move sequence related layers to kaldi_seq

1 files changed, 50 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