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
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
|
require 'speech.init'
gconf = {lrate = 0.8, wcost = 1e-6, momentum = 0.9,
cumat_type = nerv.CuMatrixFloat,
mmat_type = nerv.MMatrixFloat,
frm_ext = 5,
tr_scp = "/slfs1/users/mfy43/swb_ivec/train_bp.scp",
cv_scp = "/slfs1/users/mfy43/swb_ivec/train_cv.scp",
htk_conf = "/slfs1/users/mfy43/swb_ivec/plp_0_d_a.conf",
global_transf = "global_transf.nerv",
initialized_param = "converted.nerv",
debug = false}
function make_param_repo(param_file)
return nerv.ParamRepo({param_file, gconf.global_transf})
end
function make_sublayer_repo(param_repo)
return nerv.LayerRepo(
{
-- global transf
["nerv.BiasLayer"] =
{
blayer1 = {{bias = "bias1"}, {dim_in = {429}, dim_out = {429}}},
blayer2 = {{bias = "bias2"}, {dim_in = {429}, dim_out = {429}}}
},
["nerv.WindowLayer"] =
{
wlayer1 = {{window = "window1"}, {dim_in = {429}, dim_out = {429}}},
wlayer2 = {{window = "window2"}, {dim_in = {429}, dim_out = {429}}}
},
-- biased linearity
["nerv.AffineLayer"] =
{
affine0 = {{ltp = "affine0_ltp", bp = "affine0_bp"},
{dim_in = {429}, dim_out = {2048}}},
affine1 = {{ltp = "affine1_ltp", bp = "affine1_bp"},
{dim_in = {2048}, dim_out = {2048}}},
affine2 = {{ltp = "affine2_ltp", bp = "affine2_bp"},
{dim_in = {2048}, dim_out = {2048}}},
affine3 = {{ltp = "affine3_ltp", bp = "affine3_bp"},
{dim_in = {2048}, dim_out = {2048}}},
affine4 = {{ltp = "affine4_ltp", bp = "affine4_bp"},
{dim_in = {2048}, dim_out = {2048}}},
affine5 = {{ltp = "affine5_ltp", bp = "affine5_bp"},
{dim_in = {2048}, dim_out = {2048}}},
affine6 = {{ltp = "affine6_ltp", bp = "affine6_bp"},
{dim_in = {2048}, dim_out = {2048}}},
affine7 = {{ltp = "affine7_ltp", bp = "affine7_bp"},
{dim_in = {2048}, dim_out = {3001}}}
},
["nerv.SigmoidLayer"] =
{
sigmoid0 = {{}, {dim_in = {2048}, dim_out = {2048}}},
sigmoid1 = {{}, {dim_in = {2048}, dim_out = {2048}}},
sigmoid2 = {{}, {dim_in = {2048}, dim_out = {2048}}},
sigmoid3 = {{}, {dim_in = {2048}, dim_out = {2048}}},
sigmoid4 = {{}, {dim_in = {2048}, dim_out = {2048}}},
sigmoid5 = {{}, {dim_in = {2048}, dim_out = {2048}}},
sigmoid6 = {{}, {dim_in = {2048}, dim_out = {2048}}}
},
["nerv.SoftmaxCELayer"] =
{
criterion = {{}, {dim_in = {3001, 1}, dim_out = {}, compressed = true}}
}
}, param_repo, gconf)
end
function make_layer_repo(sublayer_repo, param_repo)
return nerv.LayerRepo(
{
["nerv.DAGLayer"] =
{
global_transf = {{}, {
dim_in = {429}, dim_out = {429},
sub_layers = sublayer_repo,
connections = {
["<input>[1]"] = "blayer1[1]",
["blayer1[1]"] = "wlayer1[1]",
["wlayer1[1]"] = "blayer2[1]",
["blayer2[1]"] = "wlayer2[1]",
["wlayer2[1]"] = "<output>[1]"
}
}},
main = {{}, {
dim_in = {429, 1}, dim_out = {},
sub_layers = sublayer_repo,
connections = {
["<input>[1]"] = "affine0[1]",
["affine0[1]"] = "sigmoid0[1]",
["sigmoid0[1]"] = "affine1[1]",
["affine1[1]"] = "sigmoid1[1]",
["sigmoid1[1]"] = "affine2[1]",
["affine2[1]"] = "sigmoid2[1]",
["sigmoid2[1]"] = "affine3[1]",
["affine3[1]"] = "sigmoid3[1]",
["sigmoid3[1]"] = "affine4[1]",
["affine4[1]"] = "sigmoid4[1]",
["sigmoid4[1]"] = "affine5[1]",
["affine5[1]"] = "sigmoid5[1]",
["sigmoid5[1]"] = "affine6[1]",
["affine6[1]"] = "sigmoid6[1]",
["sigmoid6[1]"] = "affine7[1]",
["affine7[1]"] = "criterion[1]",
["<input>[2]"] = "criterion[2]"
}
}}
}
}, param_repo, gconf)
end
function get_criterion_layer(sublayer_repo)
return sublayer_repo:get_layer("criterion")
end
function get_network(layer_repo)
return layer_repo:get_layer("main")
end
function make_reader(scp_file, layer_repo)
return nerv.TNetReader(gconf,
{
id = "main_scp",
scp_file = scp_file,
conf_file = gconf.htk_conf,
frm_ext = gconf.frm_ext,
mlfs = {
phone_state = {
file = "/slfs1/users/mfy43/swb_ivec/ref.mlf",
format = "map",
format_arg = "/slfs1/users/mfy43/swb_ivec/dict",
dir = "*/",
ext = "lab"
}
},
global_transf = layer_repo:get_layer("global_transf")
})
end
function make_buffer(reader, buffer)
return nerv.SGDBuffer(gconf,
{
buffer_size = gconf.buffer_size,
randomize = gconf.randomize,
readers = {
{ reader = reader,
data = {main_scp = 429, phone_state = 1}}
}
})
end
function get_accuracy(crit)
return crit.total_correct / crit.total_frames * 100
end
function print_stat(crit)
nerv.info("*** training stat begin ***")
nerv.utils.printf("cross entropy:\t%.8f\n", crit.total_ce)
nerv.utils.printf("correct:\t%d\n", crit.total_correct)
nerv.utils.printf("frames:\t%d\n", crit.total_frames)
nerv.utils.printf("err/frm:\t%.8f\n", crit.total_ce / crit.total_frames)
nerv.utils.printf("accuracy:\t%.3f%%\n", get_accuracy(crit))
nerv.info("*** training stat end ***")
end
|