]),
        },
        idtype=idtype,
    )
    g.nodes["user"].data["h"] = g_x.ndata["h"]
    g.nodes["user"].data["hh"] = g_y.ndata["hh"]
    g.edges["follows"].data["w"] = g_x.edata["w"]
    g.edges["knows"].data["ww"] = g_y.edata["ww"]
248
249
    return [g, g_x, g_y]

250

251
def create_heterographs2(idtype):
252
253
254
255
256
257
    g_x = dgl.heterograph(
        {("user", "follows", "user"): ([0, 1, 2], [1, 2, 3])}, idtype=idtype
    )
    g_y = dgl.heterograph(
        {("user", "knows", "user"): ([0, 2], [2, 3])}, idtype=idtype
    ).formats("csr")
258
    g_z = dgl.heterograph(
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
        {("user", "knows", "knowledge"): ([0, 1, 3], [2, 3, 4])}, idtype=idtype
    )
    g_x.ndata["h"] = F.randn((4, 3))
    g_x.edata["w"] = F.randn((3, 2))
    g_y.ndata["hh"] = F.ones((4, 5))
    g_y.edata["ww"] = F.randn((2, 10))
    g = dgl.heterograph(
        {
            ("user", "follows", "user"): ([0, 1, 2], [1, 2, 3]),
            ("user", "knows", "user"): ([0, 2], [2, 3]),
            ("user", "knows", "knowledge"): ([0, 1, 3], [2, 3, 4]),
        },
        idtype=idtype,
    )
    g.nodes["user"].data["h"] = g_x.ndata["h"]
    g.edges["follows"].data["w"] = g_x.edata["w"]
    g.nodes["user"].data["hh"] = g_y.ndata["hh"]
    g.edges[("user", "knows", "user")].data["ww"] = g_y.edata["ww"]
277
    return [g, g_x, g_y, g_z]
278

279

280
def test_deserialize_old_heterograph_file():
281
    path = os.path.join(os.path.dirname(__file__), "data/hetero1.bin")
282
    g_list, label_dict = dgl.load_graphs(path)
283
284
285
    assert g_list[0].idtype == F.int64
    assert g_list[3].idtype == F.int32
    assert np.allclose(
286
287
        F.asnumpy(g_list[2].nodes["user"].data["hh"]), np.ones((4, 5))
    )
288
    assert np.allclose(
289
290
291
        F.asnumpy(g_list[5].nodes["user"].data["hh"]), np.ones((4, 5))
    )
    edges = g_list[0]["follows"].edges()
292
293
    assert np.allclose(F.asnumpy(edges[0]), np.array([0, 1, 2]))
    assert np.allclose(F.asnumpy(edges[1]), np.array([1, 2, 3]))
294
295
    assert F.allclose(label_dict["graph_label"], F.ones(54))

296
297

def create_old_heterograph_files():
298
    path = os.path.join(os.path.dirname(__file__), "data/hetero1.bin")
299
    g_list0 = create_heterographs(F.int64) + create_heterographs(F.int32)
300
    labels_dict = {"graph_label": F.ones(54)}
301
    dgl.save_graphs(path, g_list0, labels_dict)
302
303


304
@unittest.skipIf(F._default_context_str == "gpu", reason="GPU not implemented")
305
306
307
308
def test_serialize_heterograph():
    f = tempfile.NamedTemporaryFile(delete=False)
    path = f.name
    f.close()
309
    g_list0 = create_heterographs2(F.int64) + create_heterographs2(F.int32)
310
    dgl.save_graphs(path, g_list0)
311

312
    g_list, _ = dgl.load_graphs(path)
313
    assert g_list[0].idtype == F.int64
314
315
316
317
    assert len(g_list[0].canonical_etypes) == 3
    for i in range(len(g_list0)):
        for j, etypes in enumerate(g_list0[i].canonical_etypes):
            assert g_list[i].canonical_etypes[j] == etypes
318
319
    # assert g_list[1].restrict_format() == 'any'
    # assert g_list[2].restrict_format() == 'csr'
320

321
    assert g_list[4].idtype == F.int32
322
    assert np.allclose(
323
324
        F.asnumpy(g_list[2].nodes["user"].data["hh"]), np.ones((4, 5))
    )
325
    assert np.allclose(
326
327
328
        F.asnumpy(g_list[6].nodes["user"].data["hh"]), np.ones((4, 5))
    )
    edges = g_list[0]["follows"].edges()
329
330
331
332
333
334
    assert np.allclose(F.asnumpy(edges[0]), np.array([0, 1, 2]))
    assert np.allclose(F.asnumpy(edges[1]), np.array([1, 2, 3]))
    for i in range(len(g_list)):
        assert g_list[i].ntypes == g_list0[i].ntypes
        assert g_list[i].etypes == g_list0[i].etypes

