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Unverified Commit 3e43d7b8 authored by Minjie Wang's avatar Minjie Wang Committed by GitHub
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[Test] Lower allclose precision (#129)

parent bd0e4fa0
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tests/pytorch/test_basics.py
View file @ 3e43d7b8
...@@ -2,6 +2,7 @@ import torch as th ...@@ -2,6 +2,7 @@ import torch as th
from torch.autograd import Variable from torch.autograd import Variable
import numpy as np import numpy as np
from dgl.graph import DGLGraph from dgl.graph import DGLGraph
import utils as U
D = 5 D = 5
reduce_msg_shapes = set() reduce_msg_shapes = set()
...@@ -49,7 +50,7 @@ def test_batch_setter_getter(): ...@@ -49,7 +50,7 @@ def test_batch_setter_getter():
g = generate_graph() g = generate_graph()
# set all nodes # set all nodes
g.ndata['h'] = th.zeros((10, D)) g.ndata['h'] = th.zeros((10, D))
assert th.allclose(g.ndata['h'], th.zeros((10, D))) assert U.allclose(g.ndata['h'], th.zeros((10, D)))
# pop nodes # pop nodes
old_len = len(g.ndata) old_len = len(g.ndata)
assert _pfc(g.pop_n_repr('h')) == [0.] * 10 assert _pfc(g.pop_n_repr('h')) == [0.] * 10
...@@ -175,12 +176,12 @@ def test_apply_edges(): ...@@ -175,12 +176,12 @@ def test_apply_edges():
g.register_apply_edge_func(_upd) g.register_apply_edge_func(_upd)
old = g.edata['w'] old = g.edata['w']
g.apply_edges() g.apply_edges()
assert th.allclose(old * 2, g.edata['w']) assert U.allclose(old * 2, g.edata['w'])
u = th.tensor([0, 0, 0, 4, 5, 6]) u = th.tensor([0, 0, 0, 4, 5, 6])
v = th.tensor([1, 2, 3, 9, 9, 9]) v = th.tensor([1, 2, 3, 9, 9, 9])
g.apply_edges(lambda edges : {'w' : edges.data['w'] * 0.}, (u, v)) g.apply_edges(lambda edges : {'w' : edges.data['w'] * 0.}, (u, v))
eid = g.edge_ids(u, v) eid = g.edge_ids(u, v)
assert th.allclose(g.edata['w'][eid], th.zeros((6, D))) assert U.allclose(g.edata['w'][eid], th.zeros((6, D)))
def test_update_routines(): def test_update_routines():
g = generate_graph() g = generate_graph()
...@@ -232,8 +233,8 @@ def test_reduce_0deg(): ...@@ -232,8 +233,8 @@ def test_reduce_0deg():
g.update_all(_message, _reduce) g.update_all(_message, _reduce)
new_repr = g.ndata['h'] new_repr = g.ndata['h']
assert th.allclose(new_repr[1:], old_repr[1:]) assert U.allclose(new_repr[1:], old_repr[1:])
assert th.allclose(new_repr[0], old_repr.sum(0), rtol=1e-3, atol=1e-3) assert U.allclose(new_repr[0], old_repr.sum(0))
def test_pull_0deg(): def test_pull_0deg():
g = DGLGraph() g = DGLGraph()
...@@ -248,19 +249,19 @@ def test_pull_0deg(): ...@@ -248,19 +249,19 @@ def test_pull_0deg():
g.pull(0, _message, _reduce) g.pull(0, _message, _reduce)
new_repr = g.ndata['h'] new_repr = g.ndata['h']
assert th.allclose(new_repr[0], old_repr[0]) assert U.allclose(new_repr[0], old_repr[0])
assert th.allclose(new_repr[1], old_repr[1]) assert U.allclose(new_repr[1], old_repr[1])
g.pull(1, _message, _reduce) g.pull(1, _message, _reduce)
new_repr = g.ndata['h'] new_repr = g.ndata['h']
assert th.allclose(new_repr[1], old_repr[0]) assert U.allclose(new_repr[1], old_repr[0])
old_repr = th.randn(2, 5) old_repr = th.randn(2, 5)
g.ndata['h'] = old_repr g.ndata['h'] = old_repr
g.pull([0, 1], _message, _reduce) g.pull([0, 1], _message, _reduce)
new_repr = g.ndata['h'] new_repr = g.ndata['h']
assert th.allclose(new_repr[0], old_repr[0]) assert U.allclose(new_repr[0], old_repr[0])
assert th.allclose(new_repr[1], old_repr[0]) assert U.allclose(new_repr[1], old_repr[0])
def _disabled_test_send_twice(): def _disabled_test_send_twice():
# TODO(minjie): please re-enable this unittest after the send code problem is fixed. # TODO(minjie): please re-enable this unittest after the send code problem is fixed.
