1 files changed, 0 insertions, 78 deletions
diff --git a/examples/test_dnn_layers.lua b/examples/test_dnn_layers.lua
deleted file mode 100644
index 64c0dec..0000000
--- a/examples/test_dnn_layers.lua
+++ /dev/null
@@ -1,78 +0,0 @@
-require 'layer.affine'
-require 'layer.sigmoid'
-require 'layer.softmax_ce'
-
-global_conf = {lrate = 0.8, wcost = 1e-6,
-                momentum = 0.9, cumat_type = nerv.CuMatrixFloat}
-
-pf = nerv.ChunkFile("affine.param", "r")
-ltp = pf:read_chunk("a", global_conf)
-bp = pf:read_chunk("b", global_conf)
-
--- print(bp.trans)
-
-af = nerv.AffineLayer("test", global_conf, {["ltp"] = ltp,
-                                            ["bp"] = bp,
-                                            dim_in = {429},
-                                            dim_out = {2048}})
-sg = nerv.SigmoidLayer("test2", global_conf, {dim_in = {2048},
-                                                dim_out = {2048}})
-sm = nerv.SoftmaxCELayer("test3", global_conf, {dim_in = {2048, 2048},
-                                                dim_out = {}})
-af:init()
-sg:init()
-sm:init()
-
-df = nerv.ChunkFile("input.param", "r")
-
-label = nerv.CuMatrixFloat(10, 2048)
-label:fill(0)
-for i = 0, 9 do
-    label[i][i] = 1.0
-end
-
-input1 = {df:read_chunk("input", global_conf).trans}
-output1 = {nerv.CuMatrixFloat(10, 2048)}
-input2 = output1
-output2 = {nerv.CuMatrixFloat(10, 2048)}
-input3 = {output2[1], label}
-output3 = {}
-err_input1 = {}
-err_output1 = {nerv.CuMatrixFloat(10, 2048)}
-err_input2 = err_output1
-err_output2 = {nerv.CuMatrixFloat(10, 2048)}
-err_input3 = err_output2
-err_output3 = {input1[1]:create()}
-
-for i = 0, 3 do
-    -- propagate
-    af:propagate(input1, output1)
-    sg:propagate(input2, output2)
-    sm:propagate(input3, output3)
-
-    -- back_propagate
-    sm:back_propagate(err_output1, err_input1, input3, output3)
-    sg:back_propagate(err_output2, err_input2, input2, output2)
-    af:back_propagate(err_output3, err_input3, input1, output1)
-
-    -- update
-    sm:update(err_input1, input3, output3)
-    sg:update(err_input2, input2, output2)
-    af:update(err_input3, input1, output1)
-
-
-    print("output1")
-    print(output1[1])
-    print("output2")
-    print(output2[1])
-    print("err_output1")
-    print(err_output1[1])
-    print("err_output2")
-    print(err_output2[1])
-    nerv.printf("cross entropy: %.8f\n", sm.total_ce)
-    nerv.printf("frames: %.8f\n", sm.total_frames)
-end
-print("linear")
-print(af.ltp.trans)
-print("linear2")
-print(af.bp.trans)