From 10cce5f6a5c9e2f8e00d5a2a4d87c9cb7c26bf4c Mon Sep 17 00:00:00 2001 From: Determinant Date: Fri, 14 Aug 2015 13:54:51 +0800 Subject: add example script for converting to kaldi nnet --- kaldi_io/tools/nerv_to_kaldi.lua | 66 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 66 insertions(+) create mode 100644 kaldi_io/tools/nerv_to_kaldi.lua (limited to 'kaldi_io/tools') diff --git a/kaldi_io/tools/nerv_to_kaldi.lua b/kaldi_io/tools/nerv_to_kaldi.lua new file mode 100644 index 0000000..804f09b --- /dev/null +++ b/kaldi_io/tools/nerv_to_kaldi.lua @@ -0,0 +1,66 @@ +-- usage: nerv config_file nerv_param_input tnet_output + +dofile(arg[1]) +param_repo = nerv.ParamRepo() +param_repo:import({arg[2], gconf.initialized_param[2]}, nil, gconf) +layer_repo = make_layer_repo(param_repo) +f = assert(io.open(arg[3], "w")) + +function print_tnet_matrix(cumat) + local strs = {} + collectgarbage() + if cumat:nrow() == 1 then + local mat = nerv.MMatrixFloat(1, cumat:ncol()) + cumat:copy_toh(mat) + table.insert(strs, "[ ") + for j = 0, mat:ncol() - 1 do + table.insert(strs, string.format("%.8f ", mat[0][j])) + end + table.insert(strs, " ]\n") + f:write(table.concat(strs)) + else + cumat = cumat:trans() + local mat = nerv.MMatrixFloat(cumat:nrow(), cumat:ncol()) + cumat:copy_toh(mat) + table.insert(strs, string.format(" [\n", mat:nrow(), mat:ncol())) + for i = 0, mat:nrow() - 1 do + local row = mat[i] + for j = 0, mat:ncol() - 1 do + table.insert(strs, string.format("%.8f ", row[j])) + end + if i == mat:nrow() - 1 then + table.insert(strs, " ]\n") + else + table.insert(strs, "\n") + end + f:write(table.concat(strs)) + strs = {} + end + end +end +local lnames = {"affine0", "sigmoid0", + "affine1", "sigmoid1", + "affine2", "sigmoid2", + "affine3", "sigmoid3", + "affine4", "sigmoid4", + "affine5", "sigmoid5", + "affine6", "ce_crit"} +f:write("\n") +for i, name in ipairs(lnames) do + local layer = layer_repo:get_layer(name) + local layer_type = layer.__typename + if layer_type == "nerv.AffineLayer" then + f:write(string.format(" %d %d\n 1 1 0", + layer.dim_out[1], layer.dim_in[1])) + print_tnet_matrix(layer.ltp.trans) + print_tnet_matrix(layer.bp.trans) + elseif layer_type == "nerv.SigmoidLayer" then + f:write(string.format(" %d %d\n", layer.dim_out[1], layer.dim_in[1])) + elseif layer_type == "nerv.SoftmaxCELayer" then + f:write(string.format(" %d %d\n", layer.dim_in[1], layer.dim_in[1])) + else + nerv.error("unknown layer type %s", layer_type) + end +end +f:write("\n") +f:close() -- cgit v1.2.3-70-g09d2