...@@ -281,14 +282,14 @@ def _disabled_test_send_twice(): ...@@ -281,14 +282,14 @@ def _disabled_test_send_twice():
g.send((0, 1), _message_b) g.send((0, 1), _message_b)
g.recv(1, _reduce) g.recv(1, _reduce)
new_repr = g.ndata['a'] new_repr = g.ndata['a']
assert th.allclose(new_repr[1], old_repr[0] * 3) assert U.allclose(new_repr[1], old_repr[0] * 3)
g.ndata['a'] = old_repr g.ndata['a'] = old_repr
g.send((0, 1), _message_a) g.send((0, 1), _message_a)
g.send((2, 1), _message_b) g.send((2, 1), _message_b)
g.recv(1, _reduce) g.recv(1, _reduce)
new_repr = g.ndata['a'] new_repr = g.ndata['a']
assert th.allclose(new_repr[1], th.stack([old_repr[0], old_repr[2] * 3], 0).max(0)[0]) assert U.allclose(new_repr[1], th.stack([old_repr[0], old_repr[2] * 3], 0).max(0)[0])
def test_send_multigraph(): def test_send_multigraph():
g = DGLGraph(multigraph=True) g = DGLGraph(multigraph=True)
...@@ -315,14 +316,14 @@ def test_send_multigraph(): ...@@ -315,14 +316,14 @@ def test_send_multigraph():
g.send([0, 2], message_func=_message_a) g.send([0, 2], message_func=_message_a)
g.recv(1, _reduce) g.recv(1, _reduce)
new_repr = g.ndata['a'] new_repr = g.ndata['a']
assert th.allclose(new_repr[1], answer(old_repr[0], old_repr[2])) assert U.allclose(new_repr[1], answer(old_repr[0], old_repr[2]))
g.ndata['a'] = th.zeros(3, 5) g.ndata['a'] = th.zeros(3, 5)
g.edata['a'] = old_repr g.edata['a'] = old_repr
g.send([0, 2, 3], message_func=_message_a) g.send([0, 2, 3], message_func=_message_a)
g.recv(1, _reduce) g.recv(1, _reduce)
new_repr = g.ndata['a'] new_repr = g.ndata['a']
assert th.allclose(new_repr[1], answer(old_repr[0], old_repr[2], old_repr[3])) assert U.allclose(new_repr[1], answer(old_repr[0], old_repr[2], old_repr[3]))
# send on multigraph # send on multigraph
g.ndata['a'] = th.zeros(3, 5) g.ndata['a'] = th.zeros(3, 5)
...@@ -330,7 +331,7 @@ def test_send_multigraph(): ...@@ -330,7 +331,7 @@ def test_send_multigraph():
g.send(([0, 2], [1, 1]), _message_a) g.send(([0, 2], [1, 1]), _message_a)
g.recv(1, _reduce) g.recv(1, _reduce)
new_repr = g.ndata['a'] new_repr = g.ndata['a']
assert th.allclose(new_repr[1], old_repr.max(0)[0]) assert U.allclose(new_repr[1], old_repr.max(0)[0])
# consecutive send and send_on # consecutive send and send_on
g.ndata['a'] = th.zeros(3, 5) g.ndata['a'] = th.zeros(3, 5)
...@@ -339,7 +340,7 @@ def test_send_multigraph(): ...@@ -339,7 +340,7 @@ def test_send_multigraph():
g.send([0, 1], message_func=_message_b) g.send([0, 1], message_func=_message_b)
g.recv(1, _reduce) g.recv(1, _reduce)
new_repr = g.ndata['a'] new_repr = g.ndata['a']
assert th.allclose(new_repr[1], answer(old_repr[0] * 3, old_repr[1] * 3, old_repr[3])) assert U.allclose(new_repr[1], answer(old_repr[0] * 3, old_repr[1] * 3, old_repr[3]))
# consecutive send_on # consecutive send_on
g.ndata['a'] = th.zeros(3, 5) g.ndata['a'] = th.zeros(3, 5)
...@@ -348,15 +349,15 @@ def test_send_multigraph(): ...@@ -348,15 +349,15 @@ def test_send_multigraph():
g.send(1, message_func=_message_b) g.send(1, message_func=_message_b)
g.recv(1, _reduce) g.recv(1, _reduce)
new_repr = g.ndata['a'] new_repr = g.ndata['a']
assert th.allclose(new_repr[1], answer(old_repr[0], old_repr[1] * 3)) assert U.allclose(new_repr[1], answer(old_repr[0], old_repr[1] * 3))
# send_and_recv_on # send_and_recv_on
g.ndata['a'] = th.zeros(3, 5) g.ndata['a'] = th.zeros(3, 5)
g.edata['a'] = old_repr g.edata['a'] = old_repr
g.send_and_recv([0, 2, 3], message_func=_message_a, reduce_func=_reduce) g.send_and_recv([0, 2, 3], message_func=_message_a, reduce_func=_reduce)
new_repr = g.ndata['a'] new_repr = g.ndata['a']
assert th.allclose(new_repr[1], answer(old_repr[0], old_repr[2], old_repr[3])) assert U.allclose(new_repr[1], answer(old_repr[0], old_repr[2], old_repr[3]))
assert th.allclose(new_repr[[0, 2]], th.zeros(2, 5)) assert U.allclose(new_repr[[0, 2]], th.zeros(2, 5))
def test_dynamic_addition(): def test_dynamic_addition():
N = 3 N = 3
......
