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author | cloudygoose <[email protected]> | 2015-06-03 10:29:41 +0800 |
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committer | cloudygoose <[email protected]> | 2015-06-03 10:29:41 +0800 |
commit | bf01fd6cea42def51becb6ea866d4fd335e45842 (patch) | |
tree | 09d12e50e3a6156c7e0cd7412b22fa4b61189495 /examples/test_dnn_layers.lua | |
parent | 6984519cbb659aac0b0b323de93d5a90aa2049b7 (diff) | |
parent | bb56a806e0636a0b20117b1644701d63e2bfaefb (diff) |
...
Merge remote-tracking branch 'upstream/master'
Diffstat (limited to 'examples/test_dnn_layers.lua')
-rw-r--r-- | examples/test_dnn_layers.lua | 43 |
1 files changed, 23 insertions, 20 deletions
diff --git a/examples/test_dnn_layers.lua b/examples/test_dnn_layers.lua index 866e685..6e4d98d 100644 --- a/examples/test_dnn_layers.lua +++ b/examples/test_dnn_layers.lua @@ -11,10 +11,14 @@ bp = pf:read_chunk("b", global_conf) -- print(bp.trans) -af = nerv.AffineLayer("test", global_conf, ltp, bp) -sg = nerv.SigmoidLayer("test2", global_conf) -sm = nerv.SoftmaxCELayer("test3", global_conf) - +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() @@ -27,18 +31,18 @@ for i = 0, 9 do label[i][i] = 1.0 end -input1 = {[0] = df:read_chunk("input", global_conf).trans} -output1 = {[0] = nerv.CuMatrixFloat(10, 2048)} +input1 = {df:read_chunk("input", global_conf).trans} +output1 = {nerv.CuMatrixFloat(10, 2048)} input2 = output1 -output2 = {[0] = nerv.CuMatrixFloat(10, 2048)} -input3 = {[0] = output2[0], [1] = label} +output2 = {nerv.CuMatrixFloat(10, 2048)} +input3 = {output2[1], label} output3 = nil err_input1 = nil -err_output1 = {[0] = nerv.CuMatrixFloat(10, 2048)} +err_output1 = {nerv.CuMatrixFloat(10, 2048)} err_input2 = err_output1 -err_output2 = {[0] = nerv.CuMatrixFloat(10, 2048)} +err_output2 = {nerv.CuMatrixFloat(10, 2048)} err_input3 = err_output2 -err_output3 = {[0] = input1[0]:create()} +err_output3 = {input1[1]:create()} for i = 0, 3 do -- propagate @@ -46,26 +50,25 @@ for i = 0, 3 do sg:propagate(input2, output2) sm:propagate(input3, output3) - -- back_propagate sm:back_propagate(err_output1, err_input1, input3, output3) - sm:update(err_input1, input3, output3) - sg:back_propagate(err_output2, err_input2, input2, output2) - sg:update(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[0]) + print(output1[1]) print("output2") - print(output2[0]) + print(output2[1]) print("err_output1") - print(err_output1[0]) + print(err_output1[1]) print("err_output2") - print(err_output2[0]) + print(err_output2[1]) nerv.utils.printf("cross entropy: %.8f\n", sm.total_ce) nerv.utils.printf("frames: %.8f\n", sm.total_frames) end |