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-rw-r--r--fastnn/fastnn_baseline.lua236
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