tests/pytorch/test_batched_graph.py
View file @ 3e43d7b8
...@@ -2,6 +2,7 @@ import networkx as nx ...@@ -2,6 +2,7 @@ import networkx as nx
import dgl import dgl
import torch as th import torch as th
import numpy as np import numpy as np
import utils as U
def tree1(): def tree1():
"""Generate a tree """Generate a tree
...@@ -57,10 +58,10 @@ def test_batch_unbatch(): ...@@ -57,10 +58,10 @@ def test_batch_unbatch():
assert bg.batch_num_edges == [4, 4] assert bg.batch_num_edges == [4, 4]
tt1, tt2 = dgl.unbatch(bg) tt1, tt2 = dgl.unbatch(bg)
assert th.allclose(t1.ndata['h'], tt1.ndata['h']) assert U.allclose(t1.ndata['h'], tt1.ndata['h'])
assert th.allclose(t1.edata['h'], tt1.edata['h']) assert U.allclose(t1.edata['h'], tt1.edata['h'])
assert th.allclose(t2.ndata['h'], tt2.ndata['h']) assert U.allclose(t2.ndata['h'], tt2.ndata['h'])
assert th.allclose(t2.edata['h'], tt2.edata['h']) assert U.allclose(t2.edata['h'], tt2.edata['h'])
def test_batch_unbatch1(): def test_batch_unbatch1():
t1 = tree1() t1 = tree1()
...@@ -74,12 +75,12 @@ def test_batch_unbatch1(): ...@@ -74,12 +75,12 @@ def test_batch_unbatch1():
assert b2.batch_num_edges == [4, 4, 4] assert b2.batch_num_edges == [4, 4, 4]
s1, s2, s3 = dgl.unbatch(b2) s1, s2, s3 = dgl.unbatch(b2)
assert th.allclose(t2.ndata['h'], s1.ndata['h']) assert U.allclose(t2.ndata['h'], s1.ndata['h'])
assert th.allclose(t2.edata['h'], s1.edata['h']) assert U.allclose(t2.edata['h'], s1.edata['h'])
assert th.allclose(t1.ndata['h'], s2.ndata['h']) assert U.allclose(t1.ndata['h'], s2.ndata['h'])
assert th.allclose(t1.edata['h'], s2.edata['h']) assert U.allclose(t1.edata['h'], s2.edata['h'])
assert th.allclose(t2.ndata['h'], s3.ndata['h']) assert U.allclose(t2.ndata['h'], s3.ndata['h'])
assert th.allclose(t2.edata['h'], s3.edata['h']) assert U.allclose(t2.edata['h'], s3.edata['h'])
def test_batch_sendrecv(): def test_batch_sendrecv():
t1 = tree1() t1 = tree1()
......
tests/pytorch/test_filter.py
View file @ 3e43d7b8
import torch as th import torch as th
import numpy as np import numpy as np
from dgl.graph import DGLGraph from dgl.graph import DGLGraph
import utils as U
def test_filter(): def test_filter():
g = DGLGraph() g = DGLGraph()
......
tests/pytorch/test_frame.py
View file @ 3e43d7b8
...@@ -3,6 +3,7 @@ from torch.autograd import Variable ...@@ -3,6 +3,7 @@ from torch.autograd import Variable
import numpy as np import numpy as np
from dgl.frame import Frame, FrameRef from dgl.frame import Frame, FrameRef
from dgl.utils import Index, toindex from dgl.utils import Index, toindex
import utils as U
N = 10 N = 10
D = 5 D = 5
...@@ -43,9 +44,9 @@ def test_column1(): ...@@ -43,9 +44,9 @@ def test_column1():
f = Frame(data) f = Frame(data)
assert f.num_rows == N assert f.num_rows == N
assert len(f) == 3 assert len(f) == 3
assert th.allclose(f['a1'].data, data['a1'].data) assert U.allclose(f['a1'].data, data['a1'].data)
f['a1'] = data['a2'] f['a1'] = data['a2']
assert th.allclose(f['a2'].data, data['a2'].data) assert U.allclose(f['a2'].data, data['a2'].data)
# add a different length column should fail # add a different length column should fail
def failed_add_col(): def failed_add_col():
f['a4'] = th.zeros([N+1, D]) f['a4'] = th.zeros([N+1, D])
...@@ -68,10 +69,10 @@ def test_column2(): ...@@ -68,10 +69,10 @@ def test_column2():
f = FrameRef(data, [3, 4, 5, 6, 7]) f = FrameRef(data, [3, 4, 5, 6, 7])
assert f.num_rows == 5 assert f.num_rows == 5
assert len(f) == 3 assert len(f) == 3
assert th.allclose(f['a1'], data['a1'].data[3:8]) assert U.allclose(f['a1'], data['a1'].data[3:8])
# set column should reflect on the referenced data # set column should reflect on the referenced data
f['a1'] = th.zeros([5, D]) f['a1'] = th.zeros([5, D])
