diff options
Diffstat (limited to 'kaldi_decode/src')
| -rw-r--r-- | kaldi_decode/src/Makefile | 12 | ||||
| -rw-r--r-- | kaldi_decode/src/asr_propagator.lua | 84 | ||||
| -rw-r--r-- | kaldi_decode/src/nerv4decode.lua | 79 | ||||
| -rw-r--r-- | kaldi_decode/src/nnet-forward.cc | 18 |
4 files changed, 93 insertions, 100 deletions
diff --git a/kaldi_decode/src/Makefile b/kaldi_decode/src/Makefile deleted file mode 100644 index 7cffbc2..0000000 --- a/kaldi_decode/src/Makefile +++ /dev/null @@ -1,12 +0,0 @@ -# Change KDIR to `kaldi-trunk' path (Kaldi must be compiled with --share) -KDIR := /slfs6/users/ymz09/kaldi/ -NERVDIR := /slfs6/users/ymz09/nerv-project/nerv/ -CUDADIR := /usr/local/cuda/ - -nnet-forward: - g++ -msse -msse2 -Wall -I $(KDIR)/src/ -pthread -DKALDI_DOUBLEPRECISION=0 -DHAVE_POSIX_MEMALIGN -Wno-sign-compare -Wno-unused-local-typedefs -Winit-self -DHAVE_EXECINFO_H=1 -rdynamic -DHAVE_CXXABI_H -DHAVE_ATLAS -I $(KDIR)/tools/ATLAS/include -I $(KDIR)/tools/openfst/include -Wno-sign-compare -g -fPIC -DHAVE_CUDA -I $(CUDADIR)/include -DKALDI_NO_EXPF -I $(NERVDIR)/install//include/luajit-2.0/ -I $(NERVDIR)/install/include/ -DLUA_USE_APICHECK -c -o nnet-forward.o nnet-forward.cc - g++ -rdynamic -Wl,-rpath=$(KDIR)/tools/openfst/lib -L$(CUDADIR)/lib64 -Wl,-rpath=$(CUDADIR)/lib64 -Wl,-rpath=$(KDIR)/src/lib -L. -L$(KDIR)/src/nnet/ -L$(KDIR)/src/cudamatrix/ -L$(KDIR)/src/lat/ -L$(KDIR)/src/hmm/ -L$(KDIR)/src/tree/ -L$(KDIR)/src/matrix/ -L$(KDIR)/src/util/ -L$(KDIR)/src/base/ nnet-forward.o $(KDIR)/src/nnet//libkaldi-nnet.so $(KDIR)/src/cudamatrix//libkaldi-cudamatrix.so $(KDIR)/src/lat//libkaldi-lat.so $(KDIR)/src/hmm//libkaldi-hmm.so $(KDIR)/src/tree//libkaldi-tree.so $(KDIR)/src/matrix//libkaldi-matrix.so $(KDIR)/src/util//libkaldi-util.so $(KDIR)/src/base//libkaldi-base.so -L$(KDIR)/tools/openfst/lib -lfst /usr/lib/liblapack.so /usr/lib/libcblas.so /usr/lib/libatlas.so /usr/lib/libf77blas.so -lm -lpthread -ldl -lcublas -lcudart -lkaldi-nnet -lkaldi-cudamatrix -lkaldi-lat -lkaldi-hmm -lkaldi-tree -lkaldi-matrix -lkaldi-util -lkaldi-base -lstdc++ -L$(NERVDIR)/install/lib -Wl,-rpath=$(NERVDIR)/install/lib -lnervcore -lluaT -rdynamic -Wl,-rpath=$(KDIR)//tools/openfst/lib -L$(CUDADIR)/lib64 -Wl,-rpath=$(CUDADIR)/lib64 -Wl,-rpath=$(KDIR)//src/lib -lfst -lm -lpthread -ldl -lcublas -lcudart -L $(NERVDIR)/luajit-2.0/src/ -lluajit -o nnet-forward - -clean: - -rm nnet-forward.o nnet-forward - diff --git a/kaldi_decode/src/asr_propagator.lua b/kaldi_decode/src/asr_propagator.lua new file mode 100644 index 0000000..5d0ad7c --- /dev/null +++ b/kaldi_decode/src/asr_propagator.lua @@ -0,0 +1,84 @@ +print = function(...) io.write(table.concat({...