diff options
| -rw-r--r-- | nerv/examples/asr_trainer.lua | 23 | ||||
| -rw-r--r-- | nerv/examples/swb_baseline.lua | 7 | ||||
| -rw-r--r-- | nerv/examples/swb_baseline_basic.lua | 7 | ||||
| -rw-r--r-- | nerv/io/sgd_buffer.lua | 2 | ||||
| -rw-r--r-- | nerv/layer/mse.lua | 2 | ||||
| -rw-r--r-- | nerv/nn/layer_dag.lua | 27 |
6 files changed, 56 insertions, 12 deletions
diff --git a/nerv/examples/asr_trainer.lua b/nerv/examples/asr_trainer.lua index dcadfa3..5a50542 100644 --- a/nerv/examples/asr_trainer.lua +++ b/nerv/examples/asr_trainer.lua @@ -3,6 +3,7 @@ function build_trainer(ifname) param_repo:import(ifname, nil, gconf) local layer_repo = make_layer_repo(param_repo) local network = get_network(layer_repo) + local global_transf = get_global_transf(layer_repo) local input_order = get_input_order() local iterative_trainer = function (prefix, scp_file, bp) gconf.randomize = bp @@ -24,15 +25,29 @@ function build_trainer(ifname) -- break end local input = {} --- if gconf.cnt == 100 then break end - for i, id in ipairs(input_order) do +-- if gconf.cnt == 1000 then break end + for i, e in ipairs(input_order) do + local id = e.id if data[id] == nil then nerv.error("input data %s not found", id) end - table.insert(input, data[id]) + local transformed + if e.global_transf then + transformed = nerv.speech_utils.global_transf(data[id], + global_transf, + gconf.frm_ext or 0, + gconf.frm_trim or 0, + gconf) + else + transformed = data[id] + end + table.insert(input, transformed) end local output = {nerv.CuMatrixFloat(gconf.batch_size, 1)} - err_output = {input[1]:create()} + err_output = {} + for i = 1, #input do + table.insert(err_output, input[i]:create()) + end network:propagate(input, output) if bp then network:back_propagate(err_input, err_output, input, output) diff --git a/nerv/examples/swb_baseline.lua b/nerv/examples/swb_baseline.lua index 0e9f897..bbc6467 100644 --- a/nerv/examples/swb_baseline.lua +++ b/nerv/examples/swb_baseline.lua @@ -3,6 +3,7 @@ gconf = {lrate = 0.8, wcost = 1e-6, momentum = 0.9, cumat_type = nerv.CuMatrixFloat, mmat_type = nerv.MMatrixFloat, frm_ext = 5, + frm_trim = 5, tr_scp = "/slfs1/users/mfy43/swb_ivec/train_bp.scp", cv_scp = "/slfs1/users/mfy43/swb_ivec/train_cv.scp", htk_conf = "/slfs1/users/mfy43/swb_ivec/plp_0_d_a.conf", @@ -161,8 +162,7 @@ function make_readers(scp_file, layer_repo) dir = "*/", ext = "lab" } - }, - global_transf = layer_repo:get_layer("global_transf") + } }), data = {main_scp = 429, phone_state = 1}} } @@ -178,7 +178,8 @@ function make_buffer(readers) end function get_input_order() - return {"main_scp", "phone_state"} + return {{id = "main_scp", global_transf = true}, + {id = "phone_state"}} end function get_accuracy(layer_repo) diff --git a/nerv/examples/swb_baseline_basic.lua b/nerv/examples/swb_baseline_basic.lua index c47ec3e..71f04a3 100644 --- a/nerv/examples/swb_baseline_basic.lua +++ b/nerv/examples/swb_baseline_basic.lua @@ -3,6 +3,7 @@ gconf = {lrate = 0.8, wcost = 1e-6, momentum = 0.9, cumat_type = nerv.CuMatrixFloat, mmat_type = nerv.MMatrixFloat, frm_ext = 5, + frm_trim = 5, tr_scp = "/slfs1/users/mfy43/swb_ivec/train_bp.scp", cv_scp = "/slfs1/users/mfy43/swb_ivec/train_cv.scp", htk_conf = "/slfs1/users/mfy43/swb_ivec/plp_0_d_a.conf", @@ -124,8 +125,7 @@ function make_readers(scp_file, layer_repo) dir = "*/", ext = "lab" } - }, - global_transf = layer_repo:get_layer("global_transf") + } }), data = {main_scp = 429, phone_state = 1}} } @@ -141,7 +141,8 @@ function make_buffer(readers) end function get_input_order() - return {"main_scp", "phone_state"} + return {{id = "main_scp", global_transf = true}, + {id = "phone_state"}} end function get_accuracy(layer_repo) diff --git a/nerv/io/sgd_buffer.lua b/nerv/io/sgd_buffer.lua index 604fa07..f9d281c 100644 --- a/nerv/io/sgd_buffer.lua +++ b/nerv/io/sgd_buffer.lua @@ -91,7 +91,7 @@ function SGDBuffer:get_data() if not self:saturate() then return nil -- the remaining data cannot build a batch end - nerv.info("%.3fs to fill the buffer\n", os.clock() - t) + nerv.info("%.3fs to fill the buffer", os.clock() - t) end if self.head + batch_size > self.tail then return nil -- the remaining data cannot build a batch diff --git a/nerv/layer/mse.lua b/nerv/layer/mse.lua index 9a97add..2516998 100644 --- a/nerv/layer/mse.lua +++ b/nerv/layer/mse.lua @@ -34,7 +34,7 @@ function MSELayer:propagate(input, output) if output[1] ~= nil then output[1]:copy_fromd(mse_sum) end - self.total_mse = self.total_mse + mse_sum:colsum()[0] + self.total_mse = self.total_mse + mse_sum:colsum()[0][0] self.total_frames = self.total_frames + mse_sum:nrow() end diff --git a/nerv/nn/layer_dag.lua b/nerv/nn/layer_dag.lua index e9d4d86..25297c2 100644 --- a/nerv/nn/layer_dag.lua +++ b/nerv/nn/layer_dag.lua @@ -254,3 +254,30 @@ function DAGLayer:get_params() end return nerv.ParamRepo.merge(param_repos) end + +DAGLayer.PORT_TYPES = { + INPUT = {}, + OUTPUT = {}, + ERR_INPUT = {}, + ERR_OUTPUT = {} +} + +function DAGLayer:get_intermediate(id, port_type) + if id == "<input>" or id == "<output>" then + nerv.error("an actual real layer id is expected") + end + local layer = layers[id] + if layer == nil then + nerv.error("layer id %s not found", id) + end + if port_type == DAGLayer.PORT_TYPES.INPUT then + return layer.inputs + elseif port_type == DAGLayer.PORT_TYPES.OUTPUT then + return layer.outputs + elseif port_type == DAGLayer.PORT_TYPES.ERR_INPUT then + return layer.err_inputs + elseif port_type == DAGLayer.PORT_TYPES.ERR_OUTPUT then + return layer.err_outputs + end + nerv.error("unrecognized port type") +end |