1 files changed, 0 insertions, 114 deletions
diff --git a/nerv/tnn/layersT/gru_t.lua b/nerv/tnn/layersT/gru_t.lua
deleted file mode 100644
index 8f15cc8..0000000
--- a/nerv/tnn/layersT/gru_t.lua
+++ /dev/null
@@ -1,114 +0,0 @@
-local GRULayerT = nerv.class('nerv.GRULayerT', 'nerv.LayerT')
-
-function GRULayerT:__init(id, global_conf, layer_conf)
-    --input1:x input2:h input3:c(h^~)
-    self.id = id
-    self.dim_in = layer_conf.dim_in
-    self.dim_out = layer_conf.dim_out
-    self.gconf = global_conf
-
-    if self.dim_in[2] ~= self.dim_out[1] then
-        nerv.error("dim_in[2](%d) mismatch with dim_out[1](%d)", self.dim_in[2], self.dim_out[1])
-    end
-
-    --prepare a DAGLayerT to hold the lstm structure
-    local pr = layer_conf.pr
-    if pr == nil then
-        pr = nerv.ParamRepo()
-    end
-    
-    local function ap(str)
-        return self.id .. '.' .. str
-    end
-
-    local layers = {
-        ["nerv.CombinerLayer"] = {
-            [ap("inputXDup")] = {{}, {["dim_in"] = {self.dim_in[1]}, 
-                ["dim_out"] = {self.dim_in[1], self.dim_in[1], self.dim_in[1]}, ["lambda"] = {1}}},
-            [ap("inputHDup")] = {{}, {["dim_in"] = {self.dim_in[2]}, 
-                ["dim_out"] = {self.dim_in[2], self.dim_in[2], self.dim_in[2], self.dim_in[2], self.dim_in[2]}, ["lambda"] = {1}}},
-            [ap("updateGDup")] = {{}, {["dim_in"] = {self.dim_in[2]},
-                ["dim_out"] = {self.dim_in[2], self.dim_in[2]}, ["lambda"] = {1}}},
-            [ap("updateMergeL")] = {{}, {["dim_in"] = {self.dim_in[2], self.dim_in[2], self.dim_in[2]}, ["dim_out"] = {self.dim_out[1]},
-                ["lambda"] = {1, -1, 1}}},
-        },
-        ["nerv.AffineLayer"] = {
-            [ap("mainAffineL")] = {{}, {["dim_in"] = {self.dim_in[1], self.dim_in[2]}, ["dim_out"] = {self.dim_out[1]}, ["pr"] = pr}},
-        },
-        ["nerv.TanhLayer"] = {
-            [ap("mainTanhL")] = {{}, {["dim_in"] = {self.dim_out[1]}, ["dim_out"] = {self.dim_out[1]}}},
-        },
-        ["nerv.GateFLayer"] = {
-            [ap("resetGateL")] = {{}, {["dim_in"] = {self.dim_in[1], self.dim_in[2]}, 
-                ["dim_out"] = {self.dim_in[2]}, ["pr"] = pr}},
-            [ap("updateGateL")] = {{}, {["dim_in"] = {self.dim_in[1], self.dim_in[2]}, 
-                ["dim_out"] = {self.dim_in[2]}, ["pr"] = pr}},
-        },
-        ["nerv.ElemMulLayer"] = {
-            [ap("resetGMulL")] = {{}, {["dim_in"] = {self.dim_in[2], self.dim_in[2]}, ["dim_out"] = {self.dim_in[2]}}},
-            [ap("updateGMulCL")] = {{}, {["dim_in"] = {self.dim_in[2], self.dim_in[2]}, ["dim_out"] = {self.dim_in[2]}}},
-            [ap("updateGMulHL")] = {{}, {["dim_in"] = {self.dim_in[2], self.dim_in[2]}, ["dim_out"] = {self.dim_in[2]}}},
-        },
-    }
-    
-    local layerRepo = nerv.LayerRepo(layers, pr, global_conf)
-
-    local connections_t = {
-        ["<input>[1]"] = ap("inputXDup[1]"), 
-        ["<input>[2]"] = ap("inputHDup[1]"),
-
-        [ap("inputXDup[1]")] = ap("resetGateL[1]"),
-        [ap("inputHDup[1]")] = ap("resetGateL[2]"),
-        [ap("inputXDup[2]")] = ap("updateGateL[1]"),
-        [ap("inputHDup[2]")] = ap("updateGateL[2]"),
-        [ap("updateGateL[1]")] = ap("updateGDup[1]"),
-
-        [ap("resetGateL[1]")] = ap("resetGMulL[1]"),
-        [ap("inputHDup[3]")] = ap("resetGMulL[2]"),
-
-        [ap("inputXDup[3]")] = ap("mainAffineL[1]"),
-        [ap("resetGMulL[1]")] = ap("mainAffineL[2]"),
-        [ap("mainAffineL[1]")] = ap("mainTanhL[1]"),
-
-        [ap("updateGDup[1]")] = ap("updateGMulHL[1]"),
-        [ap("inputHDup[4]")] = ap("updateGMulHL[2]"),
-        [ap("updateGDup[2]")] = ap("updateGMulCL[1]"),
-        [ap("mainTanhL[1]")] = ap("updateGMulCL[2]"),
- 
-        [ap("inputHDup[5]")] = ap("updateMergeL[1]"),
-        [ap("updateGMulHL[1]")] = ap("updateMergeL[2]"),
-        [ap("updateGMulCL[1]")] = ap("updateMergeL[3]"),
-
-        [ap("updateMergeL[1]")] = "<output>[1]",
-    }
-
-    self.dagL = nerv.DAGLayerT(self.id, global_conf, 
-            {["dim_in"] = self.dim_in, ["dim_out"] = self.dim_out, ["sub_layers"] = layerRepo, 
-            ["connections"] = connections_t})
-    
-    self:check_dim_len(2, 1) -- x, h and h
-end
-
-function GRULayerT:init(batch_size, chunk_size)
-    self.dagL:init(batch_size, chunk_size)
-end
-
-function GRULayerT:batch_resize(batch_size, chunk_size)
-    self.dagL:batch_resize(batch_size, chunk_size)
-end
-
-function GRULayerT:update(bp_err, input, output, t)
-    self.dagL:update(bp_err, input, output, t)
-end
-
-function GRULayerT:propagate(input, output, t)
-    self.dagL:propagate(input, output, t)
-end
-
-function GRULayerT:back_propagate(bp_err, next_bp_err, input, output, t)
-    self.dagL:back_propagate(bp_err, next_bp_err, input, output, t)
-end
-
-function GRULayerT:get_params()
-    return self.dagL:get_params()
-end