335
    # test set feature after load_graph
336
337
    g_list[3].nodes["user"].data["test"] = F.tensor([0, 1, 2, 4])
    g_list[3].edata["test"] = F.tensor([0, 1, 2])
338

339
340
    os.unlink(path)

341
342

@unittest.skipIf(F._default_context_str == "gpu", reason="GPU not implemented")
343
344
345
@pytest.mark.skip(reason="lack of permission on CI")
def test_serialize_heterograph_s3():
    path = "s3://dglci-data-test/graph2.bin"
346
    g_list0 = create_heterographs(F.int64) + create_heterographs(F.int32)
347
    dgl.save_graphs(path, g_list0)
348

349
    g_list = dgl.load_graphs(path, [0, 2, 5])
350
    assert g_list[0].idtype == F.int64
351
    # assert g_list[1].restrict_format() == 'csr'
352
    assert np.allclose(
353
354
        F.asnumpy(g_list[1].nodes["user"].data["hh"]), np.ones((4, 5))
    )
355
    assert np.allclose(
356
357
358
        F.asnumpy(g_list[2].nodes["user"].data["hh"]), np.ones((4, 5))
    )
    edges = g_list[0]["follows"].edges()
359
360
361
362
    assert np.allclose(F.asnumpy(edges[0]), np.array([0, 1, 2]))
    assert np.allclose(F.asnumpy(edges[1]), np.array([1, 2, 3]))


363
364
365
366
367
368
369
370
371
372
373
374
375
@unittest.skipIf(F._default_context_str == "gpu", reason="GPU not implemented")
@pytest.mark.parametrize(
    "formats",
    [
        "coo",
        "csr",
        "csc",
        ["coo", "csc"],
        ["coo", "csr"],
        ["csc", "csr"],
        ["coo", "csr", "csc"],
    ],
)
376
def test_graph_serialize_with_formats(formats):
377
    num_graphs = 100
378
    g_list = [generate_rand_graph(30) for _ in range(num_graphs)]
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442

    # create a temporary file and immediately release it so DGL can open it.
    f = tempfile.NamedTemporaryFile(delete=False)
    path = f.name
    f.close()

    dgl.save_graphs(path, g_list, formats=formats)

    idx_list = np.random.permutation(np.arange(num_graphs)).tolist()
    loadg_list, _ = dgl.load_graphs(path, idx_list)

    idx = idx_list[0]
    load_g = loadg_list[0]
    g_formats = load_g.formats()

    # verify formats
    if not isinstance(formats, list):
        formats = [formats]
    for fmt in formats:
        assert fmt in g_formats["created"]

    assert F.allclose(load_g.nodes(), g_list[idx].nodes())

    load_edges = load_g.all_edges("uv", "eid")
    g_edges = g_list[idx].all_edges("uv", "eid")
    assert F.allclose(load_edges[0], g_edges[0])
    assert F.allclose(load_edges[1], g_edges[1])

    os.unlink(path)


@unittest.skipIf(F._default_context_str == "gpu", reason="GPU not implemented")
def test_graph_serialize_with_restricted_formats():
    g = dgl.rand_graph(100, 200)
    g = g.formats(["coo"])
    g_list = [g]

    # create a temporary file and immediately release it so DGL can open it.
    f = tempfile.NamedTemporaryFile(delete=False)
    path = f.name
    f.close()

    expect_except = False
    try:
        dgl.save_graphs(path, g_list, formats=["csr"])
    except:
        expect_except = True
    assert expect_except

    os.unlink(path)


@unittest.skipIf(F._default_context_str == "gpu", reason="GPU not implemented")
def test_deserialize_old_graph():
    num_nodes = 100
    num_edges = 200
    path = os.path.join(os.path.dirname(__file__), "data/graph_0.9a220622.dgl")
    g_list, _ = dgl.load_graphs(path)
    g = g_list[0]
    assert "coo" in g.formats()["created"]
    assert "csr" in g.formats()["not created"]
    assert "csc" in g.formats()["not created"]
    assert num_nodes == g.num_nodes()
    assert num_edges == g.num_edges()