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-rw-r--r--nerv/examples/lmptb/m-tests/dagl_test.lua20
-rw-r--r--nerv/examples/lmptb/rnn/layer_tdag.lua134
2 files changed, 77 insertions, 77 deletions
diff --git a/nerv/examples/lmptb/m-tests/dagl_test.lua b/nerv/examples/lmptb/m-tests/dagl_test.lua
index 02e9c49..9f45b6a 100644
--- a/nerv/examples/lmptb/m-tests/dagl_test.lua
+++ b/nerv/examples/lmptb/m-tests/dagl_test.lua
@@ -98,7 +98,7 @@ end
--global_conf: table
--layerRepo: nerv.LayerRepo
---Returns: a nerv.DAGLayer
+--Returns: a nerv.TDAGLayer
function prepare_dagLayer(global_conf, layerRepo)
printf("%s Initing daglayer ...\n", global_conf.sche_log_pre)
@@ -107,14 +107,14 @@ function prepare_dagLayer(global_conf, layerRepo)
dim_in_t[1] = 1 --input to select_linear layer
dim_in_t[2] = global_conf.vocab:size() --input to softmax label
local connections_t = {
- ["<input>[1]"] = "selectL1[1],0",
- ["selectL1[1]"] = "recurrentL1[1],0",
- ["recurrentL1[1]"] = "sigmoidL1[1],0",
- ["sigmoidL1[1]"] = "outputL[1],0",
- ["sigmoidL1[1]"] = "recurrentL1[2],1",
- ["outputL[1]"] = "softmaxL[1],0",
- ["<input>[2]"] = "softmaxL[2],0",
- ["softmaxL[1]"] = "<output>[1],0"
+ {"<input>[1]", "selectL1[1]", 0},
+ {"selectL1[1]", "recurrentL1[1]", 0},
+ {"recurrentL1[1]", "sigmoidL1[1]", 0},
+ {"sigmoidL1[1]", "outputL[1]", 0},
+ {"sigmoidL1[1]", "recurrentL1[2]", 1},
+ {"outputL[1]", "softmaxL[1]", 0},
+ {"<input>[2]", "softmaxL[2]", 0},
+ {"softmaxL[1]", "<output>[1]", 0}
}
--[[
@@ -127,7 +127,6 @@ function prepare_dagLayer(global_conf, layerRepo)
local dagL = nerv.TDAGLayer("dagL", global_conf, {["dim_in"] = dim_in_t, ["dim_out"] = {1}, ["sub_layers"] = layerRepo,
["connections"] = connections_t,
})
- dagL:init(global_conf.batch_size)
printf("%s Initing DAGLayer end.\n", global_conf.sche_log_pre)
return dagL
end
@@ -162,3 +161,4 @@ global_conf.vocab:build_file(global_conf.train_fn, false)
local paramRepo = prepare_parameters(global_conf, true)
local layerRepo = prepare_layers(global_conf, paramRepo)
local dagL = prepare_dagLayer(global_conf, layerRepo)
+--dagL:init(global_conf.batch_size)
diff --git a/nerv/examples/lmptb/rnn/layer_tdag.lua b/nerv/examples/lmptb/rnn/layer_tdag.lua
index 296e2e6..f417f91 100644
--- a/nerv/examples/lmptb/rnn/layer_tdag.lua
+++ b/nerv/examples/lmptb/rnn/layer_tdag.lua
@@ -1,6 +1,7 @@
local DAGLayer = nerv.class("nerv.TDAGLayer", "nerv.Layer")
local function parse_id(str)
+ --used to parse layerid[portid],time
local id, port, time, _
_, _, id, port, time = string.find(str, "([a-zA-Z0-9_]+)%[([0-9]+)%][,]*([0-9]*)")
if id == nil or port == nil then
@@ -9,14 +10,15 @@ local function parse_id(str)
nerv.error("wrong format of connection id")
end
end
- print(str, id, port, time)
+ --print(str, id, port, time)
port = tonumber(port)
if (time == nil) then
time = 0
else
time = tonumber(time)
end
- return id, port, time
+ --now time don't need to be parsed
+ return id, port
end
local function discover(id, layers, layer_repo)
@@ -29,105 +31,103 @@ local function discover(id, layers, layer_repo)
local dim_in, dim_out = layer:get_dim()
ref = {
layer = layer,
- inputs = {},
- outputs = {},
- err_inputs = {},
- err_outputs = {},
+ inputs_m = {}, --storage for computation
+ outputs_m = {},
+ err_inputs_m = {},
+ err_outputs_m = {},
next_layers = {},
- input_len = #dim_in,
- output_len = #dim_out,
- in_deg = 0,
- visited = false
+ conns_i = {}, --list of inputing connections
+ conns_o = {}, --list of outputing connections
+ dim_in = dim_in, --list of dimensions of ports
+ dim_out = dim_out,
}
layers[id] = ref
end
return ref
end
+local function makeInitialStore(dim, batch_size, global_conf)
+ st = {}
+ for i = 1 - batch_size, batch_size * 2 do
+ st[i] = global_conf.cumat_type(batch_size, dim)
+ end
+end
+
function DAGLayer:__init(id, global_conf, layer_conf)
