diff options
| -rw-r--r-- | nerv/Makefile | 3 | ||||
| -rw-r--r-- | nerv/examples/mmi_chime3.lua | 182 | ||||
| -rw-r--r-- | nerv/examples/mpe_chime3.lua (renamed from nerv/examples/seq_chime.lua) | 0 | ||||
| -rw-r--r-- | nerv/layer/init.lua | 1 | ||||
| -rw-r--r-- | nerv/layer/mmi.lua | 50 |
5 files changed, 235 insertions, 1 deletions
diff --git a/nerv/Makefile b/nerv/Makefile index b874a94..ce178a0 100644 --- a/nerv/Makefile +++ b/nerv/Makefile @@ -31,7 +31,8 @@ OBJS := $(CORE_OBJS) $(NERV_OBJS) $(LUAT_OBJS) LIBS := $(INST_LIBDIR)/libnerv.so $(LIB_PATH)/libnervcore.so $(LIB_PATH)/libluaT.so LUA_LIBS := matrix/init.lua io/init.lua init.lua \ layer/init.lua layer/affine.lua layer/sigmoid.lua layer/softmax_ce.lua layer/softmax.lua \ - layer/window.lua layer/bias.lua layer/combiner.lua layer/mse.lua layer/affine_recurrent.lua layer/mpe.lua \ + layer/window.lua layer/bias.lua layer/combiner.lua layer/mse.lua layer/affine_recurrent.lua \ + layer/mpe.lua layer/mmi.lua \ nn/init.lua nn/layer_repo.lua nn/param_repo.lua nn/layer_dag.lua \ io/sgd_buffer.lua diff --git a/nerv/examples/mmi_chime3.lua b/nerv/examples/mmi_chime3.lua new file mode 100644 index 0000000..a7ad268 --- /dev/null +++ b/nerv/examples/mmi_chime3.lua @@ -0,0 +1,182 @@ +require 'kaldi_io' +gconf = {lrate = 0.00001, wcost = 0, momentum = 0.0, + cumat_type = nerv.CuMatrixFloat, + mmat_type = nerv.MMatrixFloat, + frm_ext = 5, + tr_scp = "ark,o:/slfs6/users/ymz09/kaldi/src/featbin/copy-feats scp:/slfs5/users/ymz09/chime/baseline/ASR/exp/tri4a_dnn_tr05_multi_enhanced_mmi/train.scp ark:- |", + initialized_param = {"/slfs6/users/ymz09/nerv-project/nerv/nerv-speech/kaldi_seq/test/chime3_init_mmi.nerv", + "/slfs6/users/ymz09/nerv-project/nerv/nerv-speech/kaldi_seq/test/chime3_global_transf_mmi.nerv"}, + debug = false} + +function make_layer_repo(param_repo) + local layer_repo = nerv.LayerRepo( + { + -- global transf + ["nerv.BiasLayer"] = + { + blayer1 = {{bias = "bias1"}, {dim_in = {440}, dim_out = {440}}}, + blayer2 = {{bias = "bias2"}, {dim_in = {440}, dim_out = {440}}} + }, + ["nerv.WindowLayer"] = + { + wlayer1 = {{window = "window1"}, {dim_in = {440}, dim_out = {440}}}, + wlayer2 = {{window = "window2"}, {dim_in = {440}, dim_out = {440}}} + }, + -- biased linearity + ["nerv.AffineLayer"] = + { + affine0 = {{ltp = "affine0_ltp", bp = "affine0_bp"}, + {dim_in = {440}, 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 = {2011}}} + }, + ["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.MMILayer"] = + { + mmi_crit = {{}, {dim_in = {2011, -1}, dim_out = {1}, + cmd = { + arg = "--class-frame-counts=/slfs5/users/ymz09/chime/baseline/ASR/exp/tri4a_dnn_tr05_multi_enhanced/ali_train_pdf.counts --acoustic-scale=0.1 --lm-scale=1.0 --learn-rate=0.00001 --drop-frames=true --verbose=1", + mdl = "/slfs5/users/ymz09/chime/baseline/ASR/exp/tri4a_dnn_tr05_multi_enhanced_ali/final.mdl", + lat = "scp:/slfs5/users/ymz09/chime/baseline/ASR/exp/tri4a_dnn_tr05_multi_enhanced_denlats/lat.scp", + ali = "ark:gunzip -c /slfs5/users/ymz09/chime/baseline/ASR/exp/tri4a_dnn_tr05_multi_enhanced_ali/ali.