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authortxh18 <[email protected]>2015-11-10 15:44:08 +0800
committertxh18 <[email protected]>2015-11-10 15:44:08 +0800
commit8f8ad5da3d178bdd74c76cea37946f5c950ed5c0 (patch)
treec10db183df8cfb01bb03334633928a1051b7d866
parent12fb5f1f473a04fc2472ce5cc9273ba1afa6176d (diff)
bug fix : changed zero-filling across borders
-rw-r--r--nerv/examples/lmptb/m-tests/tnn_test.lua3
-rw-r--r--nerv/examples/lmptb/rnn/tnn.lua31
2 files changed, 20 insertions, 14 deletions
diff --git a/nerv/examples/lmptb/m-tests/tnn_test.lua b/nerv/examples/lmptb/m-tests/tnn_test.lua
index ac9f570..40e332c 100644
--- a/nerv/examples/lmptb/m-tests/tnn_test.lua
+++ b/nerv/examples/lmptb/m-tests/tnn_test.lua
@@ -297,6 +297,7 @@ prepare_parameters(global_conf, true) --randomly generate parameters
print("===INITIAL VALIDATION===")
local tnn, paramRepo = load_net(global_conf)
local result = lm_process_file(global_conf, global_conf.valid_fn, tnn, false) --false update!
+nerv.LMUtil.wait(3)
ppl_rec = {}
lr_rec = {}
ppl_rec[0] = result:ppl_net("rnn") ppl_last = ppl_rec[0]
@@ -316,7 +317,7 @@ for iter = 1, global_conf.max_iter, 1 do
ppl_rec[iter] = result:ppl_net("rnn")
lr_rec[iter] = global_conf.lrate
if (ppl_last / ppl_rec[iter] < 1.03 or lr_half == true) then
- global_conf.lrate = (global_conf.lrate / 2)
+ global_conf.lrate = (global_conf.lrate * 0.6)
lr_half = true
end
if (ppl_rec[iter] < ppl_last) then
diff --git a/nerv/examples/lmptb/rnn/tnn.lua b/nerv/examples/lmptb/rnn/tnn.lua
index dfcef63..10b501e 100644
--- a/nerv/examples/lmptb/rnn/tnn.lua
+++ b/nerv/examples/lmptb/rnn/tnn.lua
@@ -369,6 +369,7 @@ function TNN:propagate_dfs(ref, t)
--ok, do propagate
--print("debug ok, propagating");
+ --[[
if (bit.band(self.feeds_now.flagsPack_now[t], bit.bor(nerv.TNN.FC.SEQ_START, nerv.TNN.FC.SEQ_END)) > 0) then --flush cross-border history
for i = 1, self.batch_size do
local seq_start = bit.band(self.feeds_now.flags_now[t][i], nerv.TNN.FC.SEQ_START)
@@ -383,15 +384,16 @@ function TNN:propagate_dfs(ref, t)
end
end
end
+ ]]--
ref.layer:propagate(ref.inputs_m[t], ref.outputs_m[t], t) --propagate!
if (bit.band(self.feeds_now.flagsPack_now[t], bit.bor(nerv.TNN.FC.SEQ_START, nerv.TNN.FC.SEQ_END)) > 0) then --restore cross-border history
for i = 1, self.batch_size do
local seq_start = bit.band(self.feeds_now.flags_now[t][i], nerv.TNN.FC.SEQ_START)
local seq_end = bit.band(self.feeds_now.flags_now[t][i], nerv.TNN.FC.SEQ_END)
if (seq_start > 0 or seq_end > 0) then
- for p, conn in pairs(ref.i_conns_p) do
- if ((ref.i_conns_p[p].time > 0 and seq_start > 0) or (ref.i_conns_p[p].time < 0 and seq_end > 0)) then
- ref.inputs_m[t][p][i - 1]:copy_fromd(ref.inputs_matbak_p[p][i - 1])
+ for p, conn in pairs(ref.o_conns_p) do
+ if ((ref.o_conns_p[p].time > 0 and seq_end > 0) or (ref.o_conns_p[p].time < 0 and seq_start > 0)) then
+ ref.outputs_m[t][p][i - 1]:fill(self.gconf.nn_act_default)
end
end
end
@@ -485,25 +487,28 @@ function TNN:backpropagate_dfs(ref, t, do_update)
--ok, do back_propagate
--print("debug ok, back-propagating(or updating)")
- if (bit.band(self.feeds_now.flagsPack_now[t], bit.bor(nerv.TNN.FC.SEQ_START, nerv.TNN.FC.SEQ_END)) > 0) then --flush cross-border errors
+ if (do_update == false) then
+ ref.layer:back_propagate(ref.err_inputs_m[t], ref.err_outputs_m[t], ref.inputs_m[t], ref.outputs_m[t], t)
+ else
+ --print(ref.err_inputs_m[t][1])
+ ref.layer:update(ref.err_inputs_m[t], ref.inputs_m[t], ref.outputs_m[t], t)
+ end
+
+ if (do_update == false and bit.band(self.feeds_now.flagsPack_now[t], bit.bor(nerv.TNN.FC.SEQ_START, nerv.TNN.FC.SEQ_END)) > 0) then --flush cross-border errors
for i = 1, self.batch_size do
local seq_start = bit.band(self.feeds_now.flags_now[t][i], nerv.TNN.FC.SEQ_START)
local seq_end = bit.band(self.feeds_now.flags_now[t][i], nerv.TNN.FC.SEQ_END)
if (seq_start > 0 or seq_end > 0) then
- for p, conn in pairs(ref.o_conns_p) do
- if ((ref.o_conns_p[p].time > 0 and seq_end > 0) or (ref.o_conns_p[p].time < 0 and seq_start > 0)) then --cross-border, set to zero
- ref.err_inputs_m[t][p][i - 1]:fill(0)
+ for p, conn in pairs(ref.i_conns_p) do
+ if ((ref.i_conns_p[p].time > 0 and seq_start > 0) or (ref.i_conns_p[p].time < 0 and seq_end > 0)) then --cross-border, set to zero
+ ref.err_outputs_m[t][p][i - 1]:fill(0)
end
end
end
end
end
- if (do_update == false) then
- ref.layer:back_propagate(ref.err_inputs_m[t], ref.err_outputs_m[t], ref.inputs_m[t], ref.outputs_m[t], t)
- else
- --print(ref.err_inputs_m[t][1])
- ref.layer:update(ref.err_inputs_m[t], ref.inputs_m[t], ref.outputs_m[t], t)
- end
+
+
for i = 1, #ref.dim_in do
if (ref.err_outputs_b[t][i] == true) then
nerv.error("this time's outputs_b should be false")