fix egs of transformer lm usage

deepspeech/decoders/recog.py

@@ -24,6 +24,7 @@ from .utils import add_results_to_json
 from deepspeech.exps import dynamic_import_tester
 from deepspeech.io.reader import LoadInputsAndTargets
 from deepspeech.models.asr_interface import ASRInterface
+from deepspeech.models.lm_interface import dynamic_import_lm
 from deepspeech.utils.log import Log
 
 logger = Log(__name__).getlog()
@@ -31,11 +32,15 @@ logger = Log(__name__).getlog()
 # NOTE: you need this func to generate our sphinx doc
 
 
+def get_config(config_path):
+    confs = CfgNode(new_allowed=True)
+    confs.merge_from_file(config_path)
+    return confs
+
+
 def load_trained_model(args):
     args.nprocs = args.ngpu
-    confs = CfgNode()
+    confs = get_config(args.model_conf)
-    confs.set_new_allowed(True)
-    confs.merge_from_file(args.model_conf)
     class_obj = dynamic_import_tester(args.model_name)
     exp = class_obj(confs, args)
     with exp.eval():
@@ -46,19 +51,11 @@ def load_trained_model(args):
     return model, char_list, exp, confs
 
 
-def get_config(config_path):
-    stream = open(config_path, mode='r', encoding="utf-8")
-    config = yaml.load(stream, Loader=yaml.FullLoader)
-    stream.close()
-    return config
-
-
 def load_trained_lm(args):
     lm_args = get_config(args.rnnlm_conf)
-    # NOTE: for a compatibility with less than 0.5.0 version models
+    lm_model_module = lm_args.model_module
-    lm_model_module = getattr(lm_args, "model_module", "default")
     lm_class = dynamic_import_lm(lm_model_module)
-    lm = lm_class(lm_args.model)
+    lm = lm_class(**lm_args.model)
     model_dict = paddle.load(args.rnnlm)
     lm.set_state_dict(model_dict)
     return lm

examples/librispeech/s2/local/recog.sh

@@ -11,9 +11,9 @@ tag=
 decode_config=conf/decode/decode.yaml
 
 # lm params
-lang_model=transformerLM.pdparams
-lmexpdir=exp/lm/transformer
 rnnlm_config_path=conf/lm/transformer.yaml
+lmexpdir=exp/lm
+lang_model=rnnlm.pdparams
 lmtag='transformer'
 
 train_set=train_960
@@ -53,6 +53,9 @@ if [[ ${config_path} =~ ^.*chunk_.*yaml$ ]];then
 fi
 echo "chunk mode: ${chunk_mode}"
 echo "decode conf: ${decode_config}"
+echo "lm conf: ${rnnlm_config_path}"
+echo "lm model: ${lmexpdir}/${lang_model}"
+
 
 # download language model
 #bash local/download_lm_en.sh
@@ -61,6 +64,13 @@ echo "decode conf: ${decode_config}"
 #fi
 
 
+# download rnnlm
+mkdir -p ${lmexpdir}
+if [ ! -f ${lmexpdir}/${lang_model} ]; then
+    wget -c -O ${lmexpdir}/${lang_model} https://deepspeech.bj.bcebos.com/transformer_lm/transformerLM.pdparams
+fi
+
+
 pids=() # initialize pids
 
 for dmethd in join_ctc; do

examples/librispeech/s2/run.sh

@@ -37,12 +37,9 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
     ./local/test.sh ${conf_path} ${dict_path} exp/${ckpt}/checkpoints/${avg_ckpt} || exit -1
 fi
 
-if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ] && ${use_lm} == true; then
+if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
     # join ctc decoder, use transformerlm to score
-    if [ ! -f exp/lm/transformer/transformerLM.pdparams ]; then
+    ./local/recog.sh  --ckpt_prefix exp/${ckpt}/checkpoints/${avg_ckpt}
-        wget https://deepspeech.bj.bcebos.com/transformer_lm/transformerLM.pdparams exp/lm/transformer/
-    fi
-    bash local/recog.sh  --ckpt_prefix exp/${ckpt}/checkpoints/${avg_ckpt}
 fi
 
 if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then