3 files changed, 0 insertions, 104 deletions
diff --git a/nerv/layer/init.lua b/nerv/layer/init.lua
index 25dfebb..6861b0e 100644
--- a/nerv/layer/init.lua
+++ b/nerv/layer/init.lua
@@ -79,5 +79,3 @@ nerv.include('mse.lua')
 nerv.include('combiner.lua')
 nerv.include('affine_recurrent.lua')
 nerv.include('softmax.lua')
-nerv.include('mpe.lua')
-nerv.include('mmi.lua')
diff --git a/nerv/layer/mmi.lua b/nerv/layer/mmi.lua
deleted file mode 100644
index ecc7f48..0000000
--- a/nerv/layer/mmi.lua
+++ /dev/null
@@ -1,50 +0,0 @@
-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/nerv/layer/mpe.lua b/nerv/layer/mpe.lua
deleted file mode 100644
index ec8a8f3..0000000
--- a/nerv/layer/mpe.lua
+++ /dev/null
@@ -1,52 +0,0 @@
-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