test_batched_heterograph.py 17.1 KB
Newer Older
1
2
import dgl
import backend as F
Mufei Li's avatar
Mufei Li committed
3
import unittest
4
import pytest
5
6

from dgl.base import ALL
7
from utils import parametrize_dtype
8
from test_utils import check_graph_equal, get_cases
9

Jinjing Zhou's avatar
Jinjing Zhou committed
10

11
12
13
14
15
16
17
18
19
20
21
22
23
24
def check_equivalence_between_heterographs(g1, g2, node_attrs=None, edge_attrs=None):
    assert g1.ntypes == g2.ntypes
    assert g1.etypes == g2.etypes
    assert g1.canonical_etypes == g2.canonical_etypes

    for nty in g1.ntypes:
        assert g1.number_of_nodes(nty) == g2.number_of_nodes(nty)

    for ety in g1.etypes:
        if len(g1._etype2canonical[ety]) > 0:
            assert g1.number_of_edges(ety) == g2.number_of_edges(ety)

    for ety in g1.canonical_etypes:
        assert g1.number_of_edges(ety) == g2.number_of_edges(ety)
25
26
        src1, dst1, eid1 = g1.edges(etype=ety, form='all')
        src2, dst2, eid2 = g2.edges(etype=ety, form='all')
27
28
        assert F.allclose(src1, src2)
        assert F.allclose(dst1, dst2)
29
        assert F.allclose(eid1, eid2)
30
31
32

    if node_attrs is not None:
        for nty in node_attrs.keys():
33
34
            if g1.number_of_nodes(nty) == 0:
                continue
35
            for feat_name in node_attrs[nty]:
Jinjing Zhou's avatar
Jinjing Zhou committed
36
37
                assert F.allclose(
                    g1.nodes[nty].data[feat_name], g2.nodes[nty].data[feat_name])
38
39
40

    if edge_attrs is not None:
        for ety in edge_attrs.keys():
41
42
            if g1.number_of_edges(ety) == 0:
                continue
43
            for feat_name in edge_attrs[ety]:
Jinjing Zhou's avatar
Jinjing Zhou committed
44
45
46
                assert F.allclose(
                    g1.edges[ety].data[feat_name], g2.edges[ety].data[feat_name])

47

48
@pytest.mark.parametrize('gs', get_cases(['two_hetero_batch']))
49
@parametrize_dtype
50
def test_topology(gs, idtype):
51
    """Test batching two DGLHeteroGraphs where some nodes are isolated in some relations"""
52
53
54
    g1, g2 = gs
    g1 = g1.astype(idtype).to(F.ctx())
    g2 = g2.astype(idtype).to(F.ctx())
55
    bg = dgl.batch([g1, g2])
56

57
58
    assert bg.idtype == idtype
    assert bg.device == F.ctx()
59
60
61
62
63
64
65
    assert bg.ntypes == g2.ntypes
    assert bg.etypes == g2.etypes
    assert bg.canonical_etypes == g2.canonical_etypes
    assert bg.batch_size == 2

    # Test number of nodes
    for ntype in bg.ntypes:
66
67
        print(ntype)
        assert F.asnumpy(bg.batch_num_nodes(ntype)).tolist() == [
68
69
            g1.number_of_nodes(ntype), g2.number_of_nodes(ntype)]
        assert bg.number_of_nodes(ntype) == (
Jinjing Zhou's avatar
Jinjing Zhou committed
70
            g1.number_of_nodes(ntype) + g2.number_of_nodes(ntype))
71
72

    # Test number of edges
73
    for etype in bg.canonical_etypes:
74
        assert F.asnumpy(bg.batch_num_edges(etype)).tolist() == [
75
76
77
78
79
80
            g1.number_of_edges(etype), g2.number_of_edges(etype)]
        assert bg.number_of_edges(etype) == (
            g1.number_of_edges(etype) + g2.number_of_edges(etype))

    # Test relabeled nodes
    for ntype in bg.ntypes:
Jinjing Zhou's avatar
Jinjing Zhou committed
81
82
        assert list(F.asnumpy(bg.nodes(ntype))) == list(
            range(bg.number_of_nodes(ntype)))
83
84

