diff options
| -rw-r--r-- | Makefile | 5 | ||||
| -rw-r--r-- | examples/test_dnn_layers.lua | 9 | ||||
| -rw-r--r-- | examples/test_nn_lib.lua | 63 | ||||
| -rw-r--r-- | io/init.lua | 2 | ||||
| -rw-r--r-- | layer/init.lua | 14 | ||||
| -rw-r--r-- | nerv.lua | 5 | ||||
| -rw-r--r-- | nn/init.lua | 3 | ||||
| -rw-r--r-- | nn/layer_dag.lua | 224 | ||||
| -rw-r--r-- | nn/layer_repo.lua | 34 | ||||
| -rw-r--r-- | nn/param_repo.lua | 26 | ||||
| m--------- | speech | 0 |
11 files changed, 375 insertions, 10 deletions
@@ -8,7 +8,8 @@ LIBS := libnerv.so LUA_LIBS := matrix/init.lua io/init.lua nerv.lua \ pl/utils.lua pl/compat.lua \ layer/init.lua layer/affine.lua layer/sigmoid.lua layer/softmax_ce.lua \ - layer/window.lua layer/bias.lua + layer/window.lua layer/bias.lua \ + nn/init.lua nn/layer_repo.lua nn/param_repo.lua nn/layer_dag.lua INCLUDE := -I build/luajit-2.0/include/luajit-2.0/ -DLUA_USE_APICHECK CUDA_BASE := /usr/local/cuda-6.5 CUDA_INCLUDE := -I $(CUDA_BASE)/include/ @@ -18,7 +19,7 @@ CFLAGS := -Wall -Wextra OBJ_DIR := $(BUILD_DIR)/objs LUA_DIR := $(BUILD_DIR)/lua LIB_DIR := $(BUILD_DIR)/lib -SUBDIR := matrix io layer examples pl +SUBDIR := matrix io layer examples pl nn NVCC := $(CUDA_BASE)/bin/nvcc NVCC_FLAGS := -Xcompiler -fPIC,-Wall,-Wextra diff --git a/examples/test_dnn_layers.lua b/examples/test_dnn_layers.lua index 9be9d71..6e4d98d 100644 --- a/examples/test_dnn_layers.lua +++ b/examples/test_dnn_layers.lua @@ -50,15 +50,14 @@ for i = 0, 3 do sg:propagate(input2, output2) sm:propagate(input3, output3) - -- back_propagate sm:back_propagate(err_output1, err_input1, input3, output3) - sm:update(err_input1, input3, output3) - sg:back_propagate(err_output2, err_input2, input2, output2) - sg:update(err_input2, input2, output2) - af:back_propagate(err_output3, err_input3, input1, output1) + + -- update + sm:update(err_input1, input3, output3) + sg:update(err_input2, input2, output2) af:update(err_input3, input1, output1) diff --git a/examples/test_nn_lib.lua b/examples/test_nn_lib.lua new file mode 100644 index 0000000..fd7167a --- /dev/null +++ b/examples/test_nn_lib.lua @@ -0,0 +1,63 @@ +require 'layer.affine' +require 'layer.sigmoid' +require 'layer.softmax_ce' + +gconf = {lrate = 0.8, wcost = 1e-6, momentum = 0.9, + mat_type = nerv.CuMatrixFloat, + batch_size = 10} + +param_repo = nerv.ParamRepo({"affine.param"}) +sublayer_repo = nerv.LayerRepo( + { + ["nerv.AffineLayer"] = + { + affine1 = {{ltp = "a", bp = "b"}, {dim_in = {429}, dim_out = {2048}}} + }, + ["nerv.SigmoidLayer"] = + { + sigmoid1 = {{}, {dim_in = {2048}, dim_out = {2048}}} + }, + ["nerv.SoftmaxCELayer"] = + { + softmax_ce1 = {{}, {dim_in = {2048, 2048}, dim_out = {}}} + } + }, param_repo, gconf) + +layer_repo = nerv.LayerRepo( + { + ["nerv.DAGLayer"] = + { + main = {{}, { + dim_in = {429, 2048}, dim_out = {}, + sub_layers = sublayer_repo, + connections = { + ["<input>[1]"] = "affine1[1]", + ["affine1[1]"] = "sigmoid1[1]", + ["sigmoid1[1]"] = "softmax_ce1[1]", + ["<input>[2]"] = "softmax_ce1[2]" + } + }} + } + }, param_repo, gconf) + +df = nerv.ChunkFile("input.param", "r") +label = nerv.CuMatrixFloat(10, 2048) +label:fill(0) +for i = 0, 9 do + label[i][i] = 1.0 +end + +input = {df:read_chunk("input", gconf).trans, label} +output = {} +err_input = {} +err_output = {input[1]:create()} +sm = sublayer_repo:get_layer("softmax_ce1") +main = layer_repo:get_layer("main") +main:init() +for i = 0, 3 do + main:propagate(input, output) + main:back_propagate(err_output, err_input, input, output) + main:update(err_input, input, output) + nerv.utils.printf("cross entropy: %.8f\n", sm.total_ce) + nerv.utils.printf("frames: %.8f\n", sm.total_frames) +end diff --git a/io/init.lua b/io/init.lua index 7c312f4..4a663a7 100644 --- a/io/init.lua +++ b/io/init.lua @@ -22,7 +22,7 @@ function nerv.ChunkFile:read_chunk(id, global_conf) if metadata == nil then nerv.error("chunk with id %s does not exist", id) end - local chunk_type = assert(loadstring("return " .. metadata.type))() + local chunk_type = nerv.get_type(metadata.type) local chunk = chunk_type(id, global_conf) chunk:set_info(metadata.info) chunk:read(self:get_chunkdata(id)) diff --git a/layer/init.lua b/layer/init.lua index 4881cb7..c8c691b 100644 --- a/layer/init.lua +++ b/layer/init.lua @@ -46,8 +46,8 @@ function nerv.Layer:back_propagate(next_bp_err, bp_err, input, output) end function nerv.Layer:check_dim_len(len_in, len_out) - local expected_in = table.getn(self.dim_in) - local expected_out = table.getn(self.dim_out) + local expected_in = #self.dim_in + local expected_out = #self.dim_out if len_in > 0 and expected_in ~= len_in then nerv.error("layer %s expects %d inputs, %d given", self.id, len_in, expected_in) @@ -57,3 +57,13 @@ function nerv.Layer:check_dim_len(len_in, len_out) self.id, len_out, expected_out) end end + +function nerv.Layer:get_dim() + return self.dim_in, self.dim_out +end + +require 'layer.affine' +require 'layer.sigmoid' +require 'layer.softmax_ce' +require 'layer.bias' +require 'layer.window' @@ -71,6 +71,11 @@ function table.tostring(tbl) return "{" .. table.concat(result, ",") .. "}" end +function nerv.get_type(typename) + return assert(loadstring("return " .. typename))() +end + require 'matrix.init' require 'io.init' require 'layer.init' +require 'nn.init' diff --git a/nn/init.lua b/nn/init.lua new file mode 100644 index 0000000..1bafa77 --- /dev/null +++ b/nn/init.lua @@ -0,0 +1,3 @@ +require 'nn.layer_repo' +require 'nn.param_repo' +require 'nn.layer_dag' diff --git a/nn/layer_dag.lua b/nn/layer_dag.lua new file mode 100644 index 0000000..8ea28a0 --- /dev/null +++ b/nn/layer_dag.lua @@ -0,0 +1,224 @@ +local DAGLayer = nerv.class("nerv.DAGLayer", "nerv.Layer") + +local function parse_id(str) + local id, port, _ + _, _, id, port = string.find(str, "([a-zA-Z0-9_]+)%[([0-9]+)%]") + if id == nil or port == nil then + _, _, id, port = string.find(str, "(.+)%[([0-9]+)%]") + if not (id == "<input>" or id == "<output>") then + nerv.error("wrong format of connection id") + end + end + port = tonumber(port) + return id, port +end + +local function discover(id, layers, layer_repo) + local ref = layers[id] + if id == "<input>" or id == "<output>" then + return nil + end + if ref == nil then + local layer = layer_repo:get_layer(id) + local dim_in, dim_out = layer:get_dim() + ref = { + layer = layer, + inputs = {}, + outputs = {}, + err_inputs = {}, + err_outputs = {}, + next_layers = {}, + input_len = #dim_in, + output_len = #dim_out, + in_deg = 0, + visited = false + } + layers[id] = ref + end + return ref +end + +function nerv.DAGLayer:__init(id, global_conf, layer_conf) + local layers = {} + local inputs = {} + local outputs = {} + local dim_in = layer_conf.dim_in + local dim_out = layer_conf.dim_out + for from, to in pairs(layer_conf.connections) do + local id_from, port_from = parse_id(from) + local id_to, port_to = parse_id(to) + local ref_from = discover(id_from, layers, layer_conf.sub_layers) + local ref_to = discover(id_to, layers, layer_conf.sub_layers) + local input_dim, output_dim, _ + if ref_from and ref_from.outputs[port_from] ~= nil then + nerv.error("%s has already been attached", from) + end + if ref_to and ref_to.inputs[port_to] ~= nil then + nerv.error("%s has already been attached", to) + end + if id_from == "<input>" then + input_dim, _ = ref_to.layer:get_dim() + if dim_in[port_from] ~= input_dim[port_to] then + nerv.error("mismatching data dimension between %s and %s", from, to) + end + inputs[port_from] = {ref_to, port_to} + ref_to.inputs[port_to] = inputs -- just a place holder + elseif id_to == "<output>" then + _, output_dim = ref_from.layer:get_dim() + if output_dim[port_from] ~= dim_out[port_to] then + nerv.error("mismatching data dimension between %s and %s", from, to) + end + outputs[port_to] = {ref_from, port_from} + ref_from.outputs[port_from] = outputs -- just a place holder + else + _, output_dim = ref_from.layer:get_dim() + input_dim, _ = ref_to.layer:get_dim() + if output_dim[port_from] ~= input_dim[port_to] then + nerv.error("mismatching data dimension between %s and %s", from, to) + end + local mid = global_conf.mat_type(global_conf.batch_size, + output_dim[port_from]) + local err_mid = mid:create() + + ref_from.outputs[port_from] = mid + ref_to.inputs[port_to] = mid + + ref_from.err_inputs[port_from] = err_mid + ref_to.err_outputs[port_to] = err_mid + + table.insert(ref_from.next_layers, ref_to) -- add edge + ref_to.in_deg = ref_to.in_deg + 1 -- increase the in-degree of the target layer + end + end + self.layers = layers + self.inputs = inputs + self.outputs = outputs + self.dim_in = dim_in + self.dim_out = dim_out +end + +function nerv.DAGLayer:init(id) -- topology sort + local queue = {} + local l = 1 + local r = 1 + for id, ref in pairs(self.layers) do + if ref.in_deg == 0 then + table.insert(queue, ref) + nerv.utils.printf("adding source layer: %s\n", id) + r = r + 1 + end + end + if l == r then + nerv.error("loop detected") + end + while l < r do + local cur = queue[l] + cur.visited = true + l = l + 1 + for _, nl in pairs(cur.next_layers) do + nl.in_deg = nl.in_deg - 1 + if nl.in_deg == 0 then + table.insert(queue, nl) + r = r + 1 + end + end + end + for i = 1, #queue do + nerv.utils.printf("queued layer: %s\n", queue[i].layer.id) + end + self.queue = queue + for id, ref in pairs(self.layers) do + -- check wether the graph is connected + if ref.visited == false then + nerv.utils.printf("warning: layer %s is ignored\n", id) + end + for i = 1, ref.input_len do + if ref.inputs[i] == nil then + nerv.error("dangling port %d of layer %s", i, id) + end + end + for i = 1, ref.output_len do + if ref.outputs[i] == nil then + nerv.error("dangling port %d of layer %s", i, id) + end + end + -- initialize sub layers + ref.layer:init() + end + for i = 1, #self.dim_in do + if self.inputs[i] == nil then + nerv.error("dangling port %d of layer <input>", i) + end + end + for i = 1, #self.dim_out do + if self.outputs[i] == nil then + nerv.error("dangling port %d of layer <output>", i) + end + end +end + +function nerv.DAGLayer:set_inputs(input) + for i = 1, #self.dim_in do + local layer = self.inputs[i][1] + local port = self.inputs[i][2] + layer.inputs[port] = input[i] + end +end + +function nerv.DAGLayer:set_outputs(output) + for i = 1, #self.dim_out do + local layer = self.outputs[i][1] + local port = self.outputs[i][2] + layer.outputs[port] = output[i] + end +end + +function nerv.DAGLayer:set_err_inputs(bp_err) + for i = 1, #self.dim_out do + local layer = self.outputs[i][1] + local port = self.outputs[i][2] + layer.err_inputs[port] = bp_err[i] + end +end + +function nerv.DAGLayer:set_err_outputs(next_bp_err) + for i = 1, #self.dim_in do + local layer = self.inputs[i][1] + local port = self.inputs[i][2] + layer.err_outputs[port] = next_bp_err[i] + end +end + +function nerv.DAGLayer:update(bp_err, input, output) + self:set_err_inputs(bp_err) + self:set_inputs(input) + self:set_outputs(output) + for id, ref in pairs(self.queue) do + ref.layer:update(ref.err_inputs, ref.inputs, ref.outputs) + end +end + +function nerv.DAGLayer:propagate(input, output) + self:set_inputs(input) + self:set_outputs(output) + for i = 1, #self.queue do + local ref = self.queue[i] + --[[ + print(ref.inputs[1]) + print(ref.outputs[1]) + print(#ref.inputs, #ref.outputs) + --]] + ref.layer:propagate(ref.inputs, ref.outputs) + end +end + +function nerv.DAGLayer:back_propagate(next_bp_err, bp_err, input, output) + self:set_err_outputs(next_bp_err) + self:set_err_inputs(bp_err) + self:set_inputs(input) + self:set_outputs(output) + for i = #self.queue, 1, -1 do + local ref = self.queue[i] + ref.layer:back_propagate(ref.err_outputs, ref.err_inputs, ref.inputs, ref.outputs) + end +end diff --git a/nn/layer_repo.lua b/nn/layer_repo.lua new file mode 100644 index 0000000..b1d2248 --- /dev/null +++ b/nn/layer_repo.lua @@ -0,0 +1,34 @@ +local LayerRepo = nerv.class("nerv.LayerRepo") + +function LayerRepo:__init(layer_spec, param_repo, global_conf) + local layers = {} + for ltype, llist in pairs(layer_spec) do + local layer_type = nerv.get_type(ltype) + for id, spec in pairs(llist) do + if layers[id] ~= nil then + nerv.error("a layer with id %s already exists", id) + end + nerv.utils.printf("id: %s\n", id) + if type(spec[2]) ~= "table" then + nerv.error("layer config table is need") + end + layer_config = spec[2] + if type(spec[1]) ~= "table" then + nerv.error("parameter description table is needed") + end + for pname, pid in pairs(spec[1]) do + layer_config[pname] = param_repo:get_param(pid, global_conf) + end + layers[id] = layer_type(id, global_conf, layer_config) + end + end + self.layers = layers +end + +function LayerRepo:get_layer(lid) + local layer = self.layers[lid] + if layer == nil then + nerv.error("layer with id %s not found", lid) + end + return layer +end diff --git a/nn/param_repo.lua b/nn/param_repo.lua new file mode 100644 index 0000000..3e37c31 --- /dev/null +++ b/nn/param_repo.lua @@ -0,0 +1,26 @@ +local ParamRepo = nerv.class("nerv.ParamRepo") + +function ParamRepo:__init(param_files) + local param_table = {} + if type(param_files) ~= "table" then + nerv.error("param file table is need") + end + for i = 1, #param_files do + local pf = nerv.ChunkFile(param_files[i], "r") + for cid, cspec in pairs(pf.metadata) do + if param_table[cid] ~= nil then + nerv.error("conflicting chunk id in param files") + end + param_table[cid] = pf + end + end + self.param_table = param_table +end + +function ParamRepo:get_param(pid, global_conf) + local pf = self.param_table[pid] + if pf == nil then + nerv.error("param with id %s not found", pid) + end + return pf:read_chunk(pid, global_conf) +end diff --git a/speech b/speech -Subproject 821aec314824b89e9fe9c3ee467793a05ed89ee +Subproject 0c6ca6a17f06821cd5d612f489ca6cb68c2c4d5 |