-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathautoencoder_architecture
More file actions
84 lines (84 loc) · 2.93 KB
/
Copy pathautoencoder_architecture
File metadata and controls
84 lines (84 loc) · 2.93 KB
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
digraph {
graph [size="12,12"]
node [align=left fontname=monospace fontsize=10 height=0.2 ranksep=0.1 shape=box style=filled]
1858550302192 [label="
(1, 1, 256, 256)" fillcolor=darkolivegreen1]
1858696626720 [label=SigmoidBackward0]
1858679580528 -> 1858696626720
1858679580528 [label=ConvolutionBackward0]
1858696721936 -> 1858679580528
1858696721936 [label=UpsampleNearest2DBackward0]
1858696722560 -> 1858696721936
1858696722560 [label=ReluBackward0]
1858696722416 -> 1858696722560
1858696722416 [label=ConvolutionBackward0]
1858696722656 -> 1858696722416
1858696722656 [label=UpsampleNearest2DBackward0]
1858696722848 -> 1858696722656
1858696722848 [label=ReluBackward0]
1858696722944 -> 1858696722848
1858696722944 [label=ConvolutionBackward0]
1858696723040 -> 1858696722944
1858696723040 [label=MaxPool2DWithIndicesBackward0]
1858696723232 -> 1858696723040
1858696723232 [label=ReluBackward0]
1858696723328 -> 1858696723232
1858696723328 [label=ConvolutionBackward0]
1858696723424 -> 1858696723328
1858696723424 [label=MaxPool2DWithIndicesBackward0]
1858696723616 -> 1858696723424
1858696723616 [label=ReluBackward0]
1858696723712 -> 1858696723616
1858696723712 [label=ConvolutionBackward0]
1858696723808 -> 1858696723712
1858635032096 [label="encoder.0.weight
(32, 1, 3, 3)" fillcolor=lightblue]
1858635032096 -> 1858696723808
1858696723808 [label=AccumulateGrad]
1858696723856 -> 1858696723712
1858550250496 [label="encoder.0.bias
(32)" fillcolor=lightblue]
1858550250496 -> 1858696723856
1858696723856 [label=AccumulateGrad]
1858696723472 -> 1858696723328
1858550250576 [label="encoder.3.weight
(64, 32, 3, 3)" fillcolor=lightblue]
1858550250576 -> 1858696723472
1858696723472 [label=AccumulateGrad]
1858696723184 -> 1858696723328
1858550250416 [label="encoder.3.bias
(64)" fillcolor=lightblue]
1858550250416 -> 1858696723184
1858696723184 [label=AccumulateGrad]
1858696723088 -> 1858696722944
1858550250336 [label="decoder.0.weight
(64, 32, 3, 3)" fillcolor=lightblue]
1858550250336 -> 1858696723088
1858696723088 [label=AccumulateGrad]
1858696722800 -> 1858696722944
1858550250256 [label="decoder.0.bias
(32)" fillcolor=lightblue]
1858550250256 -> 1858696722800
1858696722800 [label=AccumulateGrad]
1858696722704 -> 1858696722416
1858550250176 [label="decoder.3.weight
(32, 32, 3, 3)" fillcolor=lightblue]
1858550250176 -> 1858696722704
1858696722704 [label=AccumulateGrad]
1858696722464 -> 1858696722416
1858550250096 [label="decoder.3.bias
(32)" fillcolor=lightblue]
1858550250096 -> 1858696722464
1858696722464 [label=AccumulateGrad]
1858696721888 -> 1858679580528
1858550249936 [label="decoder.6.weight
(1, 32, 3, 3)" fillcolor=lightblue]
1858550249936 -> 1858696721888
1858696721888 [label=AccumulateGrad]
1858696722320 -> 1858679580528
1858550249856 [label="decoder.6.bias
(1)" fillcolor=lightblue]
1858550249856 -> 1858696722320
1858696722320 [label=AccumulateGrad]
1858696626720 -> 1858550302192
}