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-rw-r--r--Makefile5
-rw-r--r--examples/tnet_preprocessing_example2.lua68
-rw-r--r--init.lua43
-rw-r--r--tnet_io/cwrapper.h1
-rw-r--r--tnet_io/test.c4
5 files changed, 118 insertions, 3 deletions
diff --git a/Makefile b/Makefile
index 531e43f..78c18da 100644
--- a/Makefile
+++ b/Makefile
@@ -1,6 +1,9 @@
.PHONY: tnet
INCLUDE := -I $(BUILD_DIR)/luajit-2.0/include/luajit-2.0
-all: tnet $(OBJ_DIR)/tnet_io/test $(LIB_DIR)/libspeech.so
+all: tnet $(OBJ_DIR)/tnet_io/test $(LIB_DIR)/libspeech.so $(LUA_DIR)/speech/init.lua
+$(LUA_DIR)/speech/init.lua: init.lua
+ mkdir -p $(LUA_DIR)/speech
+ cp $< $@
$(LIB_DIR)/libspeech.so: $(OBJ_DIR)/tnet_io/cwrapper.o $(OBJ_DIR)/init.o $(OBJ_DIR)/tnet_io/init.o $(OBJ_DIR)/tnet_io/libKaldiLib.a
gcc -shared -o $@ $(OBJ_DIR)/tnet_io/cwrapper.o $(OBJ_DIR)/init.o $(OBJ_DIR)/tnet_io/libKaldiLib.a $(OBJ_DIR)/tnet_io/init.o -lstdc++ -Wl,-rpath=$(LIB_DIR) -L$(LIB_DIR) -lnerv
$(OBJ_DIR)/tnet_io/test: $(OBJ_DIR)/tnet_io/cwrapper.o $(OBJ_DIR)/tnet_io/test.o $(OBJ_DIR)/tnet_io/libKaldiLib.a
diff --git a/examples/tnet_preprocessing_example2.lua b/examples/tnet_preprocessing_example2.lua
new file mode 100644
index 0000000..ae8d86b
--- /dev/null
+++ b/examples/tnet_preprocessing_example2.lua
@@ -0,0 +1,68 @@
+require 'speech.init'
+gconf = {mat_type = nerv.CuMatrixFloat,
+ batch_size = 158}
+param_repo = nerv.ParamRepo({"global_transf.nerv"})
+
+sublayer_repo = nerv.LayerRepo(
+ {
+ ["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}}}
+ }
+ }, param_repo, gconf)
+
+layer_repo = nerv.LayerRepo(
+ {
+ ["nerv.DAGLayer"] =
+ {
+ main = {{}, {
+ 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]"
+ }
+ }}
+ }
+ }, param_repo, gconf)
+
+reader = nerv.TNetReader({},
+ {
+ id = "main_scp",
+ scp_file = "/slfs1/users/mfy43/swb_ivec/train_bp.scp",
+ conf_file = "/slfs1/users/mfy43/swb_ivec/plp_0_d_a.conf",
+ frm_ext = 5,
+ mlfs = {
+ ref = {
+ 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("main")
+ })
+
+utter = reader:get_data()
+-- print(utter.main_scp)
+print(utter.ref)
+-- cf2 = nerv.ChunkFile("feat_256", "r")
+-- input = cf2:read_chunk("input", gconf)
+
+-- for i = 0, 157 - 10 do
+-- row_diff = input.trans[i] - utter.main_scp[i]
+-- for j = 0, row_diff:ncol() - 1 do
+-- nerv.utils.printf("%.8f ", row_diff[j])
+-- end
+-- nerv.utils.printf("\n")
+-- end
diff --git a/init.lua b/init.lua
new file mode 100644
index 0000000..1f20096
--- /dev/null
+++ b/init.lua
@@ -0,0 +1,43 @@
+require 'libspeech'
+local TNetReader = nerv.class("nerv.TNetReader", "nerv.DataReader")
+
+function TNetReader:__init(global_conf, reader_conf)
+ self.feat_id = reader_conf.id
+ self.frm_ext = reader_conf.frm_ext
+ self.feat_repo = nerv.TNetFeatureRepo(reader_conf.scp_file,
+ reader_conf.conf_file,
+ reader_conf.frm_ext)
+ self.lab_repo = {}
+ for id, mlf_spec in pairs(reader_conf.mlfs) do
+ self.lab_repo[id] = nerv.TNetLabelRepo(mlf_spec.file,
+ mlf_spec.format,
+ mlf_spec.format_arg,
+ mlf_spec.dir,
+ mlf_spec.ext)
+ end
+ self.global_transf = reader_conf.global_transf
+end
+
+function TNetReader:get_data()
+ local res = {}
+ local frm_ext = self.frm_ext
+ local step = frm_ext * 2 + 1
+ local feat_utter = self.feat_repo:cur_utter()
+ local expanded = nerv.CuMatrixFloat(feat_utter:nrow(), feat_utter:ncol() * step)
+ expanded:expand_frm(nerv.CuMatrixFloat.new_from_host(feat_utter), frm_ext)
+ local rearranged = expanded:create()
+ rearranged:rearrange_frm(expanded, step)
+ local input = {rearranged}
+ local output = {rearranged:create()}
+ self.global_transf:init()
+ self.global_transf:propagate(input, output)
+ expanded = nerv.CuMatrixFloat(output[1]:nrow() - frm_ext * 2, output[1]:ncol())
+ expanded:copy_fromd(output[1], frm_ext, feat_utter:nrow() - frm_ext)
+ res[self.feat_id] = expanded
+ for id, repo in pairs(self.lab_repo) do
+ local lab_utter = repo:get_utter(self.feat_repo, expanded:nrow())
+ res[id] = lab_utter
+ end
+ self.feat_repo:next()
+ return res
+end
diff --git a/tnet_io/cwrapper.h b/tnet_io/cwrapper.h
index 810901b..a34f090 100644
--- a/tnet_io/cwrapper.h
+++ b/tnet_io/cwrapper.h
@@ -1,6 +1,7 @@
#ifndef NERV_TNET_IO_CWRAPPER
#define NERV_TNET_IO_CWRAPPER
#include "../../matrix/generic/matrix.h"
+#include "../../common.h"
#ifdef __cplusplus
extern "C" {
#endif
diff --git a/tnet_io/test.c b/tnet_io/test.c
index a5b8f55..8c06805 100644
--- a/tnet_io/test.c
+++ b/tnet_io/test.c
@@ -22,7 +22,7 @@ int main() {
"/slfs1/users/mfy43/swb_ivec/train_bp.scp",
"/slfs1/users/mfy43/swb_ivec/plp_0_d_a.conf", 5);
Matrix *feat_utter;
- feat_utter = tnet_feature_repo_read_utterance(feat_repo);
+ feat_utter = tnet_feature_repo_read_utterance(feat_repo, NULL);
TNetLabelRepo *lab_repo = tnet_label_repo_new(
"/slfs1/users/mfy43/swb_ivec/ref.mlf",
@@ -33,7 +33,7 @@ int main() {
Matrix *lab_utter = tnet_label_repo_read_utterance(lab_repo,
feat_utter->nrow - 5 * 2,
tnet_feature_repo_current_samplerate(feat_repo),
- tnet_feature_repo_current_tag(feat_repo));
+ tnet_feature_repo_current_tag(feat_repo), NULL);
print_nerv_matrix(lab_utter);
return 0;
}