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authorDeterminant <[email protected]>2015-08-14 11:51:42 +0800
committerDeterminant <[email protected]>2015-08-14 11:51:42 +0800
commit96a32415ab43377cf1575bd3f4f2980f58028209 (patch)
tree30a2d92d73e8f40ac87b79f6f56e227bfc4eea6e /kaldi_io/example/swb_baseline.lua
parentc177a7549bd90670af4b29fa813ddea32cfe0f78 (diff)
add implementation for kaldi io (by ymz)
Diffstat (limited to 'kaldi_io/example/swb_baseline.lua')
-rw-r--r--kaldi_io/example/swb_baseline.lua193
1 files changed, 193 insertions, 0 deletions
diff --git a/kaldi_io/example/swb_baseline.lua b/kaldi_io/example/swb_baseline.lua
new file mode 100644
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+++ b/kaldi_io/example/swb_baseline.lua
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+require 'kaldi_io'
+gconf = {lrate = 0.8, wcost = 1e-6, momentum = 0.9,
+ cumat_type = nerv.CuMatrixFloat,
+ mmat_type = nerv.MMatrixFloat,
+ frm_ext = 5,
+ tr_scp = "ark:/slfs6/users/ymz09/kaldi/src/featbin/copy-feats scp:/slfs6/users/ymz09/swb_ivec/train_bp.scp ark:- |",
+ cv_scp = "ark:/slfs6/users/ymz09/kaldi/src/featbin/copy-feats scp:/slfs6/users/ymz09/swb_ivec/train_cv.scp ark:- |",
+ initialized_param = {"/slfs6/users/ymz09/swb_ivec/swb_init.nerv",
+ "/slfs6/users/ymz09/swb_ivec/swb_global_transf.nerv"},
+ debug = false}
+
+function make_layer_repo(param_repo)
+ local layer_repo = 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"] = -- softmax + ce criterion layer for finetune output
+ {
+ ce_crit = {{}, {dim_in = {3001, 1}, dim_out = {1}, compressed = true}}
+ },
+ ["nerv.SoftmaxLayer"] = -- softmax for decode output
+ {
+ softmax = {{}, {dim_in = {3001}, dim_out = {3001}}}
+ }
+ }, param_repo, gconf)
+
+ layer_repo:add_layers(
+ {
+ ["nerv.DAGLayer"] =
+ {
+ global_transf = {{}, {
+ dim_in = {429}, dim_out = {429},
+ sub_layers = layer_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 = layer_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]"] = "<output>[1]"
+ }
+ }}
+ }
+ }, param_repo, gconf)
+
+ layer_repo:add_layers(
+ {
+ ["nerv.DAGLayer"] =
+ {
+ ce_output = {{}, {
+ dim_in = {429, 1}, dim_out = {1},
+ sub_layers = layer_repo,
+ connections = {
+ ["<input>[1]"] = "main[1]",
+ ["main[1]"] = "ce_crit[1]",
+ ["<input>[2]"] = "ce_crit[2]",
+ ["ce_crit[1]"] = "<output>[1]"
+ }
+ }},
+ softmax_output = {{}, {
+ dim_in = {429}, dim_out = {3001},
+ sub_layers = layer_repo,
+ connections = {
+ ["<input>[1]"] = "main[1]",
+ ["main[1]"] = "softmax[1]",
+ ["softmax[1]"] = "<output>[1]"
+ }
+ }}
+ }
+ }, param_repo, gconf)
+
+ return layer_repo
+end
+
+function get_network(layer_repo)
+ return layer_repo:get_layer("ce_output")
+end
+
+function get_decode_network(layer_repo)
+ return layer_repo:get_layer("softmax_output")
+end
+
+function get_global_transf(layer_repo)
+ return layer_repo:get_layer("global_transf")
+end
+
+function make_readers(feature_rspecifier, layer_repo)
+ return {
+ {reader = nerv.KaldiReader(gconf,
+ {
+ id = "main_scp",
+ feature_rspecifier = feature_rspecifier,
+ frm_ext = gconf.frm_ext,
+ mlfs = {
+ phone_state = {
+ targets_rspecifier = "ark:/slfs6/users/ymz09/kaldi/src/bin/ali-to-pdf /slfs6/users/ymz09/swb_ivec/final.mdl \"ark:gunzip -c /slfs6/users/ymz09/swb_ivec/ali.*.gz |\" ark:- | /slfs6/users/ymz09/kaldi/src/bin/ali-to-post ark:- ark:- |",
+ format = "map"
+ }
+ },
+ global_transf = layer_repo:get_layer("global_transf")
+ }),
+ data = {main_scp = 429, phone_state = 1}}
+ }
+end
+
+function make_buffer(readers)
+ return nerv.SGDBuffer(gconf,
+ {
+ buffer_size = gconf.buffer_size,
+ randomize = gconf.randomize,
+ readers = readers
+ })
+end
+
+function get_input_order()
+ return {"main_scp", "phone_state"}
+end
+
+function get_accuracy(layer_repo)
+ local ce_crit = layer_repo:get_layer("ce_crit")
+ return ce_crit.total_correct / ce_crit.total_frames * 100
+end
+
+function print_stat(layer_repo)
+ local ce_crit = layer_repo:get_layer("ce_crit")
+ nerv.info("*** training stat begin ***")
+ 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(layer_repo))
+ nerv.info("*** training stat end ***")
+end