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-rw-r--r--examples/swb_baseline.lua87
1 files changed, 45 insertions, 42 deletions
diff --git a/examples/swb_baseline.lua b/examples/swb_baseline.lua
index 28cc6d5..8b7e01a 100644
--- a/examples/swb_baseline.lua
+++ b/examples/swb_baseline.lua
@@ -6,14 +6,10 @@ gconf = {lrate = 0.8, wcost = 1e-6, momentum = 0.9,
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 = "/slfs1/users/mfy43/swb_global_transf.nerv",
- initialized_param = "/slfs1/users/mfy43/swb_init.nerv",
+ initialized_param = {"/slfs1/users/mfy43/swb_init.nerv",
+ "/slfs1/users/mfy43/swb_global_transf.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(
{
@@ -60,7 +56,7 @@ function make_sublayer_repo(param_repo)
},
["nerv.SoftmaxCELayer"] =
{
- criterion = {{}, {dim_in = {3001, 1}, dim_out = {}, compressed = true}}
+ ce_crit = {{}, {dim_in = {3001, 1}, dim_out = {1}, compressed = true}}
}
}, param_repo, gconf)
end
@@ -82,7 +78,7 @@ function make_layer_repo(sublayer_repo, param_repo)
}
}},
main = {{}, {
- dim_in = {429, 1}, dim_out = {},
+ dim_in = {429, 1}, dim_out = {1},
sub_layers = sublayer_repo,
connections = {
["<input>[1]"] = "affine0[1]",
@@ -100,8 +96,9 @@ function make_layer_repo(sublayer_repo, param_repo)
["sigmoid5[1]"] = "affine6[1]",
["affine6[1]"] = "sigmoid6[1]",
["sigmoid6[1]"] = "affine7[1]",
- ["affine7[1]"] = "criterion[1]",
- ["<input>[2]"] = "criterion[2]"
+ ["affine7[1]"] = "ce_crit[1]",
+ ["<input>[2]"] = "ce_crit[2]",
+ ["ce_crit[1]"] = "<output>[1]"
}
}}
}
@@ -109,55 +106,61 @@ function make_layer_repo(sublayer_repo, param_repo)
end
function get_criterion_layer(sublayer_repo)
- return sublayer_repo:get_layer("criterion")
+ return sublayer_repo:get_layer("ce_crit")
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")
- })
+function make_readers(scp_file, layer_repo)
+ return {
+ {reader = 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")
+ }),
+ data = {main_scp = 429, phone_state = 1}}
+ }
end
-function make_buffer(reader, buffer)
+function make_buffer(readers)
return nerv.SGDBuffer(gconf,
{
buffer_size = gconf.buffer_size,
randomize = gconf.randomize,
- readers = {
- { reader = reader,
- data = {main_scp = 429, phone_state = 1}}
- }
+ readers = readers
})
end
-function get_accuracy(crit)
- return crit.total_correct / crit.total_frames * 100
+function get_input_order()
+ return {"main_scp", "phone_state"}
+end
+
+function get_accuracy(sublayer_repo)
+ local ce_crit = sublayer_repo:get_layer("ce_crit")
+ return ce_crit.total_correct / ce_crit.total_frames * 100
end
-function print_stat(crit)
+function print_stat(sublayer_repo)
+ local ce_crit = sublayer_repo:get_layer("ce_crit")
nerv.info("*** training stat begin ***")
- nerv.utils.printf("cross entropy:\t\t%.8f\n", crit.total_ce)
- nerv.utils.printf("correct:\t\t%d\n", crit.total_correct)
- nerv.utils.printf("frames:\t\t\t%d\n", crit.total_frames)
- nerv.utils.printf("err/frm:\t\t%.8f\n", crit.total_ce / crit.total_frames)
- nerv.utils.printf("accuracy:\t\t%.3f%%\n", get_accuracy(crit))
+ nerv.printf("cross entropy:\t\t%.8f\n", ce_crit.total_ce)
+ nerv.printf("correct:\t\t%d\n", ce_crit.total_correct)
+ nerv.printf("frames:\t\t\t%d\n", ce_crit.total_frames)
+ nerv.printf("err/frm:\t\t%.8f\n", ce_crit.total_ce / ce_crit.total_frames)
+ nerv.printf("accuracy:\t\t%.3f%%\n", get_accuracy(sublayer_repo))
nerv.info("*** training stat end ***")
end