*.gz |" + } + } + } + }, + ["nerv.SoftmaxLayer"] = -- softmax for decode output + { + softmax = {{}, {dim_in = {2011}, dim_out = {2011}}} + } + }, param_repo, gconf) + + layer_repo:add_layers( + { + ["nerv.DAGLayer"] = + { + global_transf = {{}, { + dim_in = {440}, dim_out = {440}, + 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 = {440}, dim_out = {2011}, + 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"] = + { + mmi_output = {{}, { + dim_in = {440, -1}, dim_out = {1}, + sub_layers = layer_repo, + connections = { + ["<input>[1]"] = "main[1]", + ["main[1]"] = "mmi_crit[1]", + ["<input>[2]"] = "mmi_crit[2]", + ["mmi_crit[1]"] = "<output>[1]" + } + }}, + softmax_output = {{}, { + dim_in = {440}, dim_out = {2011}, + 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("mmi_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, + global_transf = layer_repo:get_layer("global_transf"), + mlfs = {} + }) + } + } +end + +function get_input_order() + return {{id = "main_scp", global_transf = true}, + {id = "key"}} +end + +function get_accuracy(layer_repo) + return 0 +end + +function print_stat(layer_repo) + local mmi_crit = layer_repo:get_layer("mmi_crit") + nerv.info("*** training stat begin ***") + nerv.printf("frames:\t\t\t%d\n", mmi_crit.total_frames) + nerv.info("*** training stat end ***") +end diff --git a/nerv/examples/seq_chime.lua b/nerv/examples/mpe_chime3.lua index be723ca..be723ca 100644 --- a/nerv/examples/seq_chime.lua +++ b/nerv/examples/mpe_chime3.lua diff --git a/nerv/layer/init.lua b/nerv/layer/init.lua index b74422f..25dfebb 100644 --- a/nerv/layer/init.lua +++ b/nerv/layer/init.lua @@ -80,3 +80,4 @@ nerv.include('combiner.lua') nerv.include('affine_recurrent.lua') nerv.include('softmax.lua') nerv.include('mpe.lua') +nerv.include('mmi.lua') diff --git a/nerv/layer/mmi.lua b/nerv/layer/mmi.lua new file mode 100644 index 0000000..ecc7f48 --- /dev/null +++ b/nerv/layer/mmi.lua @@ -0,0 +1,50 @@ +require 'libkaldiseq' +local MMILayer = nerv.class("nerv.MMILayer", "nerv.Layer") + +function MMILayer:__init(id, global_conf, layer_conf) + self.id = id + self.gconf = global_conf + self.dim_in = layer_conf.dim_in + self.dim_out = layer_conf.dim_out + self.arg = layer_conf.cmd.arg + self.mdl = layer_conf.cmd.mdl + self.lat = layer_conf.cmd.lat + self.ali = layer_conf.cmd.ali + self:check_dim_len(2, -1) -- two inputs: nn output and utt key +end + +function MMILayer:init(batch_size) + self.total_frames = 0 + self.kaldi_mmi = nerv.KaldiMMI(self.arg, self.mdl, self.lat, self.ali) + if self.kaldi_mmi == nil then + nerv.error("kaldi arguments is expected: %s %s %s %s", self.arg, + self.mdl, self.lat, self.ali) + end +end + +function MMILayer:batch_resize(batch_size) + -- do nothing +end + +function MMILayer:update(bp_err, input, output) + -- no params, therefore do nothing +end + +function MMILayer:propagate(input, output) + self.valid = false + self.valid = self.kaldi_mmi:check(input[1], input[2]) + return self.valid +end + +function MMILayer:back_propagate(bp_err, next_bp_err, input, output) + if self.valid ~= true then + nerv.error("kaldi sequence training back_propagate fail") + end + local mmat = input[1]:new_to_host() + next_bp_err[1]:copy_fromh(self.kaldi_mmi:calc_diff(mmat, input[2])) + self.total_frames = self.total_frames + self.kaldi_mmi:get_num_frames() +end + +function MMILayer:get_params() + return nerv.ParamRepo({}) +end |