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
|
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import pytest
import torch
import torch.cuda
from torch.distributed.pipeline.sync.microbatch import Batch, check, gather, scatter
def test_batch_atomic():
x = torch.tensor(42)
b = Batch(x)
assert b.atomic
assert b.tensor is x
with pytest.raises(AttributeError):
b.tensors
assert list(b) == [x]
assert len(b) == 1
assert b[0] is x
def test_batch_non_atomic():
x, y = torch.tensor(42), torch.tensor(21)
b = Batch((x, y))
assert not b.atomic
with pytest.raises(AttributeError):
b.tensor
assert list(b) == [x, y]
assert len(b) == 2
assert b[0] is x
assert b[1] is y
def test_batch_call():
a = Batch(torch.tensor(42))
b = Batch((torch.tensor(42), torch.tensor(21)))
def f(x):
return x
def g(x, y):
return x, y
assert a.call(f).atomic
assert not b.call(g).atomic
def test_batch_setitem_by_index():
a = Batch(torch.tensor(42))
b = Batch((torch.tensor(42), torch.tensor(21)))
a[0] = torch.tensor(0)
b[0] = torch.tensor(0)
assert a.atomic
assert a[0].item() == 0
assert not b.atomic
assert len(b) == 2
assert b[0].item() == 0
assert b[1].item() == 21
def test_batch_setitem_by_slice():
a = Batch(torch.tensor(42))
b = Batch((torch.tensor(42), torch.tensor(21)))
a[:] = (torch.tensor(0),)
b[:] = (torch.tensor(0),)
assert a.atomic
assert a[0].item() == 0
assert not b.atomic
assert len(b) == 1
assert b[0].item() == 0
def test_check():
check(torch.device("cpu"), torch.tensor(42))
check(torch.device("cpu"), torch.tensor(4), torch.tensor(2))
with pytest.raises(TypeError):
check(torch.device("cpu"), 42)
with pytest.raises(TypeError):
check(torch.device("cpu"), "str")
with pytest.raises(TypeError):
check(torch.device("cpu"), (torch.tensor(4), 2))
def test_gather_tensors():
a = torch.zeros(1, 1)
b = torch.zeros(1, 1)
ab = gather([Batch(a), Batch(b)])
assert ab.size() == (2, 1)
def test_gather_tuples():
a = (torch.zeros(1, 1), torch.zeros(2, 2))
b = (torch.zeros(1, 1), torch.zeros(2, 2))
ab = gather([Batch(a), Batch(b)])
assert isinstance(ab, tuple)
assert ab[0].size() == (2, 1)
assert ab[1].size() == (4, 2)
def test_scatter_tensor():
ab = torch.zeros(2, 1)
a, b = scatter(ab, chunks=2)
assert a.tensor.size() == (1, 1)
assert b.tensor.size() == (1, 1)
def test_scatter_multiple_tensors():
ab = (torch.zeros(2, 1), torch.zeros(4, 2))
a, b = scatter(*ab, chunks=2)
assert list(a)[0].size() == (1, 1)
assert list(b)[0].size() == (1, 1)
assert list(a)[1].size() == (2, 2)
assert list(b)[1].size() == (2, 2)
|