assert th.allclose(data['a1'].data[3:8], th.zeros([5, D])) assert U.allclose(data['a1'].data[3:8], th.zeros([5, D]))
# add new partial column should fail with error initializer # add new partial column should fail with error initializer
f.set_initializer(lambda shape, dtype : assert_(False)) f.set_initializer(lambda shape, dtype : assert_(False))
def failed_add_col(): def failed_add_col():
...@@ -90,7 +91,7 @@ def test_append1(): ...@@ -90,7 +91,7 @@ def test_append1():
c1 = f1['a1'] c1 = f1['a1']
assert c1.data.shape == (2 * N, D) assert c1.data.shape == (2 * N, D)
truth = th.cat([data['a1'], data['a1']]) truth = th.cat([data['a1'], data['a1']])
assert th.allclose(truth, c1.data) assert U.allclose(truth, c1.data)
# append dict of different length columns should fail # append dict of different length columns should fail
f3 = {'a1' : th.zeros((3, D)), 'a2' : th.zeros((3, D)), 'a3' : th.zeros((2, D))} f3 = {'a1' : th.zeros((3, D)), 'a2' : th.zeros((3, D)), 'a3' : th.zeros((2, D))}
def failed_append(): def failed_append():
...@@ -129,13 +130,13 @@ def test_row1(): ...@@ -129,13 +130,13 @@ def test_row1():
rows = f[rowid] rows = f[rowid]
for k, v in rows.items(): for k, v in rows.items():
assert v.shape == (len(rowid), D) assert v.shape == (len(rowid), D)
assert th.allclose(v, data[k][rowid]) assert U.allclose(v, data[k][rowid])
# test duplicate keys # test duplicate keys
rowid = Index(th.tensor([8, 2, 2, 1])) rowid = Index(th.tensor([8, 2, 2, 1]))
rows = f[rowid] rows = f[rowid]
for k, v in rows.items(): for k, v in rows.items():
assert v.shape == (len(rowid), D) assert v.shape == (len(rowid), D)
assert th.allclose(v, data[k][rowid]) assert U.allclose(v, data[k][rowid])
# setter # setter
rowid = Index(th.tensor([0, 2, 4])) rowid = Index(th.tensor([0, 2, 4]))
...@@ -145,7 +146,7 @@ def test_row1(): ...@@ -145,7 +146,7 @@ def test_row1():
} }
f[rowid] = vals f[rowid] = vals
for k, v in f[rowid].items(): for k, v in f[rowid].items():
assert th.allclose(v, th.zeros((len(rowid), D))) assert U.allclose(v, th.zeros((len(rowid), D)))
# setting rows with new column should raise error with error initializer # setting rows with new column should raise error with error initializer
f.set_initializer(lambda shape, dtype : assert_(False)) f.set_initializer(lambda shape, dtype : assert_(False))
...@@ -165,13 +166,13 @@ def test_row2(): ...@@ -165,13 +166,13 @@ def test_row2():
rowid = Index(th.tensor([0, 2])) rowid = Index(th.tensor([0, 2]))
rows = f[rowid] rows = f[rowid]
rows['a1'].backward(th.ones((len(rowid), D))) rows['a1'].backward(th.ones((len(rowid), D)))
assert th.allclose(c1.grad[:,0], th.tensor([1., 0., 1., 0., 0., 0., 0., 0., 0., 0.])) assert U.allclose(c1.grad[:,0], th.tensor([1., 0., 1., 0., 0., 0., 0., 0., 0., 0.]))
c1.grad.data.zero_() c1.grad.data.zero_()
# test duplicate keys # test duplicate keys
rowid = Index(th.tensor([8, 2, 2, 1])) rowid = Index(th.tensor([8, 2, 2, 1]))
rows = f[rowid] rows = f[rowid]
rows['a1'].backward(th.ones((len(rowid), D))) rows['a1'].backward(th.ones((len(rowid), D)))
assert th.allclose(c1.grad[:,0], th.tensor([0., 1., 2., 0., 0., 0., 0., 0., 1., 0.])) assert U.allclose(c1.grad[:,0], th.tensor([0., 1., 2., 0., 0., 0., 0., 0., 1., 0.]))
c1.grad.data.zero_() c1.grad.data.zero_()
# setter # setter
...@@ -184,8 +185,8 @@ def test_row2(): ...@@ -184,8 +185,8 @@ def test_row2():
f[rowid] = vals f[rowid] = vals
c11 = f['a1'] c11 = f['a1']
c11.backward(th.ones((N, D))) c11.backward(th.ones((N, D)))
assert th.allclose(c1.grad[:,0], th.tensor([0., 1., 0., 1., 0., 1., 1., 1., 1., 1.])) assert U.allclose(c1.grad[:,0], th.tensor([0., 1., 0., 1., 0., 1., 1., 1., 1., 1.]))
