diff options
Diffstat (limited to 'nerv/examples')
| -rw-r--r-- | nerv/examples/asr_trainer.lua | 22 | ||||
| -rw-r--r-- | nerv/examples/timit_baseline2.lua | 60 |
2 files changed, 48 insertions, 34 deletions
diff --git a/nerv/examples/asr_trainer.lua b/nerv/examples/asr_trainer.lua index 5bf28bd..6bdf57c 100644 --- a/nerv/examples/asr_trainer.lua +++ b/nerv/examples/asr_trainer.lua @@ -20,6 +20,12 @@ local function build_trainer(ifname) local network = get_network(layer_repo) local global_transf = get_global_transf(layer_repo) local input_order = get_input_order() + + network = nerv.Network("nt", gconf, {network = network}) + network:init(gconf.batch_size, 1) + global_transf = nerv.Network("gt", gconf, {network = global_transf}) + global_transf:init(gconf.batch_size, 1) + local iterative_trainer = function (prefix, scp_file, bp, rebind_param_repo) -- rebind the params if necessary if rebind_param_repo then @@ -32,10 +38,11 @@ local function build_trainer(ifname) -- build buffer local buffer = make_buffer(make_readers(scp_file, layer_repo)) -- initialize the network - network:init(gconf.batch_size) gconf.cnt = 0 err_input = {mat_type(gconf.batch_size, 1)} err_input[1]:fill(1) + network:epoch_init() + global_transf:epoch_init() for data in buffer.get_data, buffer do -- prine stat periodically gconf.cnt = gconf.cnt + 1 @@ -69,10 +76,17 @@ local function build_trainer(ifname) for i = 1, #input do table.insert(err_output, input[i]:create()) end - network:propagate(input, output) + network:mini_batch_init({seq_length = table.vector(gconf.batch_size, 1), + new_seq = {}, + do_train = bp, + input = {input}, + output = {output}, + err_input = {err_input}, + err_output = {err_output}}) + network:propagate() if bp then - network:back_propagate(err_input, err_output, input, output) - network:update(err_input, input, output) + network:back_propagate() + network:update() end -- collect garbage in-time to save GPU memory collectgarbage("collect") diff --git a/nerv/examples/timit_baseline2.lua b/nerv/examples/timit_baseline2.lua index 2d144b5..d783c3d 100644 --- a/nerv/examples/timit_baseline2.lua +++ b/nerv/examples/timit_baseline2.lua @@ -61,35 +61,35 @@ function make_layer_repo(param_repo) layer_repo:add_layers( { - ["nerv.DAGLayer"] = + ["nerv.GraphLayer"] = { global_transf = { dim_in = {440}, dim_out = {440}, - sub_layers = layer_repo, + layer_repo = layer_repo, connections = { - ["<input>[1]"] = "blayer1[1]", - ["blayer1[1]"] = "wlayer1[1]", - ["wlayer1[1]"] = "<output>[1]" + {"<input>[1]", "blayer1[1]", 0}, + {"blayer1[1]", "wlayer1[1]", 0}, + {"wlayer1[1]", "<output>[1]", 0} } }, main = { dim_in = {440}, dim_out = {1959}, - sub_layers = layer_repo, + layer_repo = layer_repo, connections = { - ["<input>[1]"] = "affine0[1]", - ["affine0[1]"] = "sigmoid0[1]", - ["sigmoid0[1]"] = "affine1[1]", - ["affine1[1]"] = "sigmoid1[1]", - ["sigmoid1[1]"] = "affine2[1]", - ["affine2[1]"] = "sigmoid2[1]", - ["sigmoid2[1]"] = "affine3[1]", - ["affine3[1]"] = "sigmoid3[1]", - ["sigmoid3[1]"] = "affine4[1]", - ["affine4[1]"] = "sigmoid4[1]", - ["sigmoid4[1]"] = "affine5[1]", - ["affine5[1]"] = "sigmoid5[1]", - ["sigmoid5[1]"] = "affine6[1]", - ["affine6[1]"] = "<output>[1]" + {"<input>[1]", "affine0[1]", 0}, + {"affine0[1]", "sigmoid0[1]", 0}, + {"sigmoid0[1]", "affine1[1]", 0}, + {"affine1[1]", "sigmoid1[1]", 0}, + {"sigmoid1[1]", "affine2[1]", 0}, + {"affine2[1]", "sigmoid2[1]", 0}, + {"sigmoid2[1]", "affine3[1]", 0}, + {"affine3[1]", "sigmoid3[1]", 0}, + {"sigmoid3[1]", "affine4[1]", 0}, + {"affine4[1]", "sigmoid4[1]", 0}, + {"sigmoid4[1]", "affine5[1]", 0}, + {"affine5[1]", "sigmoid5[1]", 0}, + {"sigmoid5[1]", "affine6[1]", 0}, + {"affine6[1]", "<output>[1]", 0} } } } @@ -97,25 +97,25 @@ function make_layer_repo(param_repo) layer_repo:add_layers( { - ["nerv.DAGLayer"] = + ["nerv.GraphLayer"] = { ce_output = { dim_in = {440, 1}, dim_out = {1}, - sub_layers = layer_repo, + layer_repo = layer_repo, connections = { - ["<input>[1]"] = "main[1]", - ["main[1]"] = "ce_crit[1]", - ["<input>[2]"] = "ce_crit[2]", - ["ce_crit[1]"] = "<output>[1]" + {"<input>[1]", "main[1]", 0}, + {"main[1]", "ce_crit[1]", 0}, + {"<input>[2]", "ce_crit[2]", 0}, + {"ce_crit[1]", "<output>[1]", 0} } }, softmax_output = { dim_in = {440}, dim_out = {1959}, - sub_layers = layer_repo, + layer_repo = layer_repo, connections = { - ["<input>[1]"] = "main[1]", - ["main[1]"] = "softmax[1]", - ["softmax[1]"] = "<output>[1]" + {"<input>[1]", "main[1]", 0}, + {"main[1]", "softmax[1]", 0}, + {"softmax[1]", "<output>[1]", 0} } } } |