Just come back, let's merge the new master

Merge branch 'master' into txh18/rnnlm

1 files changed, 25 insertions, 0 deletions

diff --git a/embedding_example/setup_nerv.lua b/embedding_example/setup_nerv.lua
new file mode 100644
index 0000000..d80c306
--- /dev/null
+++ b/embedding_example/setup_nerv.lua
@@ -0,0 +1,25 @@
+local k,l,_=pcall(require,"luarocks.loader") _=k and l.add_context("nerv","scm-1")
+require 'nerv'
+local arg = {...}
+dofile(arg[1])
+local param_repo = nerv.ParamRepo()
+param_repo:import(gconf.initialized_param, nil, gconf)
+local layer_repo = make_layer_repo(param_repo)
+local network = get_decode_network(layer_repo)
+local global_transf = get_global_transf(layer_repo)
+local batch_size = 1
+network:init(batch_size)
+
+function propagator(input, output)
+    local transformed = nerv.speech_utils.global_transf(
+                            gconf.cumat_type.new_from_host(input),
+                            global_transf, 0, 0, gconf) -- preprocessing
+    local gpu_input = transformed
+    local gpu_output = nerv.CuMatrixFloat(output:nrow(), output:ncol())
+    network:propagate({gpu_input}, {gpu_output})
+    gpu_output:copy_toh(output)
+    -- collect garbage in-time to save GPU memory
+    collectgarbage("collect")
+end
+
+return network.dim_in[1], network.dim_out[1], propagator