    # Test relabeled edges
85
    src, dst = bg.edges(etype=('user', 'follows', 'user'))
86
87
    assert list(F.asnumpy(src)) == [0, 1, 4, 5]
    assert list(F.asnumpy(dst)) == [1, 2, 5, 6]
88
    src, dst = bg.edges(etype=('user', 'follows', 'developer'))
89
90
    assert list(F.asnumpy(src)) == [0, 1, 4, 5]
    assert list(F.asnumpy(dst)) == [1, 2, 4, 5]
91
    src, dst, eid = bg.edges(etype='plays', form='all')
92
93
94
95
96
    assert list(F.asnumpy(src)) == [0, 1, 2, 3, 4, 5, 6]
    assert list(F.asnumpy(dst)) == [0, 0, 1, 1, 2, 2, 3]
    assert list(F.asnumpy(eid)) == [0, 1, 2, 3, 4, 5, 6]

    # Test unbatching graphs
97
    g3, g4 = dgl.unbatch(bg)
98
99
100
    check_equivalence_between_heterographs(g1, g3)
    check_equivalence_between_heterographs(g2, g4)

101
102
103
104
105
106
    # Test dtype cast
    if idtype == "int32":
        bg_cast = bg.long()
    else:
        bg_cast = bg.int()
    assert bg.batch_size == bg_cast.batch_size
107

108
109
110
    # Test local var
    bg_local = bg.local_var()
    assert bg.batch_size == bg_local.batch_size
111

Jinjing Zhou's avatar
Jinjing Zhou committed
112

113
@parametrize_dtype
114
def test_batching_batched(idtype):
115
116
    """Test batching a DGLHeteroGraph and a BatchedDGLHeteroGraph."""
    g1 = dgl.heterograph({
117
118
        ('user', 'follows', 'user'): ([0, 1], [1, 2]),
        ('user', 'plays', 'game'): ([0, 1], [0, 0])
119
    }, idtype=idtype, device=F.ctx())
120
    g2 = dgl.heterograph({
121
122
        ('user', 'follows', 'user'): ([0, 1], [1, 2]),
        ('user', 'plays', 'game'): ([0, 1], [0, 0])
123
124
    }, idtype=idtype, device=F.ctx())
    bg1 = dgl.batch([g1, g2])
125
    g3 = dgl.heterograph({
126
127
        ('user', 'follows', 'user'): ([0], [1]),
        ('user', 'plays', 'game'): ([1], [0])
128
129
130
131
    }, idtype=idtype, device=F.ctx())
    bg2 = dgl.batch([bg1, g3])
    assert bg2.idtype == idtype
    assert bg2.device == F.ctx()
132
133
134
135
136
137
138
    assert bg2.ntypes == g3.ntypes
    assert bg2.etypes == g3.etypes
    assert bg2.canonical_etypes == g3.canonical_etypes
    assert bg2.batch_size == 3

    # Test number of nodes
    for ntype in bg2.ntypes:
139
        assert F.asnumpy(bg2.batch_num_nodes(ntype)).tolist() == [
140
141
            g1.number_of_nodes(ntype), g2.number_of_nodes(ntype), g3.number_of_nodes(ntype)]
        assert bg2.number_of_nodes(ntype) == (
Jinjing Zhou's avatar
Jinjing Zhou committed
142
            g1.number_of_nodes(ntype) + g2.number_of_nodes(ntype) + g3.number_of_nodes(ntype))
143
144
145

    # Test number of edges
    for etype in bg2.canonical_etypes:
146
        assert F.asnumpy(bg2.batch_num_edges(etype)).tolist() == [
147
148
            g1.number_of_edges(etype), g2.number_of_edges(etype), g3.number_of_edges(etype)]
        assert bg2.number_of_edges(etype) == (
Jinjing Zhou's avatar
Jinjing Zhou committed
149
            g1.number_of_edges(etype) + g2.number_of_edges(etype) + g3.number_of_edges(etype))
150
151
152

    # Test relabeled nodes
    for ntype in bg2.ntypes:
Jinjing Zhou's avatar
Jinjing Zhou committed
153
154
        assert list(F.asnumpy(bg2.nodes(ntype))) == list(
            range(bg2.number_of_nodes(ntype)))
155
156

