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-rw-r--r--kaldi_seq/layer/mmi.lua50
-rw-r--r--kaldi_seq/layer/mpe.lua52
2 files changed, 102 insertions, 0 deletions
diff --git a/kaldi_seq/layer/mmi.lua b/kaldi_seq/layer/mmi.lua
new file mode 100644
index 0000000..ecc7f48
--- /dev/null
+++ b/kaldi_seq/layer/mmi.lua
@@ -0,0 +1,50 @@
+require 'libkaldiseq'
+local MMILayer = nerv.class("nerv.MMILayer", "nerv.Layer")
+
+function MMILayer:__init(id, global_conf, layer_conf)
+ self.id = id
+ self.gconf = global_conf
+ self.dim_in = layer_conf.dim_in
+ self.dim_out = layer_conf.dim_out
+ self.arg = layer_conf.cmd.arg
+ self.mdl = layer_conf.cmd.mdl
+ self.lat = layer_conf.cmd.lat
+ self.ali = layer_conf.cmd.ali
+ self:check_dim_len(2, -1) -- two inputs: nn output and utt key
+end
+
+function MMILayer:init(batch_size)
+ self.total_frames = 0
+ self.kaldi_mmi = nerv.KaldiMMI(self.arg, self.mdl, self.lat, self.ali)
+ if self.kaldi_mmi == nil then
+ nerv.error("kaldi arguments is expected: %s %s %s %s", self.arg,
+ self.mdl, self.lat, self.ali)
+ end
+end
+
+function MMILayer:batch_resize(batch_size)
+ -- do nothing
+end
+
+function MMILayer:update(bp_err, input, output)
+ -- no params, therefore do nothing
+end
+
+function MMILayer:propagate(input, output)
+ self.valid = false
+ self.valid = self.kaldi_mmi:check(input[1], input[2])
+ return self.valid
+end
+
+function MMILayer:back_propagate(bp_err, next_bp_err, input, output)
+ if self.valid ~= true then
+ nerv.error("kaldi sequence training back_propagate fail")
+ end
+ local mmat = input[1]:new_to_host()
+ next_bp_err[1]:copy_fromh(self.kaldi_mmi:calc_diff(mmat, input[2]))
+ self.total_frames = self.total_frames + self.kaldi_mmi:get_num_frames()
+end
+
+function MMILayer:get_params()
+ return nerv.ParamRepo({})
+end
diff --git a/kaldi_seq/layer/mpe.lua b/kaldi_seq/layer/mpe.lua
new file mode 100644
index 0000000..ec8a8f3
--- /dev/null
+++ b/kaldi_seq/layer/mpe.lua
@@ -0,0 +1,52 @@
+require 'libkaldiseq'
+local MPELayer = nerv.class("nerv.MPELayer", "nerv.Layer")
+
+function MPELayer:__init(id, global_conf, layer_conf)
+ self.id = id
+ self.gconf = global_conf
+ self.dim_in = layer_conf.dim_in
+ self.dim_out = layer_conf.dim_out
+ self.arg = layer_conf.cmd.arg
+ self.mdl = layer_conf.cmd.mdl
+ self.lat = layer_conf.cmd.lat
+ self.ali = layer_conf.cmd.ali
+ self:check_dim_len(2, -1) -- two inputs: nn output and utt key
+end
+
+function MPELayer:init(batch_size)
+ self.total_correct = 0
+ self.total_frames = 0
+ self.kaldi_mpe = nerv.KaldiMPE(self.arg, self.mdl, self.lat, self.ali)
+ if self.kaldi_mpe == nil then
+ nerv.error("kaldi arguments is expected: %s %s %s %s", self.arg,
+ self.mdl, self.lat, self.ali)
+ end
+end
+
+function MPELayer:batch_resize(batch_size)
+ -- do nothing
+end
+
+function MPELayer:update(bp_err, input, output)
+ -- no params, therefore do nothing
+end
+
+function MPELayer:propagate(input, output)
+ self.valid = false
+ self.valid = self.kaldi_mpe:check(input[1], input[2])
+ return self.valid
+end
+
+function MPELayer:back_propagate(bp_err, next_bp_err, input, output)
+ if self.valid ~= true then
+ nerv.error("kaldi sequence training back_propagate fail")
+ end
+ local mmat = input[1]:new_to_host()
+ next_bp_err[1]:copy_fromh(self.kaldi_mpe:calc_diff(mmat, input[2]))
+ self.total_frames = self.total_frames + self.kaldi_mpe:get_num_frames()
+ self.total_correct = self.total_correct + self.kaldi_mpe:get_utt_frame_acc()
+end
+
+function MPELayer:get_params()
+ return nerv.ParamRepo({})
+end