diff options
| -rw-r--r-- | examples/test_nn_lib.lua | 60 | ||||
| -rw-r--r-- | layer/softmax_ce.lua | 4 | ||||
| -rw-r--r-- | nn/layer_dag.lua | 4 |
3 files changed, 54 insertions, 14 deletions
diff --git a/examples/test_nn_lib.lua b/examples/test_nn_lib.lua index fd7167a..ec338fe 100644 --- a/examples/test_nn_lib.lua +++ b/examples/test_nn_lib.lua @@ -1,25 +1,46 @@ -require 'layer.affine' -require 'layer.sigmoid' -require 'layer.softmax_ce' +-- require 'layer.affine' +-- require 'layer.sigmoid' +-- require 'layer.softmax_ce' gconf = {lrate = 0.8, wcost = 1e-6, momentum = 0.9, mat_type = nerv.CuMatrixFloat, batch_size = 10} -param_repo = nerv.ParamRepo({"affine.param"}) +param_repo = nerv.ParamRepo({"converted.nerv"}) sublayer_repo = nerv.LayerRepo( { ["nerv.AffineLayer"] = { - affine1 = {{ltp = "a", bp = "b"}, {dim_in = {429}, dim_out = {2048}}} + affine0 = {{ltp = "affine0_ltp", bp = "affine0_bp"}, + {dim_in = {429}, dim_out = {2048}}}, + affine1 = {{ltp = "affine1_ltp", bp = "affine1_bp"}, + {dim_in = {2048}, dim_out = {2048}}}, + affine2 = {{ltp = "affine2_ltp", bp = "affine2_bp"}, + {dim_in = {2048}, dim_out = {2048}}}, + affine3 = {{ltp = "affine3_ltp", bp = "affine3_bp"}, + {dim_in = {2048}, dim_out = {2048}}}, + affine4 = {{ltp = "affine4_ltp", bp = "affine4_bp"}, + {dim_in = {2048}, dim_out = {2048}}}, + affine5 = {{ltp = "affine5_ltp", bp = "affine5_bp"}, + {dim_in = {2048}, dim_out = {2048}}}, + affine6 = {{ltp = "affine6_ltp", bp = "affine6_bp"}, + {dim_in = {2048}, dim_out = {2048}}}, + affine7 = {{ltp = "affine7_ltp", bp = "affine7_bp"}, + {dim_in = {2048}, dim_out = {3001}}} }, ["nerv.SigmoidLayer"] = { - sigmoid1 = {{}, {dim_in = {2048}, dim_out = {2048}}} + sigmoid0 = {{}, {dim_in = {2048}, dim_out = {2048}}}, + sigmoid1 = {{}, {dim_in = {2048}, dim_out = {2048}}}, + sigmoid2 = {{}, {dim_in = {2048}, dim_out = {2048}}}, + sigmoid3 = {{}, {dim_in = {2048}, dim_out = {2048}}}, + sigmoid4 = {{}, {dim_in = {2048}, dim_out = {2048}}}, + sigmoid5 = {{}, {dim_in = {2048}, dim_out = {2048}}}, + sigmoid6 = {{}, {dim_in = {2048}, dim_out = {2048}}} }, ["nerv.SoftmaxCELayer"] = { - softmax_ce1 = {{}, {dim_in = {2048, 2048}, dim_out = {}}} + softmax_ce0 = {{}, {dim_in = {3001, 3001}, dim_out = {}}} } }, param_repo, gconf) @@ -28,20 +49,33 @@ layer_repo = nerv.LayerRepo( ["nerv.DAGLayer"] = { main = {{}, { - dim_in = {429, 2048}, dim_out = {}, + dim_in = {429, 3001}, dim_out = {}, sub_layers = sublayer_repo, connections = { - ["<input>[1]"] = "affine1[1]", + ["<input>[1]"] = "affine0[1]", + ["affine0[1]"] = "sigmoid0[1]", + ["sigmoid0[1]"] = "affine1[1]", ["affine1[1]"] = "sigmoid1[1]", - ["sigmoid1[1]"] = "softmax_ce1[1]", - ["<input>[2]"] = "softmax_ce1[2]" + ["sigmoid1[1]"] = "affine2[1]", + ["affine2[1]"] = "sigmoid2[1]", + ["sigmoid2[1]"] = "affine3[1]", + ["affine3[1]"] = "sigmoid3[1]", + ["sigmoid3[1]"] = "affine4[1]", + ["affine4[1]"] = "sigmoid4[1]", + ["sigmoid4[1]"] = "affine5[1]", + ["affine5[1]"] = "sigmoid5[1]", + ["sigmoid5[1]"] = "affine6[1]", + ["affine6[1]"] = "sigmoid6[1]", + ["sigmoid6[1]"] = "affine7[1]", + ["affine7[1]"] = "softmax_ce0[1]", + ["<input>[2]"] = "softmax_ce0[2]" } }} } }, param_repo, gconf) df = nerv.ChunkFile("input.param", "r") -label = nerv.CuMatrixFloat(10, 2048) +label = nerv.CuMatrixFloat(10, 3001) label:fill(0) for i = 0, 9 do label[i][i] = 1.0 @@ -51,7 +85,7 @@ input = {df:read_chunk("input", gconf).trans, label} output = {} err_input = {} err_output = {input[1]:create()} -sm = sublayer_repo:get_layer("softmax_ce1") +sm = sublayer_repo:get_layer("softmax_ce0") main = layer_repo:get_layer("main") main:init() for i = 0, 3 do diff --git a/layer/softmax_ce.lua b/layer/softmax_ce.lua index 3dfebc5..09eb3a9 100644 --- a/layer/softmax_ce.lua +++ b/layer/softmax_ce.lua @@ -27,6 +27,8 @@ function SoftmaxCELayer:propagate(input, output) local ce = soutput:create() ce:log_elem(soutput) ce:mul_elem(ce, input[2]) +-- print(input[1][0]) +-- print(soutput[1][0]) -- add total ce self.total_ce = self.total_ce - ce:rowsum():colsum()[0] self.total_frames = self.total_frames + soutput:nrow() @@ -34,5 +36,5 @@ end function SoftmaxCELayer:back_propagate(next_bp_err, bp_err, input, output) -- softmax output - label - next_bp_err[1]:add(self.soutput, input[1], 1.0, -1.0) + next_bp_err[1]:add(self.soutput, input[2], 1.0, -1.0) end diff --git a/nn/layer_dag.lua b/nn/layer_dag.lua index 8ea28a0..1ab18fa 100644 --- a/nn/layer_dag.lua +++ b/nn/layer_dag.lua @@ -219,6 +219,10 @@ function nerv.DAGLayer:back_propagate(next_bp_err, bp_err, input, output) self:set_outputs(output) for i = #self.queue, 1, -1 do local ref = self.queue[i] + -- print(ref.layer.id) ref.layer:back_propagate(ref.err_outputs, ref.err_inputs, ref.inputs, ref.outputs) + -- if #ref.err_outputs > 0 then + -- print(ref.err_outputs[1]) + -- end end end |