}, "\t")) end +io.output('/dev/null') +-- path and cpath are correctly set by `path.sh` +local k,l,_=pcall(require,"luarocks.loader") _=k and l.add_context("nerv","scm-1") +require 'nerv' +nerv.printf("*** NERV: A Lua-based toolkit for high-performance deep learning (alpha) ***\n") +nerv.info("automatically initialize a default MContext...") +nerv.MMatrix._default_context = nerv.MContext() +nerv.info("the default MContext is ok") +-- only for backward compatibilty, will be removed in the future +local function _add_profile_method(cls) + local c = cls._default_context + cls.print_profile = function () c:print_profile() end + cls.clear_profile = function () c:clear_profile() end +end +_add_profile_method(nerv.MMatrix) + +function build_propagator(ifname, feature) + local param_repo = nerv.ParamRepo() + param_repo:import(ifname, nil, gconf) + local layer_repo = make_layer_repo(param_repo) + local network = get_decode_network(layer_repo) + local global_transf = get_global_transf(layer_repo) + local input_order = get_decode_input_order() + local readers = make_decode_readers(feature, layer_repo) + + local batch_propagator = function() + local data = nil + for ri = 1, #readers do + data = readers[ri].reader:get_data() + if data ~= nil then + break + end + end + + if data == nil then + return "", nil + end + + gconf.batch_size = data[input_order[1].id]:nrow() + network:init(gconf.batch_size) + + local input = {} + for i, e in ipairs(input_order) do + local id = e.id + if data[id] == nil then + nerv.error("input data %s not found", id) + end + local transformed + if e.global_transf then + transformed = nerv.speech_utils.global_transf(data[id], + global_transf, + gconf.frm_ext or 0, 0, + gconf) + else + transformed = data[id] + end + table.insert(input, transformed) + end + local output = {nerv.MMatrixFloat(input[1]:nrow(), network.dim_out[1])} + network:propagate(input, output) + + local utt = data["key"] + if utt == nil then + nerv.error("no key found.") + end + + collectgarbage("collect") + return utt, output[1] + end + + return batch_propagator +end + +function init(config, feature) + dofile(config) + gconf.use_cpu = true -- use CPU to decode + trainer = build_propagator(gconf.decode_param, feature) +end + +function feed() + local utt, mat = trainer() + return utt, mat +end diff --git a/kaldi_decode/src/nerv4decode.lua b/kaldi_decode/src/nerv4decode.lua deleted file mode 100644 index b2ff344..0000000 --- a/kaldi_decode/src/nerv4decode.lua +++ /dev/null @@ -1,79 +0,0 @@ -package.path="/home/slhome/ymz09/.luarocks/share/lua/5.1/?.lua;/home/slhome/ymz09/.luarocks/share/lua/5.1/?/init.lua;/slfs6/users/ymz09/nerv-project/nerv/install/share/lua/5.1/?.lua;/slfs6/users/ymz09/nerv-project/nerv/install/share/lua/5.1/?/init.lua;"..package.path; -package.cpath="/home/slhome/ymz09/.luarocks/lib/lua/5.1/?.so;/slfs6/users/ymz09/nerv-project/nerv/install/lib/lua/5.1/?.so;"..package.cpath; -local k,l,_=pcall(require,"luarocks.loader") _=k and l.add_context("nerv","scm-1") -require 'nerv' - -function build_trainer(ifname, feature) - local param_repo = nerv.ParamRepo() - param_repo:import(ifname, nil, gconf) - local layer_repo = make_layer_repo(param_repo) - local network = get_decode_network(layer_repo) - local global_transf = get_global_transf(layer_repo) - local input_order = get_input_order() - local readers = make_readers(feature, layer_repo) - network:init(1) - - local iterative_trainer = function() - local