    # Test relabeled edges
157
    src, dst = bg2.edges(etype='follows')
158
159
    assert list(F.asnumpy(src)) == [0, 1, 3, 4, 6]
    assert list(F.asnumpy(dst)) == [1, 2, 4, 5, 7]
160
    src, dst = bg2.edges(etype='plays')
161
162
163
164
    assert list(F.asnumpy(src)) == [0, 1, 3, 4, 7]
    assert list(F.asnumpy(dst)) == [0, 0, 1, 1, 2]

    # Test unbatching graphs
165
    g4, g5, g6 = dgl.unbatch(bg2)
166
167
168
169
    check_equivalence_between_heterographs(g1, g4)
    check_equivalence_between_heterographs(g2, g5)
    check_equivalence_between_heterographs(g3, g6)

Jinjing Zhou's avatar
Jinjing Zhou committed
170

171
@parametrize_dtype
172
def test_features(idtype):
173
174
    """Test the features of batched DGLHeteroGraphs"""
    g1 = dgl.heterograph({
175
176
        ('user', 'follows', 'user'): ([0, 1], [1, 2]),
        ('user', 'plays', 'game'): ([0, 1], [0, 0])
177
    }, idtype=idtype, device=F.ctx())
178
179
180
181
182
183
184
185
186
    g1.nodes['user'].data['h1'] = F.tensor([[0.], [1.], [2.]])
    g1.nodes['user'].data['h2'] = F.tensor([[3.], [4.], [5.]])
    g1.nodes['game'].data['h1'] = F.tensor([[0.]])
    g1.nodes['game'].data['h2'] = F.tensor([[1.]])
    g1.edges['follows'].data['h1'] = F.tensor([[0.], [1.]])
    g1.edges['follows'].data['h2'] = F.tensor([[2.], [3.]])
    g1.edges['plays'].data['h1'] = F.tensor([[0.], [1.]])

    g2 = dgl.heterograph({
187
188
        ('user', 'follows', 'user'): ([0, 1], [1, 2]),
        ('user', 'plays', 'game'): ([0, 1], [0, 0])
189
    }, idtype=idtype, device=F.ctx())
190
191
192
193
194
195
196
197
    g2.nodes['user'].data['h1'] = F.tensor([[0.], [1.], [2.]])
    g2.nodes['user'].data['h2'] = F.tensor([[3.], [4.], [5.]])
    g2.nodes['game'].data['h1'] = F.tensor([[0.]])
    g2.nodes['game'].data['h2'] = F.tensor([[1.]])
    g2.edges['follows'].data['h1'] = F.tensor([[0.], [1.]])
    g2.edges['follows'].data['h2'] = F.tensor([[2.], [3.]])
    g2.edges['plays'].data['h1'] = F.tensor([[0.], [1.]])

198
199
    # test default setting
    bg = dgl.batch([g1, g2])
200
201
202
203
204
205
206
207
208
209
    assert F.allclose(bg.nodes['user'].data['h1'],
                      F.cat([g1.nodes['user'].data['h1'], g2.nodes['user'].data['h1']], dim=0))
    assert F.allclose(bg.nodes['user'].data['h2'],
                      F.cat([g1.nodes['user'].data['h2'], g2.nodes['user'].data['h2']], dim=0))
    assert F.allclose(bg.nodes['game'].data['h1'],
                      F.cat([g1.nodes['game'].data['h1'], g2.nodes['game'].data['h1']], dim=0))
    assert F.allclose(bg.nodes['game'].data['h2'],
                      F.cat([g1.nodes['game'].data['h2'], g2.nodes['game'].data['h2']], dim=0))
    assert F.allclose(bg.edges['follows'].data['h1'],
                      F.cat([g1.edges['follows'].data['h1'], g2.edges['follows'].data['h1']], dim=0))
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
    assert F.allclose(bg.edges['follows'].data['h2'],
                      F.cat([g1.edges['follows'].data['h2'], g2.edges['follows'].data['h2']], dim=0))
    assert F.allclose(bg.edges['plays'].data['h1'],
                      F.cat([g1.edges['plays'].data['h1'], g2.edges['plays'].data['h1']], dim=0))