assert th.allclose(vals['a1'].grad, th.ones((len(rowid), D))) assert U.allclose(vals['a1'].grad, th.ones((len(rowid), D)))
assert vals['a2'].grad is None assert vals['a2'].grad is None
def test_row3(): def test_row3():
...@@ -207,7 +208,7 @@ def test_row3(): ...@@ -207,7 +208,7 @@ def test_row3():
newidx.pop(2) newidx.pop(2)
newidx = toindex(newidx) newidx = toindex(newidx)
for k, v in f.items(): for k, v in f.items():
assert th.allclose(v, data[k][newidx]) assert U.allclose(v, data[k][newidx])
def test_sharing(): def test_sharing():
data = Frame(create_test_data()) data = Frame(create_test_data())
...@@ -215,9 +216,9 @@ def test_sharing(): ...@@ -215,9 +216,9 @@ def test_sharing():
f2 = FrameRef(data, index=[2, 3, 4, 5, 6]) f2 = FrameRef(data, index=[2, 3, 4, 5, 6])
# test read # test read
for k, v in f1.items(): for k, v in f1.items():
assert th.allclose(data[k].data[0:4], v) assert U.allclose(data[k].data[0:4], v)
for k, v in f2.items(): for k, v in f2.items():
assert th.allclose(data[k].data[2:7], v) assert U.allclose(data[k].data[2:7], v)
f2_a1 = f2['a1'].data f2_a1 = f2['a1'].data
# test write # test write
# update own ref should not been seen by the other. # update own ref should not been seen by the other.
...@@ -226,7 +227,7 @@ def test_sharing(): ...@@ -226,7 +227,7 @@ def test_sharing():
'a2' : th.zeros([2, D]), 'a2' : th.zeros([2, D]),
'a3' : th.zeros([2, D]), 'a3' : th.zeros([2, D]),
} }
assert th.allclose(f2['a1'], f2_a1) assert U.allclose(f2['a1'], f2_a1)
# update shared space should been seen by the other. # update shared space should been seen by the other.
f1[Index(th.tensor([2, 3]))] = { f1[Index(th.tensor([2, 3]))] = {
'a1' : th.ones([2, D]), 'a1' : th.ones([2, D]),
...@@ -234,7 +235,7 @@ def test_sharing(): ...@@ -234,7 +235,7 @@ def test_sharing():
'a3' : th.ones([2, D]), 'a3' : th.ones([2, D]),
} }
f2_a1[0:2] = th.ones([2, D]) f2_a1[0:2] = th.ones([2, D])
assert th.allclose(f2['a1'], f2_a1) assert U.allclose(f2['a1'], f2_a1)
def test_slicing(): def test_slicing():
data = Frame(create_test_data(grad=True)) data = Frame(create_test_data(grad=True))
...@@ -242,7 +243,7 @@ def test_slicing(): ...@@ -242,7 +243,7 @@ def test_slicing():
f2 = FrameRef(data, index=slice(3, 8)) f2 = FrameRef(data, index=slice(3, 8))
# test read # test read
for k, v in f1.items(): for k, v in f1.items():
assert th.allclose(data[k].data[1:5], v) assert U.allclose(data[k].data[1:5], v)
f2_a1 = f2['a1'].data f2_a1 = f2['a1'].data
# test write # test write
f1[Index(th.tensor([0, 1]))] = { f1[Index(th.tensor([0, 1]))] = {
...@@ -250,7 +251,7 @@ def test_slicing(): ...@@ -250,7 +251,7 @@ def test_slicing():
'a2': th.zeros([2, D]), 'a2': th.zeros([2, D]),
'a3': th.zeros([2, D]), 'a3': th.zeros([2, D]),
} }
assert th.allclose(f2['a1'], f2_a1) assert U.allclose(f2['a1'], f2_a1)
f1[Index(th.tensor([2, 3]))] = { f1[Index(th.tensor([2, 3]))] = {
'a1': th.ones([2, D]), 'a1': th.ones([2, D]),
...@@ -258,7 +259,7 @@ def test_slicing(): ...@@ -258,7 +259,7 @@ def test_slicing():
'a3': th.ones([2, D]), 'a3': th.ones([2, D]),
} }
f2_a1[0:2] = 1 f2_a1[0:2] = 1
assert th.allclose(f2['a1'], f2_a1) assert U.allclose(f2['a1'], f2_a1)
f1[2:4] = { f1[2:4] = {
'a1': th.zeros([2, D]), 'a1': th.zeros([2, D]),
...@@ -266,7 +267,7 @@ def test_slicing(): ...@@ -266,7 +267,7 @@ def test_slicing():
'a3': th.zeros([2, D]), 'a3': th.zeros([2, D]),
} }
f2_a1[0:2] = 0 f2_a1[0:2] = 0
assert th.allclose(f2['a1'], f2_a1) assert U.allclose(f2['a1'], f2_a1)
if __name__ == '__main__': if __name__ == '__main__':
test_create() test_create()
......
tests/pytorch/test_function.py
View file @ 3e43d7b8
import torch as th import torch as th
import dgl import dgl
import dgl.function as fn import dgl.function as fn
import utils as U
def generate_graph(): def generate_graph():
g = dgl.DGLGraph() g = dgl.DGLGraph()
...@@ -27,7 +28,7 @@ def test_copy_src(): ...@@ -27,7 +28,7 @@ def test_copy_src():
g.register_message_func(fn.copy_src(src='h', out='m')) g.register_message_func(fn.copy_src(src='h', out='m'))
g.register_reduce_func(reducer_both) g.register_reduce_func(reducer_both)
g.update_all() g.update_all()
assert th.allclose(g.ndata['h'], assert U.allclose(g.ndata['h'],
th.tensor([10., 1., 1., 1., 1., 1., 1., 1., 1., 44.])) th.tensor([10., 1., 1., 1., 1., 1., 1., 1., 1., 44.]))
