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Diffstat (limited to 'examples/test_nn_lib.lua')
-rw-r--r-- | examples/test_nn_lib.lua | 63 |
1 files changed, 63 insertions, 0 deletions
diff --git a/examples/test_nn_lib.lua b/examples/test_nn_lib.lua new file mode 100644 index 0000000..fd7167a --- /dev/null +++ b/examples/test_nn_lib.lua @@ -0,0 +1,63 @@ +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"}) +sublayer_repo = nerv.LayerRepo( + { + ["nerv.AffineLayer"] = + { + affine1 = {{ltp = "a", bp = "b"}, {dim_in = {429}, dim_out = {2048}}} + }, + ["nerv.SigmoidLayer"] = + { + sigmoid1 = {{}, {dim_in = {2048}, dim_out = {2048}}} + }, + ["nerv.SoftmaxCELayer"] = + { + softmax_ce1 = {{}, {dim_in = {2048, 2048}, dim_out = {}}} + } + }, param_repo, gconf) + +layer_repo = nerv.LayerRepo( + { + ["nerv.DAGLayer"] = + { + main = {{}, { + dim_in = {429, 2048}, dim_out = {}, + sub_layers = sublayer_repo, + connections = { + ["<input>[1]"] = "affine1[1]", + ["affine1[1]"] = "sigmoid1[1]", + ["sigmoid1[1]"] = "softmax_ce1[1]", + ["<input>[2]"] = "softmax_ce1[2]" + } + }} + } + }, param_repo, gconf) + +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 + +input = {df:read_chunk("input", gconf).trans, label} +output = {} +err_input = {} +err_output = {input[1]:create()} +sm = sublayer_repo:get_layer("softmax_ce1") +main = layer_repo:get_layer("main") +main:init() +for i = 0, 3 do + main:propagate(input, output) + main:back_propagate(err_output, err_input, input, output) + main:update(err_input, input, output) + nerv.utils.printf("cross entropy: %.8f\n", sm.total_ce) + nerv.utils.printf("frames: %.8f\n", sm.total_frames) +end |