    # test specifying ndata/edata
    bg = dgl.batch([g1, g2], ndata=['h2'], edata=['h1'])
    assert F.allclose(bg.nodes['user'].data['h2'],
                      F.cat([g1.nodes['user'].data['h2'], g2.nodes['user'].data['h2']], dim=0))
    assert F.allclose(bg.nodes['game'].data['h2'],
                      F.cat([g1.nodes['game'].data['h2'], g2.nodes['game'].data['h2']], dim=0))
    assert F.allclose(bg.edges['follows'].data['h1'],
                      F.cat([g1.edges['follows'].data['h1'], g2.edges['follows'].data['h1']], dim=0))
    assert F.allclose(bg.edges['plays'].data['h1'],
                      F.cat([g1.edges['plays'].data['h1'], g2.edges['plays'].data['h1']], dim=0))
    assert 'h1' not in bg.nodes['user'].data
    assert 'h1' not in bg.nodes['game'].data
    assert 'h2' not in bg.edges['follows'].data
228
229

    # Test unbatching graphs
230
    g3, g4 = dgl.unbatch(bg)
231
232
    check_equivalence_between_heterographs(
        g1, g3,
233
        node_attrs={'user': ['h2'], 'game': ['h2']},
234
235
236
        edge_attrs={('user', 'follows', 'user'): ['h1']})
    check_equivalence_between_heterographs(
        g2, g4,
237
        node_attrs={'user': ['h2'], 'game': ['h2']},
238
239
        edge_attrs={('user', 'follows', 'user'): ['h1']})

240
241
242
243
    # test legacy
    bg = dgl.batch([g1, g2], edge_attrs=['h1'])
    assert 'h2' not in bg.edges['follows'].data.keys()

Jinjing Zhou's avatar
Jinjing Zhou committed
244

245
@unittest.skipIf(F.backend_name == 'mxnet', reason="MXNet does not support split array with zero-length segment.")
246
@parametrize_dtype
247
def test_empty_relation(idtype):
248
249
    """Test the features of batched DGLHeteroGraphs"""
    g1 = dgl.heterograph({
250
251
        ('user', 'follows', 'user'): ([0, 1], [1, 2]),
        ('user', 'plays', 'game'): ([], [])
252
    }, idtype=idtype, device=F.ctx())
253
254
255
256
257
258
    g1.nodes['user'].data['h1'] = F.tensor([[0.], [1.], [2.]])
    g1.nodes['user'].data['h2'] = F.tensor([[3.], [4.], [5.]])
    g1.edges['follows'].data['h1'] = F.tensor([[0.], [1.]])
    g1.edges['follows'].data['h2'] = F.tensor([[2.], [3.]])

    g2 = dgl.heterograph({
259
260
        ('user', 'follows', 'user'): ([0, 1], [1, 2]),
        ('user', 'plays', 'game'): ([0, 1], [0, 0])
261
    }, idtype=idtype, device=F.ctx())
262
263
264
265
266
267
268
269
    g2.nodes['user'].data['h1'] = F.tensor([[0.], [1.], [2.]])
    g2.nodes['user'].data['h2'] = F.tensor([[3.], [4.], [5.]])
    g2.nodes['game'].data['h1'] = F.tensor([[0.]])
    g2.nodes['game'].data['h2'] = F.tensor([[1.]])
    g2.edges['follows'].data['h1'] = F.tensor([[0.], [1.]])
    g2.edges['follows'].data['h2'] = F.tensor([[2.], [3.]])
    g2.edges['plays'].data['h1'] = F.tensor([[0.], [1.]])

270
271
272
273
274
275
276
277
278
279
280
    bg = dgl.batch([g1, g2])

    # Test number of nodes
    for ntype in bg.ntypes:
        assert F.asnumpy(bg.batch_num_nodes(ntype)).tolist() == [
            g1.number_of_nodes(ntype), g2.number_of_nodes(ntype)]

    # Test number of edges
    for etype in bg.canonical_etypes:
        assert F.asnumpy(bg.batch_num_edges(etype)).tolist() == [
            g1.number_of_edges(etype), g2.number_of_edges(etype)]
281

