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authorDeterminant <[email protected]>2015-08-04 14:41:22 +0800
committerDeterminant <[email protected]>2015-08-04 14:41:22 +0800
commit462d1982f299c8be4ae9a746e6ae7d04c04faa33 (patch)
treed2230feda37d972989bb573fbe11f7ea6b4ac279 /embedding_example/swb_baseline_decode.lua
parent5b16335a903551ffef4fafa88d67146b9131a74e (diff)
add embedding_example
Diffstat (limited to 'embedding_example/swb_baseline_decode.lua')
-rw-r--r--embedding_example/swb_baseline_decode.lua109
1 files changed, 109 insertions, 0 deletions
diff --git a/embedding_example/swb_baseline_decode.lua b/embedding_example/swb_baseline_decode.lua
new file mode 100644
index 0000000..14a463b
--- /dev/null
+++ b/embedding_example/swb_baseline_decode.lua
@@ -0,0 +1,109 @@
+require 'htk_io'
+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",
+ initialized_param = {"/slfs1/users/mfy43/swb_init.nerv",
+ "/slfs1/users/mfy43/swb_global_transf.nerv"},
+ debug = false}
+
+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.SoftmaxLayer"] =
+ {
+ soutput = {{}, {dim_in = {3001}, dim_out = {3001}}}
+ }
+ }, 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}, dim_out = {3001},
+ 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]"] = "soutput[1]",
+ ["soutput[1]"] = "<output>[1]"
+ }
+ }}
+ }
+ }, param_repo, gconf)
+end
+
+function get_network(layer_repo)
+ return layer_repo:get_layer("main")
+end