local layers = {}
- local inputs = {}
- local outputs = {}
+ local inputs_p = {} --map:port of the TDAGLayer to layer ref and port
+ local outputs_p = {}
local dim_in = layer_conf.dim_in
local dim_out = layer_conf.dim_out
- local parsed_conn = {}
+ local parsed_conns = {}
local _
- local time_to
- for from, to in pairs(layer_conf.connections) do
-
- local id_from, port_from, _ = parse_id(from)
- local id_to, port_to, time_to = parse_id(to)
-
+ for _, ll in pairs(layer_conf.connections) do
+ local id_from, port_from = parse_id(ll[1])
+ local id_to, port_to = parse_id(ll[2])
+ local time_to = ll[3]
+
+ print(id_from, id_to, time_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)
+ if (id_from == "<input>") then
+ if (dim_in[port_from] ~= ref_to.dim_in[port_to] or time_to ~= 0) then
+ nerv.error("mismatch dimension or wrong time %s,%s,%d", ll[1], ll[2], ll[3])
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)
+ inputs_p[port_from] = {["ref"] = ref_to, ["port"] = port_to}
+ elseif (id_to == "<output>") then
+ if (dim_out[port_to] ~= ref_from.dim_out[port_from] or time_to ~= 0) then
+ nerv.error("mismatch dimension or wrong time %s,%s,%d", ll[1], ll[2], ll[3])
end
- outputs[port_to] = {ref_from, port_from}
- ref_from.outputs[port_from] = outputs -- just a place holder
+ outputs_p[port_to] = {["ref"] = ref_from, ["port"] = port_from}
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)
+ conn_now = {
+ ["src"] = {["ref"] = ref_from, ["port"] = port_from},
+ ["dst"] = {["ref"] = ref_to, ["port"] = port_to},
+ ["time"] = time_to
+ }
+ if (ref_to.dim_in[port_to] ~= ref_from.dim_out[port_from]) then
+ nerv.error("mismatch dimension or wrong time %s,%s,%d", ll[1], ll[2], ll[3])
end
-
- table.insert(parsed_conn,
- {{ref_from, port_from}, {ref_to, port_to}})
- 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
+ table.insert(parsed_conns, conn_now)
+ table.insert(ref_to.conns_i, conn_now)
+ table.insert(ref_from.conns_o, conn_now)
end
end
self.layers = layers
- self.inputs = inputs
- self.outputs = outputs
+ self.inputs_p = inputs_p
+ self.outputs_p = outputs_p
self.id = id
self.dim_in = dim_in
self.dim_out = dim_out
- self.parsed_conn = parsed_conn
- self.queue = queue
+ self.parsed_conns = parsed_conns
self.gconf = global_conf
end
-function DAGLayer:init(batch_size)
- for i, conn in ipairs(self.parsed_conn) do
+function DAGLayer:init(seq_size)
+ for i, conn in ipairs(self.parsed_conn) do
local _, output_dim
local ref_from, port_from, ref_to, port_to
- ref_from, port_from = unpack(conn[1])
- ref_to, port_to = unpack(conn[2])
- _, output_dim = ref_from.layer:get_dim()
- local dim = 1
- if output_dim[port_from] > 0 then
- dim = output_dim[port_from]
+ ref_from, port_from = conn.src.ref, conn.src.port
+ ref_to, port_to = conn.dst.ref, conn.dst.port
+ local dim = ref_from.dim_out[port_from]
+ if (dim == 0) then
+ nerv.error("layer %s has a zero dim port", ref_from.layer.id)
end
- local mid = self.gconf.cumat_type(batch_size, dim)
- local err_mid = mid:create()
- ref_from.outputs[port_from] = mid
- ref_to.inputs[port_to] = mid
+ local mid = makeInitialStore(dim, seq_size, global_conf)
+ local err_mid = makeInitialStore(dim, seq_size, global_conf)
+
+ print(ref_from.layer.id, "->", ref_to.layer.id)
+
+ ref_from.outputs_m[port_from] = mid
+ ref_to.inputs_m[port_to] = mid
- ref_from.err_inputs[port_from] = err_mid
- ref_to.err_outputs[port_to] = err_mid
+ ref_from.err_outputs_m[port_from] = err_mid
+ ref_to.err_inputs_m[port_to] = err_mid
end
for id, ref in pairs(self.layers) do
for i = 1, ref.input_len do
@@ -189,7 +189,7 @@ function DAGLayer:set_inputs(input)
end
local layer = self.inputs[i][1]
local port = self.inputs[i][2]
- layer.inputs[port] = input[i]
+ layer.inputs[port] = input[i] --TODO: should be inputs_m
end
end