data = nil - for ri = 1, #readers, 1 do - data = readers[ri].reader:get_data() - if data ~= nil then - break - end - end - - if data == nil then - return "", nil - end - - local input = {} - for i, e in ipairs(input_order) do - local id = e.id - if data[id] == nil then - nerv.error("input data %s not found", id) - end - local transformed - if e.global_transf then - local batch = gconf.cumat_type(data[id]:nrow(), data[id]:ncol()) - batch:copy_fromh(data[id]) - transformed = nerv.speech_utils.global_transf(batch, - global_transf, - gconf.frm_ext or 0, 0, - gconf) - else - transformed = data[id] - end - table.insert(input, transformed) - end - local output = {nerv.CuMatrixFloat(input[1]:nrow(), network.dim_out[1])} - network:batch_resize(input[1]:nrow()) - network:propagate(input, output) - - local utt = data["key"] - if utt == nil then - nerv.error("no key found.") - end - - local mat = nerv.MMatrixFloat(output[1]:nrow(), output[1]:ncol()) - output[1]:copy_toh(mat) - - collectgarbage("collect") - return utt, mat - end - - return iterative_trainer -end - -function init(config, feature) - local tmp = io.write - io.write = function(...) - end - dofile(config) - trainer = build_trainer(gconf.decode_param, feature) - io.write = tmp -end - -function feed() - local utt, mat = trainer() - return utt, mat -end diff --git a/kaldi_decode/src/nnet-forward.cc b/kaldi_decode/src/nnet-forward.cc index 007f623..8781705 100644 --- a/kaldi_decode/src/nnet-forward.cc +++ b/kaldi_decode/src/nnet-forward.cc @@ -21,9 +21,9 @@ extern "C"{ #include "lua.h" #include "lauxlib.h" #include "lualib.h" -#include "nerv/matrix/matrix.h" -#include "nerv/common.h" -#include "nerv/luaT/luaT.h" +#include "nerv/lib/matrix/matrix.h" +#include "nerv/lib/common.h" +#include "nerv/lib/luaT/luaT.h" } #include <limits> @@ -46,7 +46,7 @@ int main(int argc, char *argv[]) { const char *usage = "Perform forward pass through Neural Network.\n" "\n" - "Usage: nnet-forward [options] <nerv-config> <feature-rspecifier> <feature-wspecifier> [nerv4decode.lua]\n" + "Usage: nnet-forward [options] <nerv-config> <feature-rspecifier> <feature-wspecifier> [asr_propagator.lua]\n" "e.g.: \n" " nnet-forward config.lua ark:features.ark ark:mlpoutput.ark\n"; @@ -78,9 +78,9 @@ int main(int argc, char *argv[]) { std::string config = po.GetArg(1), feature_rspecifier = po.GetArg(2), feature_wspecifier = po.GetArg(3), - nerv4decode = "src/nerv4decode.lua"; - if(po.NumArgs() >= 4) - nerv4decode = po.GetArg(4); + propagator = "src/asr_propagator.lua"; + if(po.NumArgs() >= 4) + propagator = po.GetArg(4); //Select the GPU #if HAVE_CUDA==1 @@ -99,8 +99,8 @@ int main(int argc, char *argv[]) { lua_State *L = lua_open(); luaL_openlibs(L); - if(luaL_loadfile(L, nerv4decode.c_str())) - KALDI_ERR << "luaL_loadfile() " << nerv4decode << " failed " << lua_tostring(L, -1); + if(luaL_loadfile(L, propagator.c_str())) + KALDI_ERR << "luaL_loadfile() " << propagator << " failed " << lua_tostring(L, -1); if(lua_pcall(L, 0, 0, 0)) KALDI_ERR << "lua_pall failed " << lua_tostring(L, -1); |