def test_copy_edge(): def test_copy_edge():
...@@ -36,7 +37,7 @@ def test_copy_edge(): ...@@ -36,7 +37,7 @@ def test_copy_edge():
g.register_message_func(fn.copy_edge(edge='h', out='m')) g.register_message_func(fn.copy_edge(edge='h', out='m'))
g.register_reduce_func(reducer_both) g.register_reduce_func(reducer_both)
g.update_all() g.update_all()
assert th.allclose(g.ndata['h'], assert U.allclose(g.ndata['h'],
th.tensor([10., 1., 1., 1., 1., 1., 1., 1., 1., 44.])) th.tensor([10., 1., 1., 1., 1., 1., 1., 1., 1., 44.]))
def test_src_mul_edge(): def test_src_mul_edge():
...@@ -45,7 +46,7 @@ def test_src_mul_edge(): ...@@ -45,7 +46,7 @@ def test_src_mul_edge():
g.register_message_func(fn.src_mul_edge(src='h', edge='h', out='m')) g.register_message_func(fn.src_mul_edge(src='h', edge='h', out='m'))
g.register_reduce_func(reducer_both) g.register_reduce_func(reducer_both)
g.update_all() g.update_all()
assert th.allclose(g.ndata['h'], assert U.allclose(g.ndata['h'],
th.tensor([100., 1., 1., 1., 1., 1., 1., 1., 1., 284.])) th.tensor([100., 1., 1., 1., 1., 1., 1., 1., 1., 284.]))
if __name__ == '__main__': if __name__ == '__main__':
......
tests/pytorch/test_index.py
View file @ 3e43d7b8
...@@ -4,6 +4,7 @@ from dgl.utils import toindex ...@@ -4,6 +4,7 @@ from dgl.utils import toindex
import numpy as np import numpy as np
import torch as th import torch as th
from torch.utils import dlpack from torch.utils import dlpack
import utils as U
def test_dlpack(): def test_dlpack():
# test dlpack conversion. # test dlpack conversion.
......
tests/pytorch/test_line_graph.py
View file @ 3e43d7b8
...@@ -2,6 +2,7 @@ import torch as th ...@@ -2,6 +2,7 @@ import torch as th
import networkx as nx import networkx as nx
import numpy as np import numpy as np
import dgl import dgl
import utils as U
D = 5 D = 5
...@@ -19,13 +20,13 @@ def test_line_graph(): ...@@ -19,13 +20,13 @@ def test_line_graph():
v = [1, 2, 0, 0] v = [1, 2, 0, 0]
eid = G.edge_ids(u, v) eid = G.edge_ids(u, v)
L.nodes[eid].data['h'] = th.zeros((4, D)) L.nodes[eid].data['h'] = th.zeros((4, D))
assert th.allclose(G.edges[u, v].data['h'], th.zeros((4, D))) assert U.allclose(G.edges[u, v].data['h'], th.zeros((4, D)))
# adding a new node feature on line graph should also reflect to a new # adding a new node feature on line graph should also reflect to a new
# edge feature on original graph # edge feature on original graph
data = th.randn(n_edges, D) data = th.randn(n_edges, D)
L.ndata['w'] = data L.ndata['w'] = data
assert th.allclose(G.edata['w'], data) assert U.allclose(G.edata['w'], data)
def test_no_backtracking(): def test_no_backtracking():
N = 5 N = 5
......
tests/pytorch/test_specialization.py
View file @ 3e43d7b8
...@@ -2,6 +2,7 @@ import torch as th ...@@ -2,6 +2,7 @@ import torch as th
import numpy as np import numpy as np
import dgl import dgl
import dgl.function as fn import dgl.function as fn
import utils as U
D = 5 D = 5
...@@ -43,7 +44,7 @@ def test_update_all(): ...@@ -43,7 +44,7 @@ def test_update_all():
g.set_n_repr({fld : v1}) g.set_n_repr({fld : v1})
g.update_all(message_func, reduce_func, apply_func) g.update_all(message_func, reduce_func, apply_func)
v3 = g.ndata[fld] v3 = g.ndata[fld]
assert th.allclose(v2, v3) assert U.allclose(v2, v3)
# update all with edge weights # update all with edge weights
v1 = g.ndata[fld] v1 = g.ndata[fld]
g.update_all(fn.src_mul_edge(src=fld, edge='e1', out='m'), g.update_all(fn.src_mul_edge(src=fld, edge='e1', out='m'),
...@@ -56,8 +57,8 @@ def test_update_all(): ...@@ -56,8 +57,8 @@ def test_update_all():
g.set_n_repr({fld : v1}) g.set_n_repr({fld : v1})
g.update_all(message_func_edge, reduce_func, apply_func) g.update_all(message_func_edge, reduce_func, apply_func)
v4 = g.ndata[fld] v4 = g.ndata[fld]
assert th.allclose(v2, v3) assert U.allclose(v2, v3)
assert th.allclose(v3, v4) assert U.allclose(v3, v4)
