diff options
| author | Qi Liu <[email protected]> | 2016-03-15 10:56:35 +0800 |
|---|---|---|
| committer | Qi Liu <[email protected]> | 2016-03-15 10:56:35 +0800 |
| commit | 51a3beef4a7cbd94278a406664212b6597aedd93 (patch) | |
| tree | 298d976792164102cf7e12fb1f351f2f50857326 | |
| parent | b08da1fef90e93b188704056cdae651d7865f98d (diff) | |
speedup duplicate layer
| -rw-r--r-- | Makefile | 2 | ||||
| -rw-r--r-- | nerv/examples/network_debug/config.lua | 2 | ||||
| -rw-r--r-- | nerv/layer/duplicate.lua | 5 | ||||
| -rw-r--r-- | nerv/nn/network.lua | 30 |
4 files changed, 30 insertions, 9 deletions
@@ -27,7 +27,7 @@ export BLAS_LDFLAGS Penlight all: nerv -submodule: luajit luajit Penlight +submodule: luajit luarocks Penlight luajit: PREFIX=$(PREFIX) ./tools/build_luajit.sh luarocks: diff --git a/nerv/examples/network_debug/config.lua b/nerv/examples/network_debug/config.lua index 093bde2..e20d5a9 100644 --- a/nerv/examples/network_debug/config.lua +++ b/nerv/examples/network_debug/config.lua @@ -12,7 +12,7 @@ function get_global_conf() layer_num = 1, chunk_size = 15, batch_size = 20, - max_iter = 1, + max_iter = 35, param_random = function() return (math.random() / 5 - 0.1) end, dropout_rate = 0.5, timer = nerv.Timer(), diff --git a/nerv/layer/duplicate.lua b/nerv/layer/duplicate.lua index 137472b..2621cdf 100644 --- a/nerv/layer/duplicate.lua +++ b/nerv/layer/duplicate.lua @@ -20,10 +20,7 @@ function DuplicateLayer:batch_resize() end function DuplicateLayer:propagate(input, output) - for i = 1, #self.dim_out do - output[i]:copy_from(input[1]) - -- FIXME: use reference copy to speed up - end + -- do nothing, use reference copy in nn/network.lua end function DuplicateLayer:back_propagate(bp_err, next_bp_err) diff --git a/nerv/nn/network.lua b/nerv/nn/network.lua index 910cdad..b06028e 100644 --- a/nerv/nn/network.lua +++ b/nerv/nn/network.lua @@ -228,9 +228,11 @@ function network:make_initial_store() err_memory[t][i][j] = self.mat_type(self.batch_size, dim_in[j]) err_memory[t][i][j]:fill(0) end - for j = 1, #dim_out do - memory[t][i][j] = self.mat_type(self.batch_size, dim_out[j]) - memory[t][i][j]:fill(self.nn_act_default) + if t < 1 or t > self.chunk_size or not nerv.is_type(self.layers[i], 'nerv.DuplicateLayer') then + for j = 1, #dim_out do + memory[t][i][j] = self.mat_type(self.batch_size, dim_out[j]) + memory[t][i][j]:fill(self.nn_act_default) + end end end if t < 1 or t > self.chunk_size then @@ -288,6 +290,28 @@ function network:make_initial_store() end end + -- reference copy for duplicate layer + for i = 1, #self.queue do + local t, id = self.queue[i].chunk, self.queue[i].id + if nerv.is_type(self.layers[id], 'nerv.DuplicateLayer') then + local _, dim_out = self.layers[id]:get_dim() + for j = 1, #dim_out do + if self.output[t][id][j] ~= nil then + nerv.error('duplicate output reference not nil') + end + self.output[t][id][j] = self.input[t][id][1] + local edge = self.output_conn[id][j] + local to, port, time = edge[1], edge[2], edge[3] + t + if time >= 1 and time <= self.chunk_size then + if self.input[time][to][port] ~= nil then + nerv.error('duplicate input reference not nil') + end + self.input[time][to][port] = self.output[t][id][j] + end + end + end + end + -- check dangling reference for t = 1, self.chunk_size do for i = 1, #self.dim_in do |