diff options
Diffstat (limited to 'fastnn')
| -rw-r--r-- | fastnn/fastnn_baseline.lua | 236 |
1 files changed, 0 insertions, 236 deletions
diff --git a/fastnn/fastnn_baseline.lua b/fastnn/fastnn_baseline.lua deleted file mode 100644 index 80b1d6b..0000000 --- a/fastnn/fastnn_baseline.lua +++ /dev/null @@ -1,236 +0,0 @@ -require 'htk_io' - -gconf = {lrate = 0.2, wcost = 1e-6, momentum = 0.9, - cumat_type = nerv.CuMatrixFloat, - mmat_type = nerv.MMatrixFloat, - frm_ext = 5, - batch_size = 256, - buffer_size = 81920, - tr_scp = "/sgfs/users/wd007/asr/baseline_chn_50h/finetune/finetune_baseline/train.scp", - cv_scp = "/sgfs/users/wd007/asr/baseline_chn_50h/finetune/finetune_baseline/train_cv.scp", - htk_conf = "/sgfs/users/wd007/asr/baseline_chn_50h/finetune/finetune_baseline/fbank_d_a_z.conf", - transf = {"/sgfs/users/wd007/src/nerv/tools/nerv.global.transf"}, - network = {"/sgfs/users/wd007/src/nerv/tools/nerv.svd0.55_3000h_iter1.init"}, - debug = false} - -function make_transf_node_repo(param_transf_repo) - return nerv.LayerRepo( - { - -- global transf - ["nerv.BiasLayer"] = - { - blayer1 = {{bias = "bias1"}, {dim_in = {1320}, dim_out = {1320}}}, - }, - ["nerv.WindowLayer"] = - { - wlayer1 = {{window = "window1"}, {dim_in = {1320}, dim_out = {1320}}}, - }, - - }, param_transf_repo, gconf) -end - -function make_network_node_repo(param_network_repo) - return nerv.LayerRepo( - { - -- biased linearity - ["nerv.AffineLayer"] = - { - affine0 = {{ltp = "affine0_ltp", bp = "affine0_bp"}, - {dim_in = {1320}, dim_out = {2048}}}, - affine1 = {{ltp = "affine1_ltp", bp = "affine1_bp"}, - {dim_in = {2048}, dim_out = {367}}}, - affine2 = {{ltp = "affine2_ltp", bp = "affine2_bp"}, - {dim_in = {367}, dim_out = {2048}}}, - affine3 = {{ltp = "affine3_ltp", bp = "affine3_bp"}, - {dim_in = {2048}, dim_out = {408}}}, - affine4 = {{ltp = "affine4_ltp", bp = "affine4_bp"}, - {dim_in = {408}, dim_out = {2048}}}, - affine5 = {{ltp = "affine5_ltp", bp = "affine5_bp"}, - {dim_in = {2048}, dim_out = {368}}}, - affine6 = {{ltp = "affine6_ltp", bp = "affine6_bp"}, - {dim_in = {368}, dim_out = {2048}}}, - affine7 = {{ltp = "affine7_ltp", bp = "affine7_bp"}, - {dim_in = {2048}, dim_out = {303}}}, - affine8 = {{ltp = "affine8_ltp", bp = "affine8_bp"}, - {dim_in = {303}, dim_out = {2048}}}, - affine9 = {{ltp = "affine9_ltp", bp = "affine9_bp"}, - {dim_in = {2048}, dim_out = {277}}}, - affine10 = {{ltp = "affine10_ltp", bp = "affine10_bp"}, - {dim_in = {277}, dim_out = {2048}}}, - affine11 = {{ltp = "affine11_ltp", bp = "affine11_bp"}, - {dim_in = {2048}, dim_out = {361}}}, - affine12 = {{ltp = "affine12_ltp", bp = "affine12_bp"}, - {dim_in = {361}, dim_out = {2048}}}, - affine13 = {{ltp = "affine13_ltp", bp = "affine13_bp"}, - {dim_in = {2048}, dim_out = {441}}}, - affine14 = {{ltp = "affine14_ltp", bp = "affine14_bp"}, - {dim_in = {441}, dim_out = {10092}}}, - }, - ["nerv.SigmoidLayer"] = - { - 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"] = - { - ce_crit = {{}, {dim_in = {10092, 1}, dim_out = {1}, compressed = true}} - } - - }, param_network_repo, gconf) -end - - -function make_transf_link_repo(layer_transf_node_repo, param_transf_repo) - return nerv.LayerRepo( - { - ["nerv.DAGLayer"] = - { - global_transf = {{}, { - dim_in = {1320}, dim_out = {1320}, - sub_layers = layer_transf_node_repo, - connections = - { - ["<input>[1]"] = "blayer1[1]", - ["blayer1[1]"] = "wlayer1[1]", - ["wlayer1[1]"] = "<output>[1]" - } - }}, - - } - }, param_transf_repo, gconf) -end - - -function make_network_link_repo(layer_network_node_repo, param_network_repo) - return nerv.LayerRepo( - { - ["nerv.DAGLayer"] = - { - main = {{}, { - dim_in = {1320, 1}, dim_out = {1}, - sub_layers = layer_network_node_repo, - connections = { - ["<input>[1]"] = "affine0[1]", - ["affine0[1]"] = "sigmoid0[1]", - ["sigmoid0[1]"] = "affine1[1]", - ["affine1[1]"] = "affine2[1]", - ["affine2[1]"] = "sigmoid1[1]", - ["sigmoid1[1]"] = "affine3[1]", - ["affine3[1]"] = "affine4[1]", - ["affine4[1]"] = "sigmoid2[1]", - ["sigmoid2[1]"] = "affine5[1]", - ["affine5[1]"] = "affine6[1]", - ["affine6[1]"] = "sigmoid3[1]", - ["sigmoid3[1]"] = "affine7[1]", - ["affine7[1]"] = "affine8[1]", - ["affine8[1]"] = "sigmoid4[1]", - ["sigmoid4[1]"] = "affine9[1]", - ["affine9[1]"] = "affine10[1]", - ["affine10[1]"] = "sigmoid5[1]", - ["sigmoid5[1]"] = "affine11[1]", - ["affine11[1]"] = "affine12[1]", - ["affine12[1]"] = "sigmoid6[1]", - ["sigmoid6[1]"] = "affine13[1]", - ["affine13[1]"] = "affine14[1]", - ["affine14[1]"] = "ce_crit[1]", - ["<input>[2]"] = "ce_crit[2]", - ["ce_crit[1]"] = "<output>[1]" - } - }} - } - }, param_network_repo, gconf) -end - -function get_network(layer_repo) - return layer_repo:get_layer("main") -end - - -function make_readers(scp_file, layer_repo, feat_repo_shareid, data_mutex_shareid) - return { - {reader = nerv.TNetReader(gconf, - { - id = "main_scp", - scp_file = scp_file, - conf_file = gconf.htk_conf, - frm_ext = gconf.frm_ext, - mlfs = { - phone_state = { - file = "/sgfs/users/wd007/asr/baseline_chn_50h/finetune/finetune_baseline/ref.mlf", - format = "map", - format_arg = "/sgfs/users/wd007/asr/baseline_chn_50h/finetune/finetune_baseline/dict", - dir = "*/", - ext = "lab" - } - }, - global_transf = layer_repo:get_layer("global_transf") - }, feat_repo_shareid, data_mutex_shareid), - data = {main_scp = 1320, phone_state = 1}} - } -end - - -function make_buffer(readers) - return nerv.SGDBuffer(gconf, - { - buffer_size = gconf.buffer_size, - randomize = gconf.randomize, - readers = readers - }) -end - -function get_feat_id() - return {main_scp = true} -end - -function get_input_order() - return {"main_scp", "phone_state"} -end - -function get_accuracy(sublayer_repo) - local ce_crit = sublayer_repo:get_layer("ce_crit") - return ce_crit.total_correct / ce_crit.total_frames * 100 -end - -function print_stat(sublayer_repo) - local ce_crit = sublayer_repo:get_layer("ce_crit") - nerv.info("*** training stat begin ***") - nerv.printf("cross entropy:\t\t%.8f\n", ce_crit.total_ce) - nerv.printf("correct:\t\t%d\n", ce_crit.total_correct) - nerv.printf("frames:\t\t\t%d\n", ce_crit.total_frames) - nerv.printf("err/frm:\t\t%.8f\n", ce_crit.total_ce / ce_crit.total_frames) - nerv.printf("accuracy:\t\t%.3f%%\n", get_accuracy(sublayer_repo)) - nerv.info("*** training stat end ***") -end - -function print_xent(xent) - local totalframes = xent:totalframes() - local loss = xent:loss() - local correct = xent:correct() - nerv.info_stderr("*** training statistics info begin ***") - nerv.info_stderr("total frames:\t\t%d", totalframes) - nerv.info_stderr("cross entropy:\t%.8f", loss/totalframes) - nerv.info_stderr("frame accuracy:\t%.3f%%", 100*correct/totalframes) - nerv.info_stderr("*** training statistics info end ***") -end - -function frame_acc(xent) - local correct = xent:correct() - local totalframes = xent:totalframes() - return string.format("%.3f", 100*correct/totalframes) -end - -function print_gconf() - nerv.info_stderr("%s \t:= %s", "network", gconf.network[1]) - nerv.info_stderr("%s \t:= %s", "transf", gconf.transf[1]) - nerv.info_stderr("%s \t:= %s", "batch_size", gconf.batch_size) - nerv.info_stderr("%s \t:= %s", "buffer_size", gconf.buffer_size) - nerv.info_stderr("%s \t:= %s", "lrate", gconf.lrate) - nerv.info_stderr("%s \t:= %s", "tr_scp", gconf.tr_scp) - nerv.info_stderr("%s \t:= %s", "cv_scp", gconf.cv_scp) -end |