# test 1d node features # test 1d node features
_test('f1') _test('f1')
# test 2d node features # test 2d node features
...@@ -90,7 +91,7 @@ def test_send_and_recv(): ...@@ -90,7 +91,7 @@ def test_send_and_recv():
g.set_n_repr({fld : v1}) g.set_n_repr({fld : v1})
g.send_and_recv((u, v), message_func, reduce_func, apply_func) g.send_and_recv((u, v), message_func, reduce_func, apply_func)
v3 = g.ndata[fld] v3 = g.ndata[fld]
assert th.allclose(v2, v3) assert U.allclose(v2, v3)
# send and recv with edge weights # send and recv with edge weights
v1 = g.ndata[fld] v1 = g.ndata[fld]
g.send_and_recv((u, v), fn.src_mul_edge(src=fld, edge='e1', out='m'), g.send_and_recv((u, v), fn.src_mul_edge(src=fld, edge='e1', out='m'),
...@@ -103,8 +104,8 @@ def test_send_and_recv(): ...@@ -103,8 +104,8 @@ def test_send_and_recv():
g.set_n_repr({fld : v1}) g.set_n_repr({fld : v1})
g.send_and_recv((u, v), message_func_edge, reduce_func, apply_func) g.send_and_recv((u, v), message_func_edge, reduce_func, apply_func)
v4 = g.ndata[fld] v4 = g.ndata[fld]
assert th.allclose(v2, v3) assert U.allclose(v2, v3)
assert th.allclose(v3, v4) assert U.allclose(v3, v4)
# test 1d node features # test 1d node features
_test('f1') _test('f1')
# test 2d node features # test 2d node features
...@@ -129,19 +130,19 @@ def test_update_all_multi_fn(): ...@@ -129,19 +130,19 @@ def test_update_all_multi_fn():
None) None)
v1 = g.ndata['v1'] v1 = g.ndata['v1']
v2 = g.ndata['v2'] v2 = g.ndata['v2']
assert th.allclose(v1, v2) assert U.allclose(v1, v2)
# run builtin with single message and reduce # run builtin with single message and reduce
g.update_all(fn.copy_src(src=fld, out='m'), fn.sum(msg='m', out='v1'), None) g.update_all(fn.copy_src(src=fld, out='m'), fn.sum(msg='m', out='v1'), None)
v1 = g.ndata['v1'] v1 = g.ndata['v1']
assert th.allclose(v1, v2) assert U.allclose(v1, v2)
# 1 message, 2 reduces # 1 message, 2 reduces
g.update_all(fn.copy_src(src=fld, out='m'), [fn.sum(msg='m', out='v2'), fn.sum(msg='m', out='v3')], None) g.update_all(fn.copy_src(src=fld, out='m'), [fn.sum(msg='m', out='v2'), fn.sum(msg='m', out='v3')], None)
v2 = g.ndata['v2'] v2 = g.ndata['v2']
v3 = g.ndata['v3'] v3 = g.ndata['v3']
assert th.allclose(v1, v2) assert U.allclose(v1, v2)
assert th.allclose(v1, v3) assert U.allclose(v1, v3)
# update all with edge weights, 2 message, 3 reduces # update all with edge weights, 2 message, 3 reduces
g.update_all([fn.src_mul_edge(src=fld, edge='e1', out='m1'), fn.src_mul_edge(src=fld, edge='e2', out='m2')], g.update_all([fn.src_mul_edge(src=fld, edge='e1', out='m1'), fn.src_mul_edge(src=fld, edge='e2', out='m2')],
...@@ -150,13 +151,13 @@ def test_update_all_multi_fn(): ...@@ -150,13 +151,13 @@ def test_update_all_multi_fn():
v1 = g.ndata['v1'] v1 = g.ndata['v1']
v2 = g.ndata['v2'] v2 = g.ndata['v2']
v3 = g.ndata['v3'] v3 = g.ndata['v3']
assert th.allclose(v1, v2) assert U.allclose(v1, v2)
assert th.allclose(v1, v3) assert U.allclose(v1, v3)
# run UDF with single message and reduce # run UDF with single message and reduce
g.update_all(message_func_edge, reduce_func, None) g.update_all(message_func_edge, reduce_func, None)
v2 = g.ndata['v2'] v2 = g.ndata['v2']
assert th.allclose(v1, v2) assert U.allclose(v1, v2)
def test_send_and_recv_multi_fn(): def test_send_and_recv_multi_fn():
u = th.tensor([0, 0, 0, 3, 4, 9]) u = th.tensor([0, 0, 0, 3, 4, 9])
...@@ -183,13 +184,13 @@ def test_send_and_recv_multi_fn(): ...@@ -183,13 +184,13 @@ def test_send_and_recv_multi_fn():
None) None)
v1 = g.ndata['v1'] v1 = g.ndata['v1']
v2 = g.ndata['v2'] v2 = g.ndata['v2']
assert th.allclose(v1, v2) assert U.allclose(v1, v2)
# run builtin with single message and reduce # run builtin with single message and reduce
g.send_and_recv((u, v), fn.copy_src(src=fld, out='m'), fn.sum(msg='m', out='v1'), g.send_and_recv((u, v), fn.copy_src(src=fld, out='m'), fn.sum(msg='m', out='v1'),
