summaryrefslogtreecommitdiff
path: root/examples/tnet_preprocessing_example2.lua
diff options
context:
space:
mode:
Diffstat (limited to 'examples/tnet_preprocessing_example2.lua')
-rw-r--r--examples/tnet_preprocessing_example2.lua68
1 files changed, 0 insertions, 68 deletions
diff --git a/examples/tnet_preprocessing_example2.lua b/examples/tnet_preprocessing_example2.lua
deleted file mode 100644
index 1215b23..0000000
--- a/examples/tnet_preprocessing_example2.lua
+++ /dev/null
@@ -1,68 +0,0 @@
-require 'speech.init'
-gconf = {cumat_type = nerv.CuMatrixFloat,
- batch_size = 158}
-param_repo = nerv.ParamRepo({"global_transf.nerv"})
-
-sublayer_repo = nerv.LayerRepo(
- {
- ["nerv.BiasLayer"] =
- {
- blayer1 = {{bias = "bias1"}, {dim_in = {429}, dim_out = {429}}},
- blayer2 = {{bias = "bias2"}, {dim_in = {429}, dim_out = {429}}}
- },
- ["nerv.WindowLayer"] =
- {
- wlayer1 = {{window = "window1"}, {dim_in = {429}, dim_out = {429}}},
- wlayer2 = {{window = "window2"}, {dim_in = {429}, dim_out = {429}}}
- }
- }, param_repo, gconf)
-
-layer_repo = nerv.LayerRepo(
- {
- ["nerv.DAGLayer"] =
- {
- main = {{}, {
- dim_in = {429}, dim_out = {429},
- sub_layers = sublayer_repo,
- connections = {
- ["<input>[1]"] = "blayer1[1]",
- ["blayer1[1]"] = "wlayer1[1]",
- ["wlayer1[1]"] = "blayer2[1]",
- ["blayer2[1]"] = "wlayer2[1]",
- ["wlayer2[1]"] = "<output>[1]"
- }
- }}
- }
- }, param_repo, gconf)
-
-reader = nerv.TNetReader({},
- {
- id = "main_scp",
- scp_file = "/slfs1/users/mfy43/swb_ivec/train_bp.scp",
- conf_file = "/slfs1/users/mfy43/swb_ivec/plp_0_d_a.conf",
- frm_ext = 5,
- mlfs = {
- ref = {
- file = "/slfs1/users/mfy43/swb_ivec/ref.mlf",
- format = "map",
- format_arg = "/slfs1/users/mfy43/swb_ivec/dict",
- dir = "*/",
- ext = "lab"
- }
- },
- global_transf = layer_repo:get_layer("main")
- })
-
-utter = reader:get_data()
--- print(utter.main_scp)
-print(utter.ref)
--- cf2 = nerv.ChunkFile("feat_256", "r")
--- input = cf2:read_chunk("input", gconf)
-
--- for i = 0, 157 - 10 do
--- row_diff = input.trans[i] - utter.main_scp[i]
--- for j = 0, row_diff:ncol() - 1 do
--- nerv.printf("%.8f ", row_diff[j])
--- end
--- nerv.printf("\n")
--- end