282
    # Test features
283
284
285
286
287
288
289
290
    assert F.allclose(bg.nodes['user'].data['h1'],
                      F.cat([g1.nodes['user'].data['h1'], g2.nodes['user'].data['h1']], dim=0))
    assert F.allclose(bg.nodes['user'].data['h2'],
                      F.cat([g1.nodes['user'].data['h2'], g2.nodes['user'].data['h2']], dim=0))
    assert F.allclose(bg.nodes['game'].data['h1'], g2.nodes['game'].data['h1'])
    assert F.allclose(bg.nodes['game'].data['h2'], g2.nodes['game'].data['h2'])
    assert F.allclose(bg.edges['follows'].data['h1'],
                      F.cat([g1.edges['follows'].data['h1'], g2.edges['follows'].data['h1']], dim=0))
Jinjing Zhou's avatar
Jinjing Zhou committed
291
292
    assert F.allclose(bg.edges['plays'].data['h1'],
                      g2.edges['plays'].data['h1'])
293
294

    # Test unbatching graphs
295
    g3, g4 = dgl.unbatch(bg)
296
297
298
299
300
301
302
303
304
305
    check_equivalence_between_heterographs(
        g1, g3,
        node_attrs={'user': ['h1', 'h2'], 'game': ['h1', 'h2']},
        edge_attrs={('user', 'follows', 'user'): ['h1']})
    check_equivalence_between_heterographs(
        g2, g4,
        node_attrs={'user': ['h1', 'h2'], 'game': ['h1', 'h2']},
        edge_attrs={('user', 'follows', 'user'): ['h1']})

    # Test graphs without edges
306
307
    g1 = dgl.heterograph({('u', 'r', 'v'): ([], [])}, {'u': 0, 'v': 4})
    g2 = dgl.heterograph({('u', 'r', 'v'): ([], [])}, {'u': 1, 'v': 5})
308
    dgl.batch([g1, g2])
309

Jinjing Zhou's avatar
Jinjing Zhou committed
310

Mufei Li's avatar
Mufei Li committed
311
@parametrize_dtype
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
def test_unbatch2(idtype):
    # batch 3 graphs but unbatch to 2
    g1 = dgl.graph(([0, 1, 2], [1, 2, 3]), idtype=idtype, device=F.ctx())
    g2 = dgl.graph(([0, 1, 2], [1, 2, 3]), idtype=idtype, device=F.ctx())
    g3 = dgl.graph(([0, 1, 2], [1, 2, 3]), idtype=idtype, device=F.ctx())
    bg = dgl.batch([g1, g2, g3])
    bnn = F.tensor([8, 4])
    bne = F.tensor([6, 3])
    f1, f2 = dgl.unbatch(bg, node_split=bnn, edge_split=bne)
    u, v = f1.edges(order='eid')
    assert F.allclose(u, F.tensor([0, 1, 2, 4, 5, 6]))
    assert F.allclose(v, F.tensor([1, 2, 3, 5, 6, 7]))
    u, v = f2.edges(order='eid')
    assert F.allclose(u, F.tensor([0, 1, 2]))
    assert F.allclose(v, F.tensor([1, 2, 3]))

    # batch 2 but unbatch to 3
    bg = dgl.batch([f1, f2])
    gg1, gg2, gg3 = dgl.unbatch(bg, F.tensor([4, 4, 4]), F.tensor([3, 3, 3]))
    check_graph_equal(g1, gg1)
    check_graph_equal(g2, gg2)
    check_graph_equal(g3, gg3)
334