None) None)
v1 = g.ndata['v1'] v1 = g.ndata['v1']
assert th.allclose(v1, v2) assert U.allclose(v1, v2)
# 1 message, 2 reduces # 1 message, 2 reduces
g.send_and_recv((u, v), g.send_and_recv((u, v),
...@@ -198,8 +199,8 @@ def test_send_and_recv_multi_fn(): ...@@ -198,8 +199,8 @@ def test_send_and_recv_multi_fn():
None) None)
v2 = g.ndata['v2'] v2 = g.ndata['v2']
v3 = g.ndata['v3'] v3 = g.ndata['v3']
assert th.allclose(v1, v2) assert U.allclose(v1, v2)
assert th.allclose(v1, v3) assert U.allclose(v1, v3)
# send and recv with edge weights, 2 message, 3 reduces # send and recv with edge weights, 2 message, 3 reduces
g.send_and_recv((u, v), g.send_and_recv((u, v),
...@@ -209,14 +210,14 @@ def test_send_and_recv_multi_fn(): ...@@ -209,14 +210,14 @@ def test_send_and_recv_multi_fn():
v1 = g.ndata['v1'] v1 = g.ndata['v1']
v2 = g.ndata['v2'] v2 = g.ndata['v2']
v3 = g.ndata['v3'] v3 = g.ndata['v3']
assert th.allclose(v1, v2) assert U.allclose(v1, v2)
assert th.allclose(v1, v3) assert U.allclose(v1, v3)
# run UDF with single message and reduce # run UDF with single message and reduce
g.send_and_recv((u, v), message_func_edge, g.send_and_recv((u, v), message_func_edge,
reduce_func, None) reduce_func, None)
v2 = g.ndata['v2'] v2 = g.ndata['v2']
assert th.allclose(v1, v2) assert U.allclose(v1, v2)
if __name__ == '__main__': if __name__ == '__main__':
test_update_all() test_update_all()
......
tests/pytorch/test_subgraph.py
View file @ 3e43d7b8
...@@ -2,6 +2,7 @@ import torch as th ...@@ -2,6 +2,7 @@ import torch as th
from torch.autograd import Variable from torch.autograd import Variable
import numpy as np import numpy as np
from dgl.graph import DGLGraph from dgl.graph import DGLGraph
import utils as U
D = 5 D = 5
...@@ -37,7 +38,7 @@ def test_basics(): ...@@ -37,7 +38,7 @@ def test_basics():
assert len(sg.ndata) == 1 assert len(sg.ndata) == 1
assert len(sg.edata) == 1 assert len(sg.edata) == 1
sh = sg.ndata['h'] sh = sg.ndata['h']
assert th.allclose(h[nid], sh) assert U.allclose(h[nid], sh)
''' '''
s, d, eid s, d, eid
0, 1, 0 0, 1, 0
...@@ -58,11 +59,11 @@ def test_basics(): ...@@ -58,11 +59,11 @@ def test_basics():
8, 9, 15 3 8, 9, 15 3
9, 0, 16 1 9, 0, 16 1
''' '''
assert th.allclose(l[eid], sg.edata['l']) assert U.allclose(l[eid], sg.edata['l'])
# update the node/edge features on the subgraph should NOT # update the node/edge features on the subgraph should NOT
# reflect to the parent graph. # reflect to the parent graph.
sg.ndata['h'] = th.zeros((6, D)) sg.ndata['h'] = th.zeros((6, D))
assert th.allclose(h, g.ndata['h']) assert U.allclose(h, g.ndata['h'])
def test_merge(): def test_merge():
# FIXME: current impl cannot handle this case!!! # FIXME: current impl cannot handle this case!!!
...@@ -87,8 +88,8 @@ def test_merge(): ...@@ -87,8 +88,8 @@ def test_merge():
h = g.ndata['h'][:,0] h = g.ndata['h'][:,0]
l = g.edata['l'][:,0] l = g.edata['l'][:,0]
assert th.allclose(h, th.tensor([3., 0., 3., 3., 2., 0., 1., 1., 0., 1.])) assert U.allclose(h, th.tensor([3., 0., 3., 3., 2., 0., 1., 1., 0., 1.]))
assert th.allclose(l, assert U.allclose(l,
th.tensor([0., 0., 1., 1., 1., 1., 0., 0., 0., 3., 1., 4., 1., 4., 0., 3., 1.])) th.tensor([0., 0., 1., 1., 1., 1., 0., 0., 0., 3., 1., 4., 1., 4., 0., 3., 1.]))
""" """
......
tests/pytorch/test_traversal.py
View file @ 3e43d7b8
...@@ -7,6 +7,7 @@ import networkx as nx ...@@ -7,6 +7,7 @@ import networkx as nx
import numpy as np import numpy as np
import scipy.sparse as sp import scipy.sparse as sp
import torch as th import torch as th
import utils as U
np.random.seed(42) np.random.seed(42)
......
tests/pytorch/utils.py 0 → 100644
View file @ 3e43d7b8
import torch as th
def allclose(a, b):
return th.allclose(a, b, rtol=1e-4, atol=1e-4)
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