Jinjing Zhou's avatar
Jinjing Zhou committed
335

336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
@parametrize_dtype
def test_slice_batch(idtype):
    g1 = dgl.heterograph({
        ('user', 'follows', 'user'): ([0, 1], [1, 2]),
        ('user', 'plays', 'game'): ([], []),
        ('user', 'follows', 'game'): ([0, 0], [1, 4])
    }, idtype=idtype, device=F.ctx())
    g2 = dgl.heterograph({
        ('user', 'follows', 'user'): ([0, 1], [1, 2]),
        ('user', 'plays', 'game'): ([0, 1], [0, 0]),
        ('user', 'follows', 'game'): ([0, 1], [1, 4])
    }, num_nodes_dict={'user': 4, 'game': 6}, idtype=idtype, device=F.ctx())
    g3 = dgl.heterograph({
        ('user', 'follows', 'user'): ([0], [2]),
        ('user', 'plays', 'game'): ([1, 2], [3, 4]),
        ('user', 'follows', 'game'): ([], [])
    }, idtype=idtype, device=F.ctx())
    g_list = [g1, g2, g3]
    bg = dgl.batch(g_list)
    bg.nodes['user'].data['h1'] = F.randn((bg.num_nodes('user'), 2))
    bg.nodes['user'].data['h2'] = F.randn((bg.num_nodes('user'), 5))
    bg.edges[('user', 'follows', 'user')].data['h1'] = F.randn((
        bg.num_edges(('user', 'follows', 'user')), 2))
    for fmat in ['coo', 'csr', 'csc']:
        bg = bg.formats(fmat)
        for i in range(len(g_list)):
            g_i = g_list[i]
            g_slice = dgl.slice_batch(bg, i)
            assert g_i.ntypes == g_slice.ntypes
            assert g_i.canonical_etypes == g_slice.canonical_etypes
            assert g_i.idtype == g_slice.idtype
            assert g_i.device == g_slice.device
            for nty in g_i.ntypes:
                assert g_i.num_nodes(nty) == g_slice.num_nodes(nty)
                for feat in g_i.nodes[nty].data:
                    assert F.allclose(g_i.nodes[nty].data[feat], g_slice.nodes[nty].data[feat])

            for ety in g_i.canonical_etypes:
                assert g_i.num_edges(ety) == g_slice.num_edges(ety)
                for feat in g_i.edges[ety].data:
                    assert F.allclose(g_i.edges[ety].data[feat], g_slice.edges[ety].data[feat])


379
380
@parametrize_dtype
def test_batch_keeps_empty_data(idtype):
Jinjing Zhou's avatar
Jinjing Zhou committed
381
382
    g1 = dgl.heterograph({("a", "to", "a"): ([], [])}
                         ).astype(idtype).to(F.ctx())
383
    g1.nodes["a"].data["nh"] = F.tensor([])
Jinjing Zhou's avatar
Jinjing Zhou committed
384
385
386
    g1.edges[("a", "to", "a")].data["eh"] = F.tensor([])
    g2 = dgl.heterograph({("a", "to", "a"): ([], [])}
                         ).astype(idtype).to(F.ctx())
387
    g2.nodes["a"].data["nh"] = F.tensor([])
Jinjing Zhou's avatar
Jinjing Zhou committed
388
    g2.edges[("a", "to", "a")].data["eh"] = F.tensor([])
389
390
391
392
    g = dgl.batch([g1, g2])
    assert "nh" in g.nodes["a"].data
    assert "eh" in g.edges[("a", "to", "a")].data

Jinjing Zhou's avatar
Jinjing Zhou committed
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413

@unittest.skipIf(F._default_context_str == 'gpu', reason="Issue is not related with GPU")
def test_batch_netypes():
    # Test for https://github.com/dmlc/dgl/issues/2808
    import networkx as nx
    B = nx.DiGraph()
    B.add_nodes_from([1, 2, 3, 4], bipartite=0,
                     some_attr=F.tensor([1, 2, 3, 4], dtype=F.float32))
    B.add_nodes_from(["a", "b", "c"], bipartite=1)
    B.add_edges_from([(1, "a"), (1, "b"), (2, "b"),
                      (2, "c"), (3, "c"), (4, "a")])

    g_dict = {0: dgl.bipartite_from_networkx(B, 'A', 'e', 'B'),
              1: dgl.bipartite_from_networkx(B, 'B', 'e', 'A'),
              2: dgl.bipartite_from_networkx(B, 'A', 'e', 'B', u_attrs=['some_attr']),
              3: dgl.bipartite_from_networkx(B, 'B', 'e', 'A', u_attrs=['some_attr'])
              }
    for _, g in g_dict.items():
        dgl.batch((g, g, g))


414
if __name__ == '__main__':
Jinjing Zhou's avatar
Jinjing Zhou committed
415
416
417
    # test_topology('int32')
    # test_batching_batched('int32')
    # test_batched_features('int32')
418
    # test_empty_relation('int64')
Jinjing Zhou's avatar
Jinjing Zhou committed
419
    # test